diff --git a/README.md b/README.md
index ba5e6c029..4d4f0e57c 100644
--- a/README.md
+++ b/README.md
@@ -15,4 +15,4 @@ and benefit from contributions of other agency partners.
 
 ## Documentation
 
-https://activitysim.github.io/activitysim  
+https://activitysim.github.io/activitysim   
diff --git a/activitysim/core/simulate.py b/activitysim/core/simulate.py
index bedd3a562..c14939da9 100644
--- a/activitysim/core/simulate.py
+++ b/activitysim/core/simulate.py
@@ -445,15 +445,6 @@ def eval_utilities(spec, choosers, locals_d=None, trace_label=None,
                 # Cause all warnings to always be triggered.
                 warnings.simplefilter("always")
                 if expr.startswith('@'):
-                    tilde_idx = expr.find('~')
-                    if (tilde_idx > -1):
-                        if expr[tilde_idx + 1: tilde_idx + 3] != 'df':
-                            logger.warning(
-                                "Found a `~` operator in an expression being "
-                                "evaluated by the Python `eval()` rather than "
-                                "Pandas. This is probably a mistake since Python "
-                                "will evaluate `~False` as -1 and `~True` as -2."
-                            )
                     expression_value = eval(expr[1:], globals_dict, locals_dict)
 
                 else:
diff --git a/activitysim/examples/example_arc/configs/trip_destination.yaml b/activitysim/examples/example_arc/configs/trip_destination.yaml
index c885ea9a7..a6ee2e48e 100644
--- a/activitysim/examples/example_arc/configs/trip_destination.yaml
+++ b/activitysim/examples/example_arc/configs/trip_destination.yaml
@@ -14,7 +14,7 @@ DEST_CHOICE_SAMPLE_TABLE_NAME: trip_destination_sample
 # model-specific logsum-related settings
 TRIP_ORIGIN: origin
 ALT_DEST_COL_NAME: dest_zone_id
-PRIMARY_DEST: destination
+PRIMARY_DEST: tour_leg_dest # must be created in preprocessor
 
 REDUNDANT_TOURS_MERGED_CHOOSER_COLUMNS:
   - tour_mode
diff --git a/activitysim/examples/example_arc/configs/trip_destination_annotate_trips_preprocessor.csv b/activitysim/examples/example_arc/configs/trip_destination_annotate_trips_preprocessor.csv
index 1ba3afb70..e94b9ea22 100644
--- a/activitysim/examples/example_arc/configs/trip_destination_annotate_trips_preprocessor.csv
+++ b/activitysim/examples/example_arc/configs/trip_destination_annotate_trips_preprocessor.csv
@@ -10,3 +10,4 @@ Description,Target,Expression
 #,,not needed as school is not chosen as an intermediate trip destination
 #,_grade_school,"(df.primary_purpose == 'school') & reindex(persons.is_gradeschool, df.person_id)"
 #,size_segment,"df.primary_purpose.where(df.primary_purpose != 'school', np.where(_grade_school,'gradeschool', 'highschool'))"
+,tour_leg_dest,"np.where(df.outbound,reindex(tours.destination, df.tour_id), reindex(tours.origin, df.tour_id))"
\ No newline at end of file
diff --git a/activitysim/examples/example_mtc/configs/accessibility.csv b/activitysim/examples/example_mtc/configs/accessibility.csv
index 621387555..db2275546 100644
--- a/activitysim/examples/example_mtc/configs/accessibility.csv
+++ b/activitysim/examples/example_mtc/configs/accessibility.csv
@@ -21,12 +21,12 @@ auto off-peak total,auOpTotal,df.TOTEMP * _decay
 #,, assume peak outbound transit occurs in AM
 o-d peak transit ivt,_inVehicleTime,"skim_od[('WLK_TRN_WLK_IVT', 'AM')]"
 o-d peak transit ovt,_outOfVehicleTime,"skim_od[('WLK_TRN_WLK_IWAIT', 'AM')] + skim_od[('WLK_TRN_WLK_XWAIT', 'AM')] + skim_od[('WLK_TRN_WLK_WACC', 'AM')] + skim_od[('WLK_TRN_WLK_WAUX', 'AM')] + skim_od[('WLK_TRN_WLK_WEGR', 'AM')]"
-o-d peak transit time,_trPkTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
+o-d peak transit time,_trPkTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
 #,, assume peak inbound transit occurs in PM
 d-o peak transit ivt,_inVehicleTime,"skim_do[('WLK_TRN_WLK_IVT', 'PM')]"
 d-o peak transit ovt,_outOfVehicleTime,"skim_do[('WLK_TRN_WLK_IWAIT', 'PM')] + skim_do[('WLK_TRN_WLK_XWAIT', 'PM')] + skim_do[('WLK_TRN_WLK_WACC', 'PM')] + skim_do[('WLK_TRN_WLK_WAUX', 'PM')] + skim_do[('WLK_TRN_WLK_WEGR', 'PM')]"
-d-o peak transit time,_trPkTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
-peak transit time,_trPkTime,_trPkTime_od + _trPkTime_do
+d-o peak transit time,_trPkTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
+peak transit time,_trPkTime,(_trPkTime_od + _trPkTime_do).clip(0)
 round trip path is available,_rt_available,(_trPkTime_od > 0) & (_trPkTime_do > 0)
 decay function,_decay,_rt_available * exp(_trPkTime * dispersion_parameter_transit)
 transit peak retail,trPkRetail,df.RETEMPN * _decay
@@ -37,12 +37,12 @@ transit peak total,trPkTotal,df.TOTEMP * _decay
 #,, assume off-peak outbound transit occurs in the MD time period
 o-d off-peak transit ivt,_inVehicleTime,"skim_od[('WLK_TRN_WLK_IVT', 'MD')]"
 o-d off-peak transit ovt,_outOfVehicleTime,"skim_od[('WLK_TRN_WLK_IWAIT', 'MD')] + skim_od[('WLK_TRN_WLK_XWAIT', 'MD')] + skim_od[('WLK_TRN_WLK_WACC', 'MD')] + skim_od[('WLK_TRN_WLK_WAUX', 'MD')] + skim_od[('WLK_TRN_WLK_WEGR', 'MD')]"
-o-d off-peak transit time,_trOpTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
+o-d off-peak transit time,_trOpTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
 #,, assume off-peak inbound transit occurs in the MD time period
 d-o off-peak transit ivt,_inVehicleTime,"skim_do[('WLK_TRN_WLK_IVT', 'MD')]"
 d-o off-peak transit ovt,_outOfVehicleTime,"skim_do[('WLK_TRN_WLK_IWAIT', 'MD')] + skim_do[('WLK_TRN_WLK_XWAIT', 'MD')] + skim_do[('WLK_TRN_WLK_WACC', 'MD')] + skim_do[('WLK_TRN_WLK_WAUX', 'MD')] + skim_do[('WLK_TRN_WLK_WEGR', 'MD')]"
-d-o off-peak transit time,_trOpTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
-peak transit time,_trOpTime,_trOpTime_od + _trOpTime_do
+d-o off-peak transit time,_trOpTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
+peak transit time,_trOpTime,(_trOpTime_od + _trOpTime_do).clip(0)
 #,,FIXME - _rt_available calculation appears to be wrong in mtctm1 accessibility.job
 #round trip path is available,_rt_available,(_trOpTime > 0)
 round trip path is available,_rt_available,(_trOpTime_od > 0) & (_trOpTime_do > 0)
diff --git a/activitysim/examples/example_mtc/configs/annotate_persons_workplace.csv b/activitysim/examples/example_mtc/configs/annotate_persons_workplace.csv
index 88ef9487f..87a5853d6 100644
--- a/activitysim/examples/example_mtc/configs/annotate_persons_workplace.csv
+++ b/activitysim/examples/example_mtc/configs/annotate_persons_workplace.csv
@@ -16,14 +16,14 @@ work_zone_area_type,work_zone_area_type,"reindex(land_use.area_type, persons.wor
 ,_work_walk_available,(_walk_time_home_to_work > 0) & (_walk_time_work_to_home > 0)
 ,_roundtrip_walk_time_to_work,"np.where(_work_walk_available, _walk_time_home_to_work + _walk_time_work_to_home, _MAX_TIME_TO_WORK)"
 #,,_roundtrip_transit_time_to_work
-,_transit_ivt_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))/100"
-,_transit_ivt_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))/100"
+,_transit_ivt_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_ivt_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))/TRANSIT_SCALE_FACTOR"
 ,_work_transit_available,(_transit_ivt_home_to_work > 0) & (_transit_ivt_work_to_home > 0)
-,_transit_iwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_IWAIT', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_IWAIT', 'MD'))/100"
-,_transit_xwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_XWAIT', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_XWAIT', 'MD'))/100"
-,_transit_waux,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WAUX', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WAUX', 'MD'))/100"
-,_transit_wacc,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WACC', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WACC', 'MD'))/100"
-,_transit_wegr,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WEGR', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WEGR', 'MD'))/100"
+,_transit_iwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_IWAIT', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_IWAIT', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_xwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_XWAIT', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_XWAIT', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_waux,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WAUX', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WAUX', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_wacc,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WACC', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WACC', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_wegr,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WEGR', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WEGR', 'MD'))/TRANSIT_SCALE_FACTOR"
 ,_roundtrip_transit_time_to_work,_transit_ivt_home_to_work + _transit_ivt_work_to_home + _transit_iwait + _transit_xwait + _transit_waux + _transit_wacc + _transit_wegr
 #,,work_auto_savings_ratio
 ,_min_work_walk_transit,"np.where(_work_transit_available, np.minimum(_roundtrip_transit_time_to_work, _roundtrip_walk_time_to_work), _roundtrip_walk_time_to_work)"
diff --git a/activitysim/examples/example_mtc/configs/constants.yaml b/activitysim/examples/example_mtc/configs/constants.yaml
index 7d3864fd9..b0bd5a1f3 100644
--- a/activitysim/examples/example_mtc/configs/constants.yaml
+++ b/activitysim/examples/example_mtc/configs/constants.yaml
@@ -61,3 +61,8 @@ PTYPE_NAME:
 CDAP_ACTIVITY_MANDATORY: M
 CDAP_ACTIVITY_NONMANDATORY: N
 CDAP_ACTIVITY_HOME: H
+
+# Correction for transit skim expressions
+# e.g. MTC transit skims (Cube TRANPLAN skims) use scaled ints and
+# therefore need to be divided by the scale factor if used in expressions
+TRANSIT_SCALE_FACTOR: 100
diff --git a/activitysim/examples/example_mtc/configs/tour_mode_choice.csv b/activitysim/examples/example_mtc/configs/tour_mode_choice.csv
index d15a4c962..8f6e7aadb 100644
--- a/activitysim/examples/example_mtc/configs/tour_mode_choice.csv
+++ b/activitysim/examples/example_mtc/configs/tour_mode_choice.csv
@@ -70,89 +70,89 @@ util_SHARED3PAY_Two_person_household,SHARED3PAY - Two person household,@(df.hhsi
 util_SHARED3PAY_Person_is_16_years_old_or_older,SHARED3PAY - Person is 16 years old or older,@(df.age >= 16),,,,,,coef_age16p_sr_multiplier,,,,,,,,,,,,,,,
 #,Walk,,,,,,,,,,,,,,,,,,,,,,
 #,FIXME - skims aren't symmetrical,so we have to make sure they can get back,,,,,,,,,,,,,,,,,,,,,
-util_WALK_Time_up_to_2_miles,WALK - Time up to 2 miles,@walktimeshort_multiplier * (df.distance_walk_od.clip(upper=walkThresh) + df.distance_walk_od.clip(upper=walkThresh))*60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
-util_WALK_Time_beyond_2_of_a_miles,WALK - Time beyond 2 of a miles,@walktimelong_multiplier * ((df.distance_walk_od - walkThresh).clip(lower=0) + (df.distance_walk_od - walkThresh).clip(lower=0))*60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
+util_WALK_Time_up_to_2_miles,WALK - Time up to 2 miles,@walktimeshort_multiplier * (od_skims['DISTWALK'].clip(upper=walkThresh) + od_skims.reverse('DISTWALK').clip(upper=walkThresh))*60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
+util_WALK_Time_beyond_2_of_a_miles,WALK - Time beyond 2 of a miles,@walktimelong_multiplier * ((od_skims['DISTWALK'] - walkThresh).clip(lower=0) + (od_skims.reverse('DISTWALK') - walkThresh).clip(lower=0))*60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
 util_WALK_Destination_zone_densityIndex,WALK - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,coef_ivt,,,,,,,,,,,,,,
 util_WALK_Topology,WALK - Topology,@coef_topology_walk_multiplier * df.dest_topology,,,,,,,coef_ivt,,,,,,,,,,,,,,
 #,Bike,,,,,,,,,,,,,,,,,,,,,,
 #,FIXME - skims aren't symmetrical,so we have to make sure they can get back,,,,,,,,,,,,,,,,,,,,,
 util_BIKE_Unavailable_if_didn't_bike_to_work,BIKE - Unavailable if didn't bike to work,is_atwork_subtour & ~work_tour_is_bike,,,,,,,,-999,,,,,,,,,,,,,
-util_BIKE_Time_up_to_6_miles,BIKE - Time up to 6 miles,@biketimeshort_multiplier * (df.distance_bike_od.clip(upper=bikeThresh) + df.distance_bike_od.clip(upper=bikeThresh))*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
-util_BIKE_Time_beyond_6_of_a_miles,BIKE - Time beyond 6 of a miles,@biketimelong_multiplier * ((df.distance_bike_od-bikeThresh).clip(lower=0) + (df.distance_bike_od-bikeThresh).clip(lower=0))*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
+util_BIKE_Time_up_to_6_miles,BIKE - Time up to 6 miles,@biketimeshort_multiplier * (od_skims['DISTBIKE'].clip(upper=bikeThresh) + od_skims.reverse('DISTBIKE').clip(upper=bikeThresh))*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
+util_BIKE_Time_beyond_6_of_a_miles,BIKE - Time beyond 6 of a miles,@biketimelong_multiplier * ((od_skims['DISTBIKE']-bikeThresh).clip(lower=0) + (od_skims.reverse('DISTBIKE')-bikeThresh).clip(lower=0))*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
 util_BIKE_Destination_zone_densityIndex,BIKE - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,coef_ivt,,,,,,,,,,,,,
 util_BIKE_Topology,BIKE - Topology,@coef_topology_bike_multiplier * df.dest_topology,,,,,,,,coef_ivt,,,,,,,,,,,,,
 #,Walk to Local,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_LOC_Unavailable,WALK_LOC - Unavailable,walk_local_available == False,,,,,,,,,-999,,,,,,,,,,,,
-util_WALK_LOC_In_vehicle_time,WALK_LOC - In-vehicle time,@(odt_skims['WLK_LOC_WLK_TOTIVT']/100 + dot_skims['WLK_LOC_WLK_TOTIVT']/100),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Short_iwait_time,WALK_LOC - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_LOC_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_LOC_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Long_iwait_time,WALK_LOC - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_LOC_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_LOC_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_transfer_wait_time,WALK_LOC - transfer wait time,@xwait_multiplier * (odt_skims['WLK_LOC_WLK_XWAIT']/100 + dot_skims['WLK_LOC_WLK_XWAIT']/100),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_In_vehicle_time,WALK_LOC - In-vehicle time,@(odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Short_iwait_time,WALK_LOC - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Long_iwait_time,WALK_LOC - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_transfer_wait_time,WALK_LOC - transfer wait time,@xwait_multiplier * (odt_skims['WLK_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_number_of_transfers,WALK_LOC - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_LOC_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_LOC_WLK_BOARDS']-1).clip(0)),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Walk_access_time,WALK_LOC - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Walk_egress_time,WALK_LOC - Walk egress time,@2 * wegr_multiplier * df.destination_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Walk_other_time,WALK_LOC - Walk other time,@waux_multiplier * (odt_skims['WLK_LOC_WLK_WAUX']/100 + dot_skims['WLK_LOC_WLK_WAUX']/100),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Walk_other_time,WALK_LOC - Walk other time,@waux_multiplier * (odt_skims['WLK_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Fare,WALK_LOC - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LOC_WLK_FAR'] + dot_skims['WLK_LOC_WLK_FAR']),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Destination_zone_densityIndex,WALK_LOC - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Topology,WALK_LOC - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Person_is_less_than_10_years_old,WALK_LOC - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,coef_age010_trn_multiplier,,,,,,,,,,,,
 #,Walk to Light rail/Ferry,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_LRF_Unavailable,WALK_LRF - Unavailable,walk_lrf_available == False,,,,,,,,,,-999,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time,WALK_LRF - In-vehicle time,@(odt_skims['WLK_LRF_WLK_TOTIVT']/100 + dot_skims['WLK_LRF_WLK_TOTIVT']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time,WALK_LRF - In-vehicle time,@(odt_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
 #, FIXME coefficients below are wrong or needlessly complex? could be re-expressed to avoid subtract?,,,,,,,,,,,,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time_on_Light_Rail,WALK_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(ivt_lrt_multiplier-1)*(odt_skims['WLK_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_WLK_KEYIVT']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time_on_Ferry,WALK_LRF - In-vehicle time on Ferry (incremental w/keyivt),@(ivt_ferry_multiplier-ivt_lrt_multiplier)*(odt_skims['WLK_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Short_iwait_time,WALK_LRF - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_LRF_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_LRF_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Long_iwait_time,WALK_LRF - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_LRF_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_LRF_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_transfer_wait_time,WALK_LRF - transfer wait time,@xwait_multiplier * (odt_skims['WLK_LRF_WLK_XWAIT']/100 + dot_skims['WLK_LRF_WLK_XWAIT']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time_on_Light_Rail,WALK_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(ivt_lrt_multiplier-1)*(odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time_on_Ferry,WALK_LRF - In-vehicle time on Ferry (incremental w/keyivt),@(ivt_ferry_multiplier-ivt_lrt_multiplier)*(odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Short_iwait_time,WALK_LRF - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Long_iwait_time,WALK_LRF - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_transfer_wait_time,WALK_LRF - transfer wait time,@xwait_multiplier * (odt_skims['WLK_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_number_of_transfers,WALK_LRF - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_LRF_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_LRF_WLK_BOARDS']-1).clip(0)),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Walk_access_time,WALK_LRF - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Walk_egress_time,WALK_LRF - Walk egress time,@2 * wegr_multiplier * df.destination_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Walk_other_time,WALK_LRF - Walk other time,@waux_multiplier * (odt_skims['WLK_LRF_WLK_WAUX']/100 + dot_skims['WLK_LRF_WLK_WAUX']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Walk_other_time,WALK_LRF - Walk other time,@waux_multiplier * (odt_skims['WLK_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Fare,WALK_LRF - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LRF_WLK_FAR'] + dot_skims['WLK_LRF_WLK_FAR']),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Destination_zone_densityIndex,WALK_LRF - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Topology,WALK_LRF - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Person_is_less_than_10_years_old,WALK_LRF - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,coef_age010_trn_multiplier,,,,,,,,,,,
 #,Walk to Express bus,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_EXP_Unavailable,WALK_EXP - Unavailable,walk_express_available == False,,,,,,,,,,,-999,,,,,,,,,,
-util_WALK_EXP_In_vehicle_time,WALK_EXP - In-vehicle time,@(odt_skims['WLK_EXP_WLK_TOTIVT']/100 + dot_skims['WLK_EXP_WLK_TOTIVT']/100),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_In_vehicle_time_on_Express_bus,WALK_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier - 1)*(odt_skims['WLK_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_WLK_KEYIVT']/100),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Short_iwait_time,WALK_EXP - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_EXP_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_EXP_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Long_iwait_time,WALK_EXP - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_EXP_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_EXP_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_transfer_wait_time,WALK_EXP - transfer wait time,@xwait_multiplier * (odt_skims['WLK_EXP_WLK_XWAIT']/100 + dot_skims['WLK_EXP_WLK_XWAIT']/100),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_In_vehicle_time,WALK_EXP - In-vehicle time,@(odt_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_In_vehicle_time_on_Express_bus,WALK_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier - 1)*(odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Short_iwait_time,WALK_EXP - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Long_iwait_time,WALK_EXP - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_transfer_wait_time,WALK_EXP - transfer wait time,@xwait_multiplier * (odt_skims['WLK_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_number_of_transfers,WALK_EXP - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_EXP_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_EXP_WLK_BOARDS']-1).clip(0)),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Walk_access_time,WALK_EXP - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Walk_egress_time,WALK_EXP - Walk egress time,@2 * wegr_multiplier * df.destination_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Walk_other_time,WALK_EXP - Walk other time,@waux_multiplier * (odt_skims['WLK_EXP_WLK_WAUX']/100 + dot_skims['WLK_EXP_WLK_WAUX']/100),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Walk_other_time,WALK_EXP - Walk other time,@waux_multiplier * (odt_skims['WLK_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Fare,WALK_EXP - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_EXP_WLK_FAR'] + dot_skims['WLK_EXP_WLK_FAR']),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Destination_zone_densityIndex,WALK_EXP - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Topology,WALK_EXP - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Person_is_less_than_10_years_old,WALK_EXP - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,,coef_age010_trn_multiplier,,,,,,,,,,
 #,Walk to Heavy Rail,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_HVY_Unavailable,WALK_HVY - Unavailable,walk_heavyrail_available == False,,,,,,,,,,,,-999,,,,,,,,,
-util_WALK_HVY_In_vehicle_time,WALK_HVY - In-vehicle time,@(odt_skims['WLK_HVY_WLK_TOTIVT']/100 + dot_skims['WLK_HVY_WLK_TOTIVT']/100),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_In_vehicle_time_on_heavy_rail,WALK_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * (odt_skims['WLK_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_WLK_KEYIVT']/100),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Short_iwait_time,WALK_HVY - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_HVY_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_HVY_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Long_iwait_time,WALK_HVY - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_HVY_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_HVY_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_transfer_wait_time,WALK_HVY - transfer wait time,@xwait_multiplier * (odt_skims['WLK_HVY_WLK_XWAIT']/100 + dot_skims['WLK_HVY_WLK_XWAIT']/100),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_In_vehicle_time,WALK_HVY - In-vehicle time,@(odt_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_In_vehicle_time_on_heavy_rail,WALK_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * (odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Short_iwait_time,WALK_HVY - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Long_iwait_time,WALK_HVY - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_transfer_wait_time,WALK_HVY - transfer wait time,@xwait_multiplier * (odt_skims['WLK_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_number_of_transfers,WALK_HVY - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_HVY_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_HVY_WLK_BOARDS']-1).clip(0)),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Walk_access_time,WALK_HVY - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Walk_egress_time,WALK_HVY - Walk egress time,@wegr_multiplier * 2 *df.destination_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Walk_other_time,WALK_HVY - Walk other time,@waux_multiplier * (odt_skims['WLK_HVY_WLK_WAUX']/100 + dot_skims['WLK_HVY_WLK_WAUX']/100),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Walk_other_time,WALK_HVY - Walk other time,@waux_multiplier * (odt_skims['WLK_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Fare,WALK_HVY - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_HVY_WLK_FAR'] + dot_skims['WLK_HVY_WLK_FAR']),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Destination_zone_densityIndex,WALK_HVY - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Topology,WALK_HVY - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Person_is_less_than_10_years_old,WALK_HVY - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,,,coef_age010_trn_multiplier,,,,,,,,,
 #,Walk to Commuter rail,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_COM_Unavailable,WALK_COM - Unavailable,walk_commuter_available == False,,,,,,,,,,,,,-999,,,,,,,,
-util_WALK_COM_In_vehicle_time,WALK_COM - In-vehicle time,@(odt_skims['WLK_COM_WLK_TOTIVT']/100 + dot_skims['WLK_COM_WLK_TOTIVT']/100),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_In_vehicle_time_on_commuter_rail,WALK_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * (odt_skims['WLK_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_WLK_KEYIVT']/100),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Short_iwait_time,WALK_COM - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_COM_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_COM_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Long_iwait_time,WALK_COM - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_COM_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_COM_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_transfer_wait_time,WALK_COM - transfer wait time,@xwait_multiplier * (odt_skims['WLK_COM_WLK_XWAIT']/100 + dot_skims['WLK_COM_WLK_XWAIT']/100),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_In_vehicle_time,WALK_COM - In-vehicle time,@(odt_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_In_vehicle_time_on_commuter_rail,WALK_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * (odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Short_iwait_time,WALK_COM - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Long_iwait_time,WALK_COM - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_transfer_wait_time,WALK_COM - transfer wait time,@xwait_multiplier * (odt_skims['WLK_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_number_of_transfers,WALK_COM - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_COM_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_COM_WLK_BOARDS']-1).clip(0)),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Walk_access_time,WALK_COM - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Walk_egress_time,WALK_COM - Walk egress time,@2 * wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Walk_other_time,WALK_COM - Walk other time,@waux_multiplier * (odt_skims['WLK_COM_WLK_WAUX']/100 + dot_skims['WLK_COM_WLK_WAUX']/100),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Walk_other_time,WALK_COM - Walk other time,@waux_multiplier * (odt_skims['WLK_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Fare,WALK_COM - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_COM_WLK_FAR'] + dot_skims['WLK_COM_WLK_FAR']),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Destination_zone_densityIndex,WALK_COM - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Topology,WALK_COM - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,coef_ivt,,,,,,,,
@@ -161,17 +161,17 @@ util_WALK_COM_Person_is_less_than_10_years_old,WALK_COM - Person is less than 10
 util_DRIVE_LOC_Unavailable,DRIVE_LOC - Unavailable,drive_local_available == False,,,,,,,,,,,,,,-999,,,,,,,
 util_DRIVE_LOC_Unavailable_for_zero_auto_households,DRIVE_LOC - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,-999,,,,,,,
 util_DRIVE_LOC_Unavailable_for_persons_less_than_16,DRIVE_LOC - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,-999,,,,,,,
-util_DRIVE_LOC_In_vehicle_time,DRIVE_LOC - In-vehicle time,@(odt_skims['DRV_LOC_WLK_TOTIVT']/100 + dot_skims['WLK_LOC_DRV_TOTIVT']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Short_iwait_time,DRIVE_LOC - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_LOC_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_LOC_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Long_iwait_time,DRIVE_LOC - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_LOC_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_LOC_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_transfer_wait_time,DRIVE_LOC - transfer wait time,@xwait_multiplier * (odt_skims['DRV_LOC_WLK_XWAIT']/100 + dot_skims['WLK_LOC_DRV_XWAIT']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_In_vehicle_time,DRIVE_LOC - In-vehicle time,@(odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Short_iwait_time,DRIVE_LOC - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_LOC_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Long_iwait_time,DRIVE_LOC - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_LOC_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_transfer_wait_time,DRIVE_LOC - transfer wait time,@xwait_multiplier * (odt_skims['DRV_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_number_of_transfers,DRIVE_LOC - number of transfers,@xfers_wlk_multiplier * ((odt_skims['DRV_LOC_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_LOC_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Drive_time,DRIVE_LOC - Drive time,@dtim_multiplier * (odt_skims['DRV_LOC_WLK_DTIM']/100 + dot_skims['WLK_LOC_DRV_DTIM']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Drive_time,DRIVE_LOC - Drive time,@dtim_multiplier * (odt_skims['DRV_LOC_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Walk_access_time,DRIVE_LOC - Walk access time,@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Walk_egress_time,DRIVE_LOC - Walk egress time (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Walk_other_time,DRIVE_LOC - Walk other time,@waux_multiplier * (odt_skims['DRV_LOC_WLK_WAUX']/100 + dot_skims['WLK_LOC_DRV_WAUX']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Fare_and_operating_cost,DRIVE_LOC - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_LOC_WLK_FAR'] + dot_skims['WLK_LOC_DRV_FAR']) + ((odt_skims['DRV_LOC_WLK_DDIST']/100+dot_skims['WLK_LOC_DRV_DDIST']/100) * costPerMile)),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_LOC_WLK_DDIST']/100+ dot_skims['WLK_LOC_DRV_DDIST']/100)/ (df.distance*2)),,,,,,,,,,,,,,1,,,,,,,
+util_DRIVE_LOC_Walk_other_time,DRIVE_LOC - Walk other time,@waux_multiplier * (odt_skims['DRV_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Fare_and_operating_cost,DRIVE_LOC - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_LOC_WLK_FAR'] + dot_skims['WLK_LOC_DRV_FAR']) + ((odt_skims['DRV_LOC_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_LOC_DRV_DDIST']/TRANSIT_SCALE_FACTOR) * costPerMile)),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_LOC_WLK_DDIST']/TRANSIT_SCALE_FACTOR+ dot_skims['WLK_LOC_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']*2)),,,,,,,,,,,,,,1,,,,,,,
 util_DRIVE_LOC_Destination_zone_densityIndex,DRIVE_LOC - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Topology,DRIVE_LOC - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Person_is_less_than_10_years_old,DRIVE_LOC - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,coef_age010_trn_multiplier,,,,,,,
@@ -179,19 +179,19 @@ util_DRIVE_LOC_Person_is_less_than_10_years_old,DRIVE_LOC - Person is less than
 util_DRIVE_LRF_Unavailable,DRIVE_LRF - Unavailable,drive_lrf_available == False,,,,,,,,,,,,,,,-999,,,,,,
 util_DRIVE_LRF_Unavailable_for_zero_auto_households,DRIVE_LRF - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,-999,,,,,,
 util_DRIVE_LRF_Unavailable_for_persons_less_than_16,DRIVE_LRF - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,-999,,,,,,
-util_DRIVE_LRF_In_vehicle_time,DRIVE_LRF - In-vehicle time,@(odt_skims['DRV_LRF_WLK_TOTIVT']/100 + dot_skims['WLK_LRF_DRV_TOTIVT']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_In_vehicle_time_on_Light_Rail,DRIVE_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(ivt_lrt_multiplier-1) * (odt_skims['DRV_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_DRV_KEYIVT']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_In_vehicle_time_on_Ferry,DRIVE_LRF - In-vehicle time on Ferry (incremental w/ keyivt),@(ivt_ferry_multiplier-ivt_lrt_multiplier)*(odt_skims['DRV_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_DRV_FERRYIVT']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Short_iwait_time,DRIVE_LRF - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_LRF_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_LRF_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Long_iwait_time,DRIVE_LRF - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_LRF_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_LRF_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_transfer_wait_time,DRIVE_LRF - transfer wait time,@xwait_multiplier * (odt_skims['DRV_LRF_WLK_XWAIT']/100 + dot_skims['WLK_LRF_DRV_XWAIT']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_In_vehicle_time,DRIVE_LRF - In-vehicle time,@(odt_skims['DRV_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_In_vehicle_time_on_Light_Rail,DRIVE_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(ivt_lrt_multiplier-1) * (odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_In_vehicle_time_on_Ferry,DRIVE_LRF - In-vehicle time on Ferry (incremental w/ keyivt),@(ivt_ferry_multiplier-ivt_lrt_multiplier)*(odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_FERRYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Short_iwait_time,DRIVE_LRF - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_LRF_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Long_iwait_time,DRIVE_LRF - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_LRF_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_transfer_wait_time,DRIVE_LRF - transfer wait time,@xwait_multiplier * (odt_skims['DRV_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_number_of_transfers,DRIVE_LRF - number of transfers,@xfers_drv_multiplier * ((odt_skims['DRV_LRF_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_LRF_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Drive_time,DRIVE_LRF - Drive time,@dtim_multiplier * (odt_skims['DRV_LRF_WLK_DTIM']/100 + dot_skims['WLK_LRF_DRV_DTIM']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Drive_time,DRIVE_LRF - Drive time,@dtim_multiplier * (odt_skims['DRV_LRF_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Walk_access_time,DRIVE_LRF - Walk access time (at attraction end),@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Walk_egress_time,DRIVE_LRF - Walk egress time (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Walk_other_time,DRIVE_LRF - Walk other time,@waux_multiplier * (odt_skims['DRV_LRF_WLK_WAUX']/100 + dot_skims['WLK_LRF_DRV_WAUX']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Fare_and_operating_cost,DRIVE_LRF - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_LRF_WLK_FAR']+dot_skims['WLK_LRF_DRV_FAR']) + ((odt_skims['DRV_LRF_WLK_DDIST']/100+dot_skims['WLK_LRF_DRV_DDIST']/100) *costPerMile)),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_LRF_WLK_DDIST']/100+ dot_skims['WLK_LRF_DRV_DDIST']/100)/ (df.distance*2)),,,,,,,,,,,,,,,1,,,,,,
+util_DRIVE_LRF_Walk_other_time,DRIVE_LRF - Walk other time,@waux_multiplier * (odt_skims['DRV_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Fare_and_operating_cost,DRIVE_LRF - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_LRF_WLK_FAR']+dot_skims['WLK_LRF_DRV_FAR']) + ((odt_skims['DRV_LRF_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_LRF_DRV_DDIST']/TRANSIT_SCALE_FACTOR) *costPerMile)),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_LRF_WLK_DDIST']/TRANSIT_SCALE_FACTOR+ dot_skims['WLK_LRF_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']*2)),,,,,,,,,,,,,,,1,,,,,,
 util_DRIVE_LRF_Destination_zone_densityIndex,DRIVE_LRF - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Topology,DRIVE_LRF - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Person_is_less_than_10_years_old,DRIVE_LRF - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,coef_age010_trn_multiplier,,,,,,
@@ -199,18 +199,18 @@ util_DRIVE_LRF_Person_is_less_than_10_years_old,DRIVE_LRF - Person is less than
 util_DRIVE_EXP_Unavailable,DRIVE_EXP - Unavailable,drive_express_available == False,,,,,,,,,,,,,,,,-999,,,,,
 util_DRIVE_EXP_Unavailable_for_zero_auto_households,DRIVE_EXP - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,-999,,,,,
 util_DRIVE_EXP_Unavailable_for_persons_less_than_16,DRIVE_EXP - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,-999,,,,,
-util_DRIVE_EXP_In_vehicle_time,DRIVE_EXP - In-vehicle time,@(odt_skims['DRV_EXP_WLK_TOTIVT']/100 + dot_skims['WLK_EXP_DRV_TOTIVT']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_In_vehicle_time_on_Express_bus,DRIVE_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier-1) * (odt_skims['DRV_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_DRV_KEYIVT']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Short_iwait_time,DRIVE_EXP - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_EXP_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_EXP_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Long_iwait_time,DRIVE_EXP - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_EXP_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_EXP_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_transfer_wait_time,DRIVE_EXP - transfer wait time,@xwait_multiplier * (odt_skims['DRV_EXP_WLK_XWAIT']/100 + dot_skims['WLK_EXP_DRV_XWAIT']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_In_vehicle_time,DRIVE_EXP - In-vehicle time,@(odt_skims['DRV_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_In_vehicle_time_on_Express_bus,DRIVE_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier-1) * (odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Short_iwait_time,DRIVE_EXP - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_EXP_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Long_iwait_time,DRIVE_EXP - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_EXP_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_transfer_wait_time,DRIVE_EXP - transfer wait time,@xwait_multiplier * (odt_skims['DRV_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_number_of_transfers,DRIVE_EXP - number of transfers,@xfers_drv_multiplier * ((odt_skims['DRV_EXP_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_EXP_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Drive_time,DRIVE_EXP - Drive time,@dtim_multiplier * (odt_skims['DRV_EXP_WLK_DTIM']/100 + dot_skims['WLK_EXP_DRV_DTIM']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Drive_time,DRIVE_EXP - Drive time,@dtim_multiplier * (odt_skims['DRV_EXP_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Walk_access_time,DRIVE_EXP - Walk access time (at attraction end),@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Walk_egress_ime,DRIVE_EXP - Walk egress ime (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Walk_other_time,DRIVE_EXP - Walk other time,@waux_multiplier * (odt_skims['DRV_EXP_WLK_WAUX']/100 + dot_skims['WLK_EXP_DRV_WAUX']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Fare_and_operating_cost,DRIVE_EXP - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_EXP_WLK_FAR']+dot_skims['WLK_EXP_DRV_FAR']) + ((odt_skims['DRV_EXP_WLK_DDIST']/100+dot_skims['WLK_EXP_DRV_DDIST']/100) *costPerMile)),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_EXP_WLK_DDIST']/100+ dot_skims['WLK_EXP_DRV_DDIST']/100)/ (df.distance*2)),,,,,,,,,,,,,,,,1,,,,,
+util_DRIVE_EXP_Walk_other_time,DRIVE_EXP - Walk other time,@waux_multiplier * (odt_skims['DRV_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Fare_and_operating_cost,DRIVE_EXP - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_EXP_WLK_FAR']+dot_skims['WLK_EXP_DRV_FAR']) + ((odt_skims['DRV_EXP_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_EXP_DRV_DDIST']/TRANSIT_SCALE_FACTOR) *costPerMile)),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_EXP_WLK_DDIST']/TRANSIT_SCALE_FACTOR+ dot_skims['WLK_EXP_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']*2)),,,,,,,,,,,,,,,,1,,,,,
 util_DRIVE_EXP_Destination_zone_densityIndex,DRIVE_EXP - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Topology,DRIVE_EXP - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Person_is_less_than_10_years_old,DRIVE_EXP - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,coef_age010_trn_multiplier,,,,,
@@ -218,18 +218,18 @@ util_DRIVE_EXP_Person_is_less_than_10_years_old,DRIVE_EXP - Person is less than
 util_DRIVE_HVY_Unavailable,DRIVE_HVY - Unavailable,drive_heavyrail_available == False,,,,,,,,,,,,,,,,,-999,,,,
 util_DRIVE_HVY_Unavailable_for_zero_auto_households,DRIVE_HVY - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,,-999,,,,
 util_DRIVE_HVY_Unavailable_for_persons_less_than_16,DRIVE_HVY - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,-999,,,,
-util_DRIVE_HVY_In_vehicle_time,DRIVE_HVY - In-vehicle time,@(odt_skims['DRV_HVY_WLK_TOTIVT']/100 + dot_skims['WLK_HVY_DRV_TOTIVT']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_In_vehicle_time_on_heavy_rail,DRIVE_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * (odt_skims['DRV_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_DRV_KEYIVT']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Short_iwait_time,DRIVE_HVY - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_HVY_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_HVY_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Long_iwait_time,DRIVE_HVY - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_HVY_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_HVY_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_transfer_wait_time,DRIVE_HVY - transfer wait time,@xwait_multiplier * (odt_skims['DRV_HVY_WLK_XWAIT']/100 + dot_skims['WLK_HVY_DRV_XWAIT']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_In_vehicle_time,DRIVE_HVY - In-vehicle time,@(odt_skims['DRV_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_In_vehicle_time_on_heavy_rail,DRIVE_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * (odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Short_iwait_time,DRIVE_HVY - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_HVY_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Long_iwait_time,DRIVE_HVY - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_HVY_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_transfer_wait_time,DRIVE_HVY - transfer wait time,@xwait_multiplier * (odt_skims['DRV_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_number_of_transfers,DRIVE_HVY - number of transfers,@xfers_drv_multiplier * ((odt_skims['DRV_HVY_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_HVY_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Drive_time,DRIVE_HVY - Drive time,@dtim_multiplier * (odt_skims['DRV_HVY_WLK_DTIM']/100 + dot_skims['WLK_HVY_DRV_DTIM']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Drive_time,DRIVE_HVY - Drive time,@dtim_multiplier * (odt_skims['DRV_HVY_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Walk_access_time,DRIVE_HVY - Walk access time (at attraction end),@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Walk_egress_time,DRIVE_HVY - Walk egress time (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Walk_other_time,DRIVE_HVY - Walk other time,@waux_multiplier * (odt_skims['DRV_HVY_WLK_WAUX']/100 + dot_skims['WLK_HVY_DRV_WAUX']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Fare_and_operating_cost,DRIVE_HVY - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_HVY_WLK_FAR']+dot_skims['WLK_HVY_DRV_FAR']) + ((odt_skims['DRV_HVY_WLK_DDIST']/100+dot_skims['WLK_HVY_DRV_DDIST']/100) *costPerMile)),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY - Ratio of drive access distance to OD distance,@dacc_ratio * (odt_skims['DRV_HVY_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,,1,,,,
+util_DRIVE_HVY_Walk_other_time,DRIVE_HVY - Walk other time,@waux_multiplier * (odt_skims['DRV_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Fare_and_operating_cost,DRIVE_HVY - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_HVY_WLK_FAR']+dot_skims['WLK_HVY_DRV_FAR']) + ((odt_skims['DRV_HVY_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_HVY_DRV_DDIST']/TRANSIT_SCALE_FACTOR) *costPerMile)),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY - Ratio of drive access distance to OD distance,@dacc_ratio * (odt_skims['DRV_HVY_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,,1,,,,
 util_DRIVE_HVY_Destination_zone_densityIndex,DRIVE_HVY - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Topology,DRIVE_HVY - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Person_is_less_than_10_years_old,DRIVE_HVY - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,,coef_age010_trn_multiplier,,,,
@@ -237,18 +237,18 @@ util_DRIVE_HVY_Person_is_less_than_10_years_old,DRIVE_HVY - Person is less than
 util_DRIVE_COM_Unavailable,DRIVE_COM - Unavailable,drive_commuter_available == False,,,,,,,,,,,,,,,,,,-999,,,
 util_DRIVE_COM_Unavailable_for_zero_auto_households,DRIVE_COM - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,,,-999,,,
 util_DRIVE_COM_Unavailable_for_persons_less_than_16,DRIVE_COM - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,,-999,,,
-util_DRIVE_COM_In_vehicle_time,DRIVE_COM - In-vehicle time,@(odt_skims['DRV_COM_WLK_TOTIVT']/100 + dot_skims['WLK_COM_DRV_TOTIVT']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_In_vehicle_time_on_commuter_rail,DRIVE_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * (odt_skims['DRV_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_DRV_KEYIVT']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Short_iwait_time,DRIVE_COM - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_COM_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_COM_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Long_iwait_time,DRIVE_COM - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_COM_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_COM_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_transfer_wait_time,DRIVE_COM - transfer wait time,@xwait_multiplier * (odt_skims['DRV_COM_WLK_XWAIT']/100 + dot_skims['WLK_COM_DRV_XWAIT']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_In_vehicle_time,DRIVE_COM - In-vehicle time,@(odt_skims['DRV_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_In_vehicle_time_on_commuter_rail,DRIVE_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * (odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Short_iwait_time,DRIVE_COM - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_COM_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Long_iwait_time,DRIVE_COM - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_COM_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_transfer_wait_time,DRIVE_COM - transfer wait time,@xwait_multiplier * (odt_skims['DRV_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_number_of_transfers,DRIVE_COM - number of transfers,@xfers_drv_multiplier * ((odt_skims['DRV_COM_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_COM_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Drive_time,DRIVE_COM - Drive time,@dtim_multiplier * (odt_skims['DRV_COM_WLK_DTIM']/100 + dot_skims['WLK_COM_DRV_DTIM']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Drive_time,DRIVE_COM - Drive time,@dtim_multiplier * (odt_skims['DRV_COM_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Walk_access_time,DRIVE_COM - Walk access time (at attraction end),@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Walk_egress_time,DRIVE_COM - Walk egress time (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Walk_other_time,DRIVE_COM - Walk other time,@waux_multiplier * (odt_skims['DRV_COM_WLK_WAUX']/100 + dot_skims['WLK_COM_DRV_WAUX']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Fare_and_operating_cost,DRIVE_COM - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_COM_WLK_FAR']+dot_skims['WLK_COM_DRV_FAR']) + ((odt_skims['DRV_COM_WLK_DDIST']/100+dot_skims['WLK_COM_DRV_DDIST']/100) *costPerMile)),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_COM_WLK_DDIST']/100 + dot_skims['WLK_COM_DRV_DDIST']/100)/ (df.distance*2)),,,,,,,,,,,,,,,,,,1,,,
+util_DRIVE_COM_Walk_other_time,DRIVE_COM - Walk other time,@waux_multiplier * (odt_skims['DRV_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Fare_and_operating_cost,DRIVE_COM - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_COM_WLK_FAR']+dot_skims['WLK_COM_DRV_FAR']) + ((odt_skims['DRV_COM_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_COM_DRV_DDIST']/TRANSIT_SCALE_FACTOR) *costPerMile)),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_COM_WLK_DDIST']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']*2)),,,,,,,,,,,,,,,,,,1,,,
 util_DRIVE_COM_Destination_zone_densityIndex,DRIVE_COM - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Topology,DRIVE_COM - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Person_is_less_than_10_years_old,DRIVE_COM - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,,,coef_age010_trn_multiplier,,,
@@ -336,9 +336,9 @@ util_Heavy_Rail_ASC,Heavy Rail ASC,1,,,,,,,,,,,,heavy_rail_ASC,,,,,heavy_rail_AS
 util_Commuter_Rail,Commuter Rail,1,,,,,,,,,,,,,commuter_rail_ASC,,,,,commuter_rail_ASC,,,
 util_Walk_to_Transit_dest_CBD,Walk to Transit dest CBD,@df.destination_in_cbd,,,,,,,,,walk_transit_CBD_ASC,walk_transit_CBD_ASC,walk_transit_CBD_ASC,walk_transit_CBD_ASC,walk_transit_CBD_ASC,,,,,,,,
 util_Drive_to_Transit_dest_CBD,Drive to Transit dest CBD,@df.destination_in_cbd,,,,,,,,,,,,,,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,,,
-util_Drive_to_Transit_distance_penalty,Drive to Transit - distance penalty,@drvtrn_distpen_0_multiplier * (1-df.distance/drvtrn_distpen_max).clip(lower=0),,,,,,,,,,,,,,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,,,
+util_Drive_to_Transit_distance_penalty,Drive to Transit - distance penalty,@drvtrn_distpen_0_multiplier * (1-od_skims['DIST']/drvtrn_distpen_max).clip(lower=0),,,,,,,,,,,,,,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,,,
 #, FIXME - skims aren't symmetrical,so we have to make sure they can get back,,,,,,,,,,,,,,,,,,,,,
-util_Walk_not_available_for_long_distances,Walk not available for long distances,@df.distance_walk_od > 3,,,,,,,-999,,,,,,,,,,,,,,
-util_Bike_not_available_for_long_distances,Bike not available for long distances,@df.distance_bike_od > 8,,,,,,,,-999,,,,,,,,,,,,,
+util_Walk_not_available_for_long_distances,Walk not available for long distances,@od_skims.max('DISTWALK') > 3,,,,,,,-999,,,,,,,,,,,,,,
+util_Bike_not_available_for_long_distances,Bike not available for long distances,@od_skims.max('DISTBIKE') > 8,,,,,,,,-999,,,,,,,,,,,,,
 util_Drive_alone_not_available_for_escort_tours,Drive alone not available for escort tours,is_escort,-999,-999,,,,,,,,,,,,,,,,,,,
 #, max(c_densityIndexOrigin*originDensityIndex,originDensityIndexMax),,,,,,,,,1,1,1,1,1,1,1,,,,,,
diff --git a/activitysim/examples/example_mtc/configs/tour_mode_choice_annotate_choosers_preprocessor.csv b/activitysim/examples/example_mtc/configs/tour_mode_choice_annotate_choosers_preprocessor.csv
index 0177f286e..3ef95955f 100644
--- a/activitysim/examples/example_mtc/configs/tour_mode_choice_annotate_choosers_preprocessor.csv
+++ b/activitysim/examples/example_mtc/configs/tour_mode_choice_annotate_choosers_preprocessor.csv
@@ -75,18 +75,18 @@ local,_DF_IS_TOUR,'tour_type' in df.columns
 ,hov2toll_available,(odt_skims['HOV2TOLL_VTOLL'] + dot_skims['HOV2TOLL_VTOLL'])>0
 ,hov3_available,(odt_skims['HOV3_TIME']>0) & (dot_skims['HOV3_TIME']>0)
 ,hov3toll_available,(odt_skims['HOV3TOLL_VTOLL'] + dot_skims['HOV3TOLL_VTOLL'])>0
-,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LOC_WLK_TOTIVT']/100>0)
-,walk_commuter_available,walk_transit_available & (odt_skims['WLK_COM_WLK_TOTIVT']/100>0) & (dot_skims['WLK_COM_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_WLK_KEYIVT']/100)>0)
-,walk_express_available,walk_transit_available & (odt_skims['WLK_EXP_WLK_TOTIVT']/100>0) & (dot_skims['WLK_EXP_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_WLK_KEYIVT']/100)>0)
-,walk_heavyrail_available,walk_transit_available & (odt_skims['WLK_HVY_WLK_TOTIVT']/100>0) & (dot_skims['WLK_HVY_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_WLK_KEYIVT']/100)>0)
-,walk_lrf_available,walk_transit_available & (odt_skims['WLK_LRF_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LRF_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_WLK_KEYIVT']/100)>0)
-,walk_ferry_available,walk_lrf_available & ((odt_skims['WLK_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100)>0)
-,drive_local_available,drive_transit_available & (odt_skims['DRV_LOC_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LOC_DRV_TOTIVT']/100>0)
-,drive_commuter_available,drive_transit_available & (odt_skims['DRV_COM_WLK_TOTIVT']/100>0) & (dot_skims['WLK_COM_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_DRV_KEYIVT']/100)>0)
-,drive_express_available,drive_transit_available & (odt_skims['DRV_EXP_WLK_TOTIVT']/100>0) & (dot_skims['WLK_EXP_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_DRV_KEYIVT']/100)>0)
-,drive_heavyrail_available,drive_transit_available & (odt_skims['DRV_HVY_WLK_TOTIVT']/100>0) & (dot_skims['WLK_HVY_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_DRV_KEYIVT']/100)>0)
-,drive_lrf_available,drive_transit_available & (odt_skims['DRV_LRF_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LRF_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_DRV_KEYIVT']/100)>0)
-,drive_ferry_available,drive_lrf_available & ((odt_skims['DRV_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100)>0)
+,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_commuter_available,walk_transit_available & (odt_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,walk_express_available,walk_transit_available & (odt_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,walk_heavyrail_available,walk_transit_available & (odt_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,walk_lrf_available,walk_transit_available & (odt_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,walk_ferry_available,walk_lrf_available & ((odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_local_available,drive_transit_available & (odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_commuter_available,drive_transit_available & (odt_skims['DRV_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_COM_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_express_available,drive_transit_available & (odt_skims['DRV_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_EXP_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_heavyrail_available,drive_transit_available & (odt_skims['DRV_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_HVY_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_lrf_available,drive_transit_available & (odt_skims['DRV_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LRF_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_ferry_available,drive_lrf_available & ((odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR)>0)
 #,,
 destination in central business district,destination_in_cbd,"(reindex(land_use.area_type, df[dest_col_name]) < setting('cbd_threshold')) * 1"
 #,,FIXME diagnostic
diff --git a/activitysim/examples/example_mtc/configs/trip_destination.yaml b/activitysim/examples/example_mtc/configs/trip_destination.yaml
index 8bac788cc..75d350a3c 100644
--- a/activitysim/examples/example_mtc/configs/trip_destination.yaml
+++ b/activitysim/examples/example_mtc/configs/trip_destination.yaml
@@ -18,7 +18,7 @@ DEST_CHOICE_SAMPLE_TABLE_NAME: trip_destination_sample
 # model-specific logsum-related settings
 TRIP_ORIGIN: origin
 ALT_DEST_COL_NAME: dest_taz
-PRIMARY_DEST: destination
+PRIMARY_DEST: tour_leg_dest # must be created in preprocessor
 
 # tour_mode is already in trips table, so we don't need it from tours
 # (it is assigned in trip_destination_annotate_trips_preprocessor )
diff --git a/activitysim/examples/example_mtc/configs/trip_destination_annotate_trips_preprocessor.csv b/activitysim/examples/example_mtc/configs/trip_destination_annotate_trips_preprocessor.csv
index 0217a6855..1a1afb074 100644
--- a/activitysim/examples/example_mtc/configs/trip_destination_annotate_trips_preprocessor.csv
+++ b/activitysim/examples/example_mtc/configs/trip_destination_annotate_trips_preprocessor.csv
@@ -7,3 +7,4 @@ Description,Target,Expression
 #,,not needed as school is not chosen as an intermediate trip destination
 #,_grade_school,"(df.primary_purpose == 'school') & reindex(persons.is_gradeschool, df.person_id)"
 #,size_segment,"df.primary_purpose.where(df.primary_purpose != 'school', np.where(_grade_school,'gradeschool', 'highschool'))"
+,tour_leg_dest,"np.where(df.outbound,reindex(tours.destination, df.tour_id), reindex(tours.origin, df.tour_id))"
\ No newline at end of file
diff --git a/activitysim/examples/example_mtc/configs/trip_mode_choice.csv b/activitysim/examples/example_mtc/configs/trip_mode_choice.csv
index 7e15afc03..2da242e95 100644
--- a/activitysim/examples/example_mtc/configs/trip_mode_choice.csv
+++ b/activitysim/examples/example_mtc/configs/trip_mode_choice.csv
@@ -69,87 +69,87 @@ util_SHARED3PAY_One_person_household,SHARED3PAY - One person household,@(df.hhsi
 util_SHARED3PAY_Two_person_household,SHARED3PAY - Two person household,@(df.hhsize == 2),,,,,,coef_hhsize2_sr,,,,,,,,,,,,,,,
 util_SHARED3PAY_Person_is_16_years_old_or_older,SHARED3PAY - Person is 16 years old or older,@(df.age >= 16),,,,,,coef_age16p_sr,,,,,,,,,,,,,,,
 #,Walk,,,,,,,,,,,,,,,,,,,,,,
-util_WALK_Time_up_to_2_miles,WALK - Time up to 2 miles,@coef_walktimeshort_multiplier * df.distance_walk_od.clip(upper=walkThresh) * 60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
-util_WALK_Time_beyond_2_of_a_miles,WALK - Time beyond 2 of a miles,@walktimelong_multiplier * (df.distance_walk_od - walkThresh).clip(lower=0) * 60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
+util_WALK_Time_up_to_2_miles,WALK - Time up to 2 miles,@coef_walktimeshort_multiplier * od_skims['DISTWALK'].clip(upper=walkThresh) * 60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
+util_WALK_Time_beyond_2_of_a_miles,WALK - Time beyond 2 of a miles,@walktimelong_multiplier * (od_skims['DISTWALK'] - walkThresh).clip(lower=0) * 60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
 util_WALK_Destination_zone_densityIndex,WALK - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,coef_ivt,,,,,,,,,,,,,,
 util_WALK_Topology,WALK - Topology,@topology_walk_multiplier * df.trip_topology,,,,,,,coef_ivt,,,,,,,,,,,,,,
 #,Bike,,,,,,,,,,,,,,,,,,,,,,
 util_BIKE_Unavailable_if_didn't_bike_to_work,BIKE - Unavailable if didn't bike to work,is_atwork_subtour & ~work_tour_is_bike,,,,,,,,-999,,,,,,,,,,,,,
-util_BIKE_Time_up_to_6_miles,BIKE - Time up to 6 miles,@coef_biketimeshort_multiplier * df.distance_bike_od.clip(upper=bikeThresh)*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
-util_BIKE_Time_beyond_6_of_a_miles,BIKE - Time beyond 6 of a miles,@coef_biketimeshort_multiplier * biketimelong_multiplier * (df.distance_bike_od-bikeThresh).clip(lower=0)*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
+util_BIKE_Time_up_to_6_miles,BIKE - Time up to 6 miles,@coef_biketimeshort_multiplier * od_skims['DISTBIKE'].clip(upper=bikeThresh)*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
+util_BIKE_Time_beyond_6_of_a_miles,BIKE - Time beyond 6 of a miles,@coef_biketimeshort_multiplier * biketimelong_multiplier * (od_skims['DISTBIKE']-bikeThresh).clip(lower=0)*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
 util_BIKE_Destination_zone_densityIndex,BIKE - Destination zone densityIndex,@density_index_multiplier*df.density_index,,,,,,,,coef_ivt,,,,,,,,,,,,,
 util_BIKE_Topology,BIKE - Topology,@topology_bike_multiplier * df.trip_topology,,,,,,,,coef_ivt,,,,,,,,,,,,,
 #,Walk to Local,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_LOC_Unavailable,WALK_LOC - Unavailable,walk_local_available == False,,,,,,,,,-999,,,,,,,,,,,,
-util_WALK_LOC_In_vehicle_time,WALK_LOC - In-vehicle time,@odt_skims['WLK_LOC_WLK_TOTIVT']/100,,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Short_iwait_time,WALK_LOC - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_LOC_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Long_iwait_time,WALK_LOC - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_LOC_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_transfer_wait_time,WALK_LOC - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_LOC_WLK_XWAIT']/100,,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_In_vehicle_time,WALK_LOC - In-vehicle time,@odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Short_iwait_time,WALK_LOC - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Long_iwait_time,WALK_LOC - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_transfer_wait_time,WALK_LOC - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_number_of_transfers,WALK_LOC - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_LOC_WLK_BOARDS']-1).clip(0),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Walk_access_time,WALK_LOC - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Walk_egress_time,WALK_LOC - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Walk_other_time,WALK_LOC - Walk other time,@coef_waux_multiplier * odt_skims['WLK_LOC_WLK_WAUX']/100,,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Walk_other_time,WALK_LOC - Walk other time,@coef_waux_multiplier * odt_skims['WLK_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Fare,WALK_LOC - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_LOC_WLK_FAR'],,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Destination_zone_densityIndex,WALK_LOC - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Topology,WALK_LOC - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Person_is_less_than_10_years_old,WALK_LOC - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,coef_age010_trn,,,,,,,,,,,,
 #,Walk to Light rail/Ferry,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_LRF_Unavailable,WALK_LRF - Unavailable,walk_lrf_available == False,,,,,,,,,,-999,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time,WALK_LRF - In-vehicle time,@odt_skims['WLK_LRF_WLK_TOTIVT']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time_on_Light_Rail,WALK_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(coef_ivt_lrt_multiplier-1) * odt_skims['WLK_LRF_WLK_KEYIVT']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time_on_Ferry,WALK_LRF - In-vehicle time on Ferry (incremental w/keyivt),@(coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier) * odt_skims['WLK_LRF_WLK_FERRYIVT']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Short_iwait_time,WALK_LRF - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_LRF_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Long_iwait_time,WALK_LRF - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_LRF_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_transfer_wait_time,WALK_LRF - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_LRF_WLK_XWAIT']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time,WALK_LRF - In-vehicle time,@odt_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time_on_Light_Rail,WALK_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(coef_ivt_lrt_multiplier-1) * odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time_on_Ferry,WALK_LRF - In-vehicle time on Ferry (incremental w/keyivt),@(coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier) * odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Short_iwait_time,WALK_LRF - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Long_iwait_time,WALK_LRF - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_transfer_wait_time,WALK_LRF - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_number_of_transfers,WALK_LRF - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_LRF_WLK_BOARDS']-1).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Walk_access_time,WALK_LRF - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Walk_egress_time,WALK_LRF - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Walk_other_time,WALK_LRF - Walk otherLight rail/Ferry time,@coef_waux_multiplier * odt_skims['WLK_LRF_WLK_WAUX']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Walk_other_time,WALK_LRF - Walk otherLight rail/Ferry time,@coef_waux_multiplier * odt_skims['WLK_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Fare,WALK_LRF - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_LRF_WLK_FAR'],,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Destination_zone_densityIndex,WALK_LRF - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Topology,WALK_LRF - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Person_is_less_than_10_years_old,WALK_LRF - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,coef_age010_trn,,,,,,,,,,,
 #,Walk to Express bus,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_EXP_Unavailable,WALK_EXP - Unavailable,walk_express_available == False,,,,,,,,,,,-999,,,,,,,,,,
-util_WALK_EXP_In_vehicle_time,WALK_EXP - In-vehicle time,@odt_skims['WLK_EXP_WLK_TOTIVT']/100,,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_In_vehicle_time_on_Express_bus,WALK_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier - 1) * odt_skims['WLK_EXP_WLK_KEYIVT']/100,,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Short_iwait_time,WALK_EXP - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_EXP_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Long_iwait_time,WALK_EXP - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_EXP_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_transfer_wait_time,WALK_EXP - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_EXP_WLK_XWAIT']/100,,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_In_vehicle_time,WALK_EXP - In-vehicle time,@odt_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_In_vehicle_time_on_Express_bus,WALK_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier - 1) * odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Short_iwait_time,WALK_EXP - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Long_iwait_time,WALK_EXP - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_transfer_wait_time,WALK_EXP - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_number_of_transfers,WALK_EXP - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_EXP_WLK_BOARDS']-1).clip(0),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Walk_access_time,WALK_EXP - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Walk_egress_time,WALK_EXP - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Walk_other_time,WALK_EXP - Walk other time,@coef_waux_multiplier * odt_skims['WLK_EXP_WLK_WAUX']/100,,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Walk_other_time,WALK_EXP - Walk other time,@coef_waux_multiplier * odt_skims['WLK_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Fare,WALK_EXP - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_EXP_WLK_FAR'],,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Destination_zone_densityIndex,WALK_EXP - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Topology,WALK_EXP - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Person_is_less_than_10_years_old,WALK_EXP - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,,coef_age010_trn,,,,,,,,,,
 #,Walk to Heavy Rail,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_HVY_Unavailable,WALK_HVY - Unavailable,walk_heavyrail_available == False,,,,,,,,,,,,-999,,,,,,,,,
-util_WALK_HVY_In_vehicle_time,WALK_HVY - In-vehicle time,@odt_skims['WLK_HVY_WLK_TOTIVT']/100,,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_In_vehicle_time_on_heavy_rail,WALK_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * odt_skims['WLK_HVY_WLK_KEYIVT']/100,,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Short_iwait_time,WALK_HVY - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_HVY_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Long_iwait_time,WALK_HVY - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_HVY_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_transfer_wait_time,WALK_HVY - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_HVY_WLK_XWAIT']/100,,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_In_vehicle_time,WALK_HVY - In-vehicle time,@odt_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_In_vehicle_time_on_heavy_rail,WALK_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Short_iwait_time,WALK_HVY - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Long_iwait_time,WALK_HVY - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_transfer_wait_time,WALK_HVY - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_number_of_transfers,WALK_HVY - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_HVY_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Walk_access_time,WALK_HVY - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Walk_egress_time,WALK_HVY - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Walk_other_time,WALK_HVY - Walk other time,@coef_waux_multiplier * odt_skims['WLK_HVY_WLK_WAUX']/100,,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Walk_other_time,WALK_HVY - Walk other time,@coef_waux_multiplier * odt_skims['WLK_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Fare,WALK_HVY - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_HVY_WLK_FAR'],,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Destination_zone_densityIndex,WALK_HVY - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Topology,WALK_HVY - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Person_is_less_than_10_years_old,WALK_HVY - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,,,coef_age010_trn,,,,,,,,,
 #,Walk to Commuter rail,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_COM_Unavailable,WALK_COM - Unavailable,walk_commuter_available == False,,,,,,,,,,,,,-999,,,,,,,,
-util_WALK_COM_In_vehicle_time,WALK_COM - In-vehicle time,@odt_skims['WLK_COM_WLK_TOTIVT']/100,,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_In_vehicle_time_on_commuter_rail,WALK_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * odt_skims['WLK_COM_WLK_KEYIVT']/100,,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Short_iwait_time,WALK_COM - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_COM_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Long_iwait_time,WALK_COM - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_COM_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_transfer_wait_time,WALK_COM - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_COM_WLK_XWAIT']/100,,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_In_vehicle_time,WALK_COM - In-vehicle time,@odt_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_In_vehicle_time_on_commuter_rail,WALK_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Short_iwait_time,WALK_COM - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Long_iwait_time,WALK_COM - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_transfer_wait_time,WALK_COM - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_number_of_transfers,WALK_COM - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_COM_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Walk_access_time,WALK_COM - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Walk_egress_time,WALK_COM - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Walk_other_time,WALK_COM - Walk other time,@coef_waux_multiplier * odt_skims['WLK_COM_WLK_WAUX']/100,,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Walk_other_time,WALK_COM - Walk other time,@coef_waux_multiplier * odt_skims['WLK_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Fare,WALK_COM - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_COM_WLK_FAR'],,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Destination_zone_densityIndex,WALK_COM - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Topology,WALK_COM - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,coef_ivt,,,,,,,,
@@ -161,27 +161,27 @@ util_DRIVE_LOC_Destination_zone_densityIndex,DRIVE_LOC - Destination zone densit
 util_DRIVE_LOC_Topology,DRIVE_LOC - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Person_is_less_than_10_years_old,DRIVE_LOC - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,coef_age010_trn,,,,,,,
 util_DRIVE_LOC_outbound_Unavailable,DRIVE_LOC outbound - Unavailable,outbound & ~drive_local_available_outbound,,,,,,,,,,,,,,-999,,,,,,,
-util_DRIVE_LOC_outbound_In_vehicle_time,DRIVE_LOC outbound - In-vehicle time,@df.outbound * odt_skims['DRV_LOC_WLK_TOTIVT']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Short_iwait_time,DRIVE_LOC outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_LOC_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Long_iwait_time,DRIVE_LOC outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_LOC_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_transfer_wait_time,DRIVE_LOC outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_LOC_WLK_XWAIT']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_In_vehicle_time,DRIVE_LOC outbound - In-vehicle time,@df.outbound * odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Short_iwait_time,DRIVE_LOC outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Long_iwait_time,DRIVE_LOC outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_transfer_wait_time,DRIVE_LOC outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_outbound_number_of_transfers,DRIVE_LOC outbound - number of transfers,@df.outbound * xfers_wlk_multiplier * (odt_skims['DRV_LOC_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Drive_time,DRIVE_LOC outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_LOC_WLK_DTIM']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Drive_time,DRIVE_LOC outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_LOC_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_outbound_Walk_egress_time,DRIVE_LOC outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Walk_other_time,DRIVE_LOC outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_LOC_WLK_WAUX']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Fare_and_operating_cost,DRIVE_LOC outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_LOC_WLK_FAR'] + costPerMile*odt_skims['DRV_LOC_WLK_DDIST']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_LOC_WLK_DDIST']/100)/ (df.distance),,,,,,,,,,,,,,1,,,,,,,
+util_DRIVE_LOC_outbound_Walk_other_time,DRIVE_LOC outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Fare_and_operating_cost,DRIVE_LOC outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_LOC_WLK_FAR'] + costPerMile*odt_skims['DRV_LOC_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_LOC_WLK_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']),,,,,,,,,,,,,,1,,,,,,,
 util_DRIVE_LOC_inbound_Unavailable,DRIVE_LOC inbound - Unavailable,inbound & ~drive_local_available_inbound,,,,,,,,,,,,,,-999,,,,,,,
-util_DRIVE_LOC_inbound_In_vehicle_time,DRIVE_LOC inbound - In-vehicle time,@df.inbound * odt_skims['WLK_LOC_DRV_TOTIVT']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Short_iwait_time,DRIVE_LOC inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_LOC_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Long_iwait_time,DRIVE_LOC inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_LOC_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_transfer_wait_time,DRIVE_LOC inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_LOC_DRV_XWAIT']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_In_vehicle_time,DRIVE_LOC inbound - In-vehicle time,@df.inbound * odt_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Short_iwait_time,DRIVE_LOC inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_LOC_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Long_iwait_time,DRIVE_LOC inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_LOC_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_transfer_wait_time,DRIVE_LOC inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_LOC_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_inbound_number_of_transfers,DRIVE_LOC inbound - number of transfers,@df.inbound * xfers_wlk_multiplier * (odt_skims['WLK_LOC_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Drive_time,DRIVE_LOC inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_LOC_DRV_DTIM']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Drive_time,DRIVE_LOC inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_LOC_DRV_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_inbound_Walk_access_time,DRIVE_LOC inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Walk_other_time,DRIVE_LOC inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_LOC_DRV_WAUX']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Fare_and_operating_cost,DRIVE_LOC inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LOC_DRV_FAR'] + costPerMile*odt_skims['WLK_LOC_DRV_DDIST']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC inbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['WLK_LOC_DRV_DDIST']/100)/ (df.distance),,,,,,,,,,,,,,1,,,,,,,
+util_DRIVE_LOC_inbound_Walk_other_time,DRIVE_LOC inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_LOC_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Fare_and_operating_cost,DRIVE_LOC inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LOC_DRV_FAR'] + costPerMile*odt_skims['WLK_LOC_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC inbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['WLK_LOC_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']),,,,,,,,,,,,,,1,,,,,,,
 #,Drive to Light Rail/Ferry,,,,,,,,,,,,,,,,,,,,,,
 util_DRIVE_LRF_Unavailable_for_zero_auto_households,DRIVE_LRF - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,-999,,,,,,
 util_DRIVE_LRF_Unavailable_for_persons_less_than_16,DRIVE_LRF - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,-999,,,,,,
@@ -189,31 +189,31 @@ util_DRIVE_LRF_Destination_zone_densityIndex,DRIVE_LRF  - Destination zone densi
 util_DRIVE_LRF_Topology,DRIVE_LRF  - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Person_is_less_than_10_years_old,DRIVE_LRF  - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,coef_age010_trn,,,,,,
 util_DRIVE_LRF_outbound_Unavailable,DRIVE_LRF outbound - Unavailable,outbound & ~drive_lrf_available_outbound,,,,,,,,,,,,,,,-999,,,,,,
-util_DRIVE_LRF_outbound_In_vehicle_time,DRIVE_LRF outbound - In-vehicle time,@df.outbound * odt_skims['DRV_LRF_WLK_TOTIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_In_vehicle_time_on_LR,DRIVE_LRF outbound - In-vehicle time on Light Rail (incremental w/ ivt),@df.outbound * (coef_ivt_lrt_multiplier - 1)*odt_skims['DRV_LRF_WLK_KEYIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_In_vehicle_time_on_Ferry,DRIVE_LRF outbound - In-vehicle time on Ferry (incremental w/ keyivt),@df.outbound * (coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier)*odt_skims['DRV_LRF_WLK_FERRYIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Short_iwait_time,DRIVE_LRF outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_LRF_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Long_iwait_time,DRIVE_LRF outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_LRF_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_transfer_wait_time,DRIVE_LRF outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_LRF_WLK_XWAIT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_In_vehicle_time,DRIVE_LRF outbound - In-vehicle time,@df.outbound * odt_skims['DRV_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_In_vehicle_time_on_LR,DRIVE_LRF outbound - In-vehicle time on Light Rail (incremental w/ ivt),@df.outbound * (coef_ivt_lrt_multiplier - 1)*odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_In_vehicle_time_on_Ferry,DRIVE_LRF outbound - In-vehicle time on Ferry (incremental w/ keyivt),@df.outbound * (coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier)*odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Short_iwait_time,DRIVE_LRF outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Long_iwait_time,DRIVE_LRF outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_transfer_wait_time,DRIVE_LRF outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_outbound_number_of_transfers,DRIVE_LRF outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DRV_LRF_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Drive_time,DRIVE_LRF outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_LRF_WLK_DTIM']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Drive_time,DRIVE_LRF outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_LRF_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_outbound_Walk_egress_time,DRIVE_LRF outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Walk_other_time,DRIVE_LRF outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_LRF_WLK_WAUX']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Fare_and_operating_cost,DRIVE_LRF outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_LRF_WLK_FAR'] + costPerMile * odt_skims['DRV_LRF_WLK_DDIST']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_LRF_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,1,,,,,,
+util_DRIVE_LRF_outbound_Walk_other_time,DRIVE_LRF outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Fare_and_operating_cost,DRIVE_LRF outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_LRF_WLK_FAR'] + costPerMile * odt_skims['DRV_LRF_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_LRF_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,1,,,,,,
 util_DRIVE_LRF_inbound_Unavailable,DRIVE_LRF inbound - Unavailable,inbound & ~drive_lrf_available_inbound,,,,,,,,,,,,,,,-999,,,,,,
-util_DRIVE_LRF_inbound_In_vehicle_time,DRIVE_LRF inbound - In-vehicle time,@df.inbound * odt_skims['WLK_LRF_DRV_TOTIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_In_vehicle_time_on_LR,DRIVE_LRF inbound - In-vehicle time on Light Rail (incremental w/ ivt),@df.inbound * (coef_ivt_lrt_multiplier - 1)*odt_skims['WLK_LRF_DRV_KEYIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_In_vehicle_time_on_Ferry,DRIVE_LRF inbound - In-vehicle time on Ferry (incremental w/ keyivt),@df.inbound * (coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier)*odt_skims['WLK_LRF_DRV_FERRYIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Short_iwait_time,DRIVE_LRF inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_LRF_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Long_iwait_time,DRIVE_LRF inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_LRF_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_transfer_wait_time,DRIVE_LRF inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_LRF_DRV_XWAIT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_In_vehicle_time,DRIVE_LRF inbound - In-vehicle time,@df.inbound * odt_skims['WLK_LRF_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_In_vehicle_time_on_LR,DRIVE_LRF inbound - In-vehicle time on Light Rail (incremental w/ ivt),@df.inbound * (coef_ivt_lrt_multiplier - 1)*odt_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_In_vehicle_time_on_Ferry,DRIVE_LRF inbound - In-vehicle time on Ferry (incremental w/ keyivt),@df.inbound * (coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier)*odt_skims['WLK_LRF_DRV_FERRYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Short_iwait_time,DRIVE_LRF inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_LRF_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Long_iwait_time,DRIVE_LRF inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_LRF_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_transfer_wait_time,DRIVE_LRF inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_LRF_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_inbound_number_of_transfers,DRIVE_LRF inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WLK_LRF_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Drive_time,DRIVE_LRF inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_LRF_DRV_DTIM']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Drive_time,DRIVE_LRF inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_LRF_DRV_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_inbound_Walk_access_time,DRIVE_LRF inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Walk_other_time,DRIVE_LRF inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_LRF_DRV_WAUX']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Fare_and_operating_cost,DRIVE_LRF inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LRF_DRV_FAR'] + costPerMile * odt_skims['WLK_LRF_DRV_DDIST']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_LRF_DRV_DDIST']/100)/ df.distance,,,,,,,,,,,,,,,1,,,,,,
+util_DRIVE_LRF_inbound_Walk_other_time,DRIVE_LRF inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_LRF_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Fare_and_operating_cost,DRIVE_LRF inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LRF_DRV_FAR'] + costPerMile * odt_skims['WLK_LRF_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_LRF_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ od_skims['DIST'],,,,,,,,,,,,,,,1,,,,,,
 #,Drive to Express bus,,,,,,,,,,,,,,,,,,,,,,
 util_DRIVE_EXP_Unavailable_for_zero_auto_households,DRIVE_EXP - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,-999,,,,,
 util_DRIVE_EXP_Unavailable_for_persons_less_than_16,DRIVE_EXP - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,-999,,,,,
@@ -221,29 +221,29 @@ util_DRIVE_EXP_Destination_zone_densityIndex,DRIVE_EXP - Destination zone densit
 util_DRIVE_EXP_Topology,DRIVE_EXP - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Person_is_less_than_10_years_old,DRIVE_EXP - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,coef_age010_trn,,,,,
 util_DRIVE_EXP_outbound_Unavailable,DRIVE_EXP outbound - Unavailable,outbound & ~drive_express_available_outbound,,,,,,,,,,,,,,,,-999,,,,,
-util_DRIVE_EXP_outbound_In_vehicle_time,DRIVE_EXP outbound - In-vehicle time,@df.outbound * odt_skims['DRV_EXP_WLK_TOTIVT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_In_vehicle_time_on_EXP,DRIVE_EXP outbound - In-vehicle time on Express bus (incremental w/ ivt),@df.outbound * (ivt_exp_multiplier - 1) * odt_skims['DRV_EXP_WLK_KEYIVT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Short_iwait_time,DRIVE_EXP outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_EXP_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Long_iwait_time,DRIVE_EXP outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_EXP_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_transfer_wait_time,DRIVE_EXP outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_EXP_WLK_XWAIT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_In_vehicle_time,DRIVE_EXP outbound - In-vehicle time,@df.outbound * odt_skims['DRV_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_In_vehicle_time_on_EXP,DRIVE_EXP outbound - In-vehicle time on Express bus (incremental w/ ivt),@df.outbound * (ivt_exp_multiplier - 1) * odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Short_iwait_time,DRIVE_EXP outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Long_iwait_time,DRIVE_EXP outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_transfer_wait_time,DRIVE_EXP outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_outbound_number_of_transfers,DRIVE_EXP outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DRV_EXP_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Drive_time,DRIVE_EXP outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_EXP_WLK_DTIM']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Drive_time,DRIVE_EXP outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_EXP_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_outbound_Walk_egress_time,DRIVE_EXP outbound - Walk egress ime,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Walk_other_time,DRIVE_EXP outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_EXP_WLK_WAUX']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Fare_and_operating_cost,DRIVE_EXP outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_EXP_WLK_FAR'] + costPerMile * odt_skims['DRV_EXP_WLK_DDIST']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_EXP_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Walk_other_time,DRIVE_EXP outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Fare_and_operating_cost,DRIVE_EXP outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_EXP_WLK_FAR'] + costPerMile * odt_skims['DRV_EXP_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_EXP_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_inbound_Unavailable,DRIVE_EXP inbound - Unavailable,inbound & ~drive_express_available_inbound,,,,,,,,,,,,,,,,-999,,,,,
-util_DRIVE_EXP_inbound_In_vehicle_time,DRIVE_EXP inbound - In-vehicle time,@df.inbound * odt_skims['WLK_EXP_DRV_TOTIVT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_In_vehicle_time_on_EXP,DRIVE_EXP inbound - In-vehicle time on Express bus (incremental w/ ivt),@df.inbound * (ivt_exp_multiplier - 1) * odt_skims['WLK_EXP_DRV_KEYIVT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Short_iwait_time,DRIVE_EXP inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_EXP_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Long_iwait_time,DRIVE_EXP inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_EXP_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_transfer_wait_time,DRIVE_EXP inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_EXP_DRV_XWAIT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_In_vehicle_time,DRIVE_EXP inbound - In-vehicle time,@df.inbound * odt_skims['WLK_EXP_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_In_vehicle_time_on_EXP,DRIVE_EXP inbound - In-vehicle time on Express bus (incremental w/ ivt),@df.inbound * (ivt_exp_multiplier - 1) * odt_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Short_iwait_time,DRIVE_EXP inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_EXP_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Long_iwait_time,DRIVE_EXP inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_EXP_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_transfer_wait_time,DRIVE_EXP inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_EXP_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_inbound_number_of_transfers,DRIVE_EXP inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WLK_EXP_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Drive_time,DRIVE_EXP inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_EXP_DRV_DTIM']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Drive_time,DRIVE_EXP inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_EXP_DRV_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_inbound_Walk_access_time,DRIVE_EXP inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Walk_other_time,DRIVE_EXP inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_EXP_DRV_WAUX']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Fare_and_operating_cost,DRIVE_EXP inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_EXP_DRV_FAR'] + costPerMile * odt_skims['WLK_EXP_DRV_DDIST']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_EXP_DRV_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,1,,,,,
+util_DRIVE_EXP_inbound_Walk_other_time,DRIVE_EXP inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_EXP_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Fare_and_operating_cost,DRIVE_EXP inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_EXP_DRV_FAR'] + costPerMile * odt_skims['WLK_EXP_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_EXP_DRV_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,1,,,,,
 #,Drive to Heavy Rail,,,,,,,,,,,,,,,,,,,,,,
 util_DRIVE_HVY_Unavailable_for_zero_auto_households,DRIVE_HVY - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,,-999,,,,
 util_DRIVE_HVY_Unavailable_for_persons_less_than_16,DRIVE_HVY - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,-999,,,,
@@ -251,29 +251,29 @@ util_DRIVE_HVY_Destination_zone_densityIndex,DRIVE_HVY - Destination zone densit
 util_DRIVE_HVY_Topology,DRIVE_HVY - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Person_is_less_than_10_years_old,DRIVE_HVY - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,,coef_age010_trn,,,,
 util_DRIVE_HVY_outbound_Unavailable,DRIVE_HVY outbound - Unavailable,outbound & ~drive_heavyrail_available_outbound,,,,,,,,,,,,,,,,,-999,,,,
-util_DRIVE_HVY_outbound_In_vehicle_time,DRIVE_HVY outbound - In-vehicle time,@df.outbound * odt_skims['DRV_HVY_WLK_TOTIVT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_In_vehicle_time_on_HVY,DRIVE_HVY outbound - In-vehicle time on heavy rail (incremental w/ ivt),@df.outbound * (ivt_hvy_multiplier - 1) * odt_skims['DRV_HVY_WLK_KEYIVT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Short_iwait_time,DRIVE_HVY outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_HVY_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Long_iwait_time,DRIVE_HVY outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_HVY_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_transfer_wait_time,DRIVE_HVY outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_HVY_WLK_XWAIT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_In_vehicle_time,DRIVE_HVY outbound - In-vehicle time,@df.outbound * odt_skims['DRV_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_In_vehicle_time_on_HVY,DRIVE_HVY outbound - In-vehicle time on heavy rail (incremental w/ ivt),@df.outbound * (ivt_hvy_multiplier - 1) * odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Short_iwait_time,DRIVE_HVY outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Long_iwait_time,DRIVE_HVY outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_transfer_wait_time,DRIVE_HVY outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_outbound_number_of_transfers,DRIVE_HVY outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DRV_HVY_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Drive_time,DRIVE_HVY outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_HVY_WLK_DTIM']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Drive_time,DRIVE_HVY outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_HVY_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_outbound_Walk_egress_time,DRIVE_HVY outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Walk_other_time,DRIVE_HVY outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_HVY_WLK_WAUX']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Fare_and_operating_cost,DRIVE_HVY outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_HVY_WLK_FAR'] + costPerMile * odt_skims['DRV_HVY_WLK_DDIST']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_HVY_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Walk_other_time,DRIVE_HVY outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Fare_and_operating_cost,DRIVE_HVY outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_HVY_WLK_FAR'] + costPerMile * odt_skims['DRV_HVY_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_HVY_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_inbound_Unavailable,DRIVE_HVY inbound - Unavailable,inbound & ~drive_heavyrail_available_inbound,,,,,,,,,,,,,,,,,-999,,,,
-util_DRIVE_HVY_inbound_In_vehicle_time,DRIVE_HVY inbound - In-vehicle time,@df.inbound * odt_skims['WLK_HVY_DRV_TOTIVT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_In_vehicle_time_on_HVY,DRIVE_HVY inbound - In-vehicle time on heavy rail (incremental w/ ivt),@df.inbound * (ivt_hvy_multiplier - 1) * odt_skims['WLK_HVY_DRV_KEYIVT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Short_iwait_time,DRIVE_HVY inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_HVY_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Long_iwait_time,DRIVE_HVY inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_HVY_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_transfer_wait_time,DRIVE_HVY inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_HVY_DRV_XWAIT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_In_vehicle_time,DRIVE_HVY inbound - In-vehicle time,@df.inbound * odt_skims['WLK_HVY_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_In_vehicle_time_on_HVY,DRIVE_HVY inbound - In-vehicle time on heavy rail (incremental w/ ivt),@df.inbound * (ivt_hvy_multiplier - 1) * odt_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Short_iwait_time,DRIVE_HVY inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_HVY_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Long_iwait_time,DRIVE_HVY inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_HVY_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_transfer_wait_time,DRIVE_HVY inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_HVY_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_inbound_number_of_transfers,DRIVE_HVY inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WLK_HVY_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Drive_time,DRIVE_HVY inbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_HVY_WLK_DTIM']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Drive_time,DRIVE_HVY inbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_HVY_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_inbound_Walk_access_time,DRIVE_HVY inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Walk_other_time,DRIVE_HVY inbound - Walk other time,@coef_waux_multiplier * odt_skims['WLK_HVY_DRV_WAUX']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Fare_and_operating_cost,DRIVE_HVY inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_HVY_DRV_FAR'] + costPerMile * odt_skims['WLK_HVY_DRV_DDIST']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_HVY_DRV_DDIST']/100)/ df.distance,,,,,,,,,,,,,,,,,1,,,,
+util_DRIVE_HVY_inbound_Walk_other_time,DRIVE_HVY inbound - Walk other time,@coef_waux_multiplier * odt_skims['WLK_HVY_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Fare_and_operating_cost,DRIVE_HVY inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_HVY_DRV_FAR'] + costPerMile * odt_skims['WLK_HVY_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_HVY_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ od_skims['DIST'],,,,,,,,,,,,,,,,,1,,,,
 #,#Drive to Commuter Rail,,,,,,,,,,,,,,,,,,,,,,
 util_DRIVE_COM_Unavailable_for_zero_auto_households,DRIVE_COM - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,,,-999,,,
 util_DRIVE_COM_Unavailable_for_persons_less_than_16,DRIVE_COM - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,,-999,,,
@@ -281,29 +281,29 @@ util_DRIVE_COM_Destination_zone_densityIndex,DRIVE_COM - Destination zone densit
 util_DRIVE_COM_Topology,DRIVE_COM - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Person_is_less_than_10_years_old,DRIVE_COM - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,,,coef_age010_trn,,,
 util_DRIVE_COM_outbound_Unavailable,DRIVE_COM outbound - Unavailable,outbound & ~drive_commuter_available_outbound,,,,,,,,,,,,,,,,,,-999,,,
-util_DRIVE_COM_outbound_In_vehicle_time,DRIVE_COM outbound - In-vehicle time,@df.outbound * odt_skims['DRV_COM_WLK_TOTIVT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_In_vehicle_time_on_COM,DRIVE_COM outbound - In-vehicle time on commuter rail (incremental w/ ivt),@df.outbound * (ivt_com_multiplier - 1) * odt_skims['DRV_COM_WLK_KEYIVT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Short_iwait_time,DRIVE_COM outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_COM_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Long_iwait_time,DRIVE_COM outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_COM_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_transfer_wait_time,DRIVE_COM outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_COM_WLK_XWAIT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_In_vehicle_time,DRIVE_COM outbound - In-vehicle time,@df.outbound * odt_skims['DRV_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_In_vehicle_time_on_COM,DRIVE_COM outbound - In-vehicle time on commuter rail (incremental w/ ivt),@df.outbound * (ivt_com_multiplier - 1) * odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Short_iwait_time,DRIVE_COM outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Long_iwait_time,DRIVE_COM outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_transfer_wait_time,DRIVE_COM outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_outbound_number_of_transfers,DRIVE_COM outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DRV_COM_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Drive_time,DRIVE_COM outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_COM_WLK_DTIM']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Drive_time,DRIVE_COM outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_COM_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_outbound_Walk_egress_time,DRIVE_COM outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Walk_other_time,DRIVE_COM outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_COM_WLK_WAUX']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Fare_and_operating_cost,DRIVE_COM outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_COM_WLK_FAR'] + costPerMile * odt_skims['DRV_COM_WLK_DDIST']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_COM_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,,,1,,,
+util_DRIVE_COM_outbound_Walk_other_time,DRIVE_COM outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Fare_and_operating_cost,DRIVE_COM outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_COM_WLK_FAR'] + costPerMile * odt_skims['DRV_COM_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_COM_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,,,1,,,
 util_DRIVE_COM_inbound_Unavailable,DRIVE_COM inbound - Unavailable,inbound & ~drive_commuter_available_inbound,,,,,,,,,,,,,,,,,,-999,,,
-util_DRIVE_COM_inbound_In_vehicle_time,DRIVE_COM inbound - In-vehicle time,@df.inbound * odt_skims['WLK_COM_DRV_TOTIVT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_In_vehicle_time_on_COM,DRIVE_COM inbound - In-vehicle time on commuter rail (incremental w/ ivt),@df.inbound * (ivt_com_multiplier - 1) * odt_skims['WLK_COM_DRV_KEYIVT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Short_iwait_time,DRIVE_COM inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_COM_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Long_iwait_time,DRIVE_COM inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_COM_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_transfer_wait_time,DRIVE_COM inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_COM_DRV_XWAIT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_In_vehicle_time,DRIVE_COM inbound - In-vehicle time,@df.inbound * odt_skims['WLK_COM_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_In_vehicle_time_on_COM,DRIVE_COM inbound - In-vehicle time on commuter rail (incremental w/ ivt),@df.inbound * (ivt_com_multiplier - 1) * odt_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Short_iwait_time,DRIVE_COM inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_COM_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Long_iwait_time,DRIVE_COM inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_COM_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_transfer_wait_time,DRIVE_COM inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_COM_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_inbound_number_of_transfers,DRIVE_COM inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WLK_COM_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Drive_time,DRIVE_COM inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_COM_DRV_DTIM']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Drive_time,DRIVE_COM inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_COM_DRV_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_inbound_Walk_access_time,DRIVE_COM inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Walk_other_time,DRIVE_COM inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_COM_DRV_WAUX']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Fare_and_operating_cost,DRIVE_COM inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_COM_DRV_FAR'] + costPerMile * odt_skims['WLK_COM_DRV_DDIST']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_COM_DRV_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,,,1,,,
+util_DRIVE_COM_inbound_Walk_other_time,DRIVE_COM inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_COM_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Fare_and_operating_cost,DRIVE_COM inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_COM_DRV_FAR'] + costPerMile * odt_skims['WLK_COM_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_COM_DRV_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,,,1,,,
 #,Taxi,,,,,,,,,,,,,,,,,,,,,,
 util_Taxi_In_vehicle_time,Taxi - In-vehicle time,@odt_skims['HOV2TOLL_TIME'],,,,,,,,,,,,,,,,,,,coef_ivt,,
 util_Taxi_Wait_time,Taxi - Wait time,@ridehail_wait_time_multiplier * df.origTaxiWaitTime,,,,,,,,,,,,,,,,,,,coef_ivt,,
@@ -398,8 +398,8 @@ util_joint_Ride_Hail_tour_mode_ASC_ride_hail_taxi,joint - Ride Hail tour mode AS
 util_joint_Ride_Hail_tour_mode_ASC_ride_hail_single,joint - Ride Hail tour mode ASC -- ride hail,@(df.is_joint & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,,joint_ride_hail_ASC_tnc_single,
 util_joint_Ride_Hail_tour_mode_ASC_ride_hail_shared,joint - Ride Hail tour mode ASC -- ride hail,@(df.is_joint & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,,,joint_ride_hail_ASC_tnc_shared
 #,#,,,,,,,,,,,,,,,,,,,,,,
-util_Walk_not_available_for_long_distances,Walk not available for long distances,@df.tour_mode_is_walk & (df.distance_walk_od > 3),,,,,,,-999,,,,,,,,,,,,,,
-util_Bike_not_available_for_long_distances,Bike not available for long distances,@df.tour_mode_is_walk & (df.distance_bike_od > 8),,,,,,,,-999,,,,,,,,,,,,,
+util_Walk_not_available_for_long_distances,Walk not available for long distances,@df.tour_mode_is_walk & (od_skims['DISTWALK'] > 3),,,,,,,-999,,,,,,,,,,,,,,
+util_Bike_not_available_for_long_distances,Bike not available for long distances,@df.tour_mode_is_walk & (od_skims['DISTBIKE'] > 8),,,,,,,,-999,,,,,,,,,,,,,
 util_origin_density_index,Origin density index,@origin_density_applied*(origin_density_index_multiplier*df.origin_density_index).clip(origin_density_index_max),,,,,,,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,,,,,,,coef_ivt,coef_ivt
 util_walk_express_penalty,Walk-express penalty for intermediate stops,@walk_express_penalty * ~(df.first_trip | df.first_trip),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_adjust_tnc_shared,TNC shared adjustment,@adjust_tnc_shared,,,,,,,,,,,,,,,,,,,,,coef_ivt
diff --git a/activitysim/examples/example_mtc/configs/trip_mode_choice_annotate_trips_preprocessor.csv b/activitysim/examples/example_mtc/configs/trip_mode_choice_annotate_trips_preprocessor.csv
index 12e97e304..b0b82a22b 100644
--- a/activitysim/examples/example_mtc/configs/trip_mode_choice_annotate_trips_preprocessor.csv
+++ b/activitysim/examples/example_mtc/configs/trip_mode_choice_annotate_trips_preprocessor.csv
@@ -64,24 +64,24 @@ dest terminal time not counted at home,_dest_terminal_time,"np.where(inbound & l
 ,sovtoll_available,odt_skims['SOVTOLL_VTOLL']>0
 ,hov2toll_available,odt_skims['HOV2TOLL_VTOLL']>0
 ,hov3toll_available,odt_skims['HOV3TOLL_VTOLL']>0
-,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/100>0)
-,walk_lrf_available,walk_transit_available & (i_tour_mode >= 10) & (odt_skims['WLK_LRF_WLK_KEYIVT']/100>0)
-,walk_express_available,walk_transit_available & (i_tour_mode >= 11) & (odt_skims['WLK_EXP_WLK_KEYIVT']/100>0)
-,walk_heavyrail_available,walk_transit_available & (i_tour_mode >= 12) & (odt_skims['WLK_HVY_WLK_KEYIVT']/100>0)
-,walk_commuter_available,walk_transit_available & (i_tour_mode >= 13) & (odt_skims['WLK_COM_WLK_KEYIVT']/100>0)
-,drive_local_available_outbound,drive_transit_available & df.outbound & (odt_skims['DRV_LOC_WLK_TOTIVT']/100>0)
-,drive_local_available_inbound,drive_transit_available & ~df.outbound & (odt_skims['WLK_LOC_DRV_TOTIVT']/100>0)
-,drive_lrf_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 15) & (odt_skims['DRV_LRF_WLK_KEYIVT']/100>0)
-,drive_lrf_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 15) & (odt_skims['WLK_LRF_DRV_KEYIVT']/100>0)
-,drive_express_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 16) & (odt_skims['DRV_EXP_WLK_KEYIVT']/100>0)
-,drive_express_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 16) & (odt_skims['WLK_EXP_DRV_KEYIVT']/100>0)
-,drive_heavyrail_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 17) & (odt_skims['DRV_HVY_WLK_KEYIVT']/100>0)
-,drive_heavyrail_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 17) & (odt_skims['WLK_HVY_DRV_KEYIVT']/100>0)
-,drive_commuter_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 18) & (odt_skims['DRV_COM_WLK_KEYIVT']/100>0)
-,drive_commuter_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 18) & (odt_skims['WLK_COM_DRV_KEYIVT']/100>0)
-,walk_ferry_available,walk_lrf_available & (odt_skims['WLK_LRF_WLK_FERRYIVT']/100>0)
-,_drive_ferry_available_outbound,drive_lrf_available_outbound & (odt_skims['DRV_LRF_WLK_FERRYIVT']/100>0)
-,_drive_ferry_available_inbound,drive_lrf_available_inbound & (odt_skims['WLK_LRF_DRV_FERRYIVT']/100>0)
+,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_lrf_available,walk_transit_available & (i_tour_mode >= 10) & (odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_express_available,walk_transit_available & (i_tour_mode >= 11) & (odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_heavyrail_available,walk_transit_available & (i_tour_mode >= 12) & (odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_commuter_available,walk_transit_available & (i_tour_mode >= 13) & (odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_local_available_outbound,drive_transit_available & df.outbound & (odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_local_available_inbound,drive_transit_available & ~df.outbound & (odt_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_lrf_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 15) & (odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_lrf_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 15) & (odt_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_express_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 16) & (odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_express_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 16) & (odt_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_heavyrail_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 17) & (odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_heavyrail_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 17) & (odt_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_commuter_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 18) & (odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_commuter_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 18) & (odt_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_ferry_available,walk_lrf_available & (odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
+,_drive_ferry_available_outbound,drive_lrf_available_outbound & (odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
+,_drive_ferry_available_inbound,drive_lrf_available_inbound & (odt_skims['WLK_LRF_DRV_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
 ,drive_ferry_available,"np.where(df.outbound, _drive_ferry_available_outbound, _drive_ferry_available_inbound)"
 #,od_dist_walk,od_skims['DISTWALK']
 #,do_dist_walk,od_skims.reverse('DISTWALK')
diff --git a/activitysim/examples/example_mtc/test/regress/final_trips.csv b/activitysim/examples/example_mtc/test/regress/final_trips.csv
index 6d46c978c..8be2b7a7c 100644
--- a/activitysim/examples/example_mtc/test/regress/final_trips.csv
+++ b/activitysim/examples/example_mtc/test/regress/final_trips.csv
@@ -62,9 +62,9 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 1368291613,4171620,1810015,school,1,False,1,16,8,171036451,home,,15,WALK_LOC,10.665116381563836
 1368292281,4171622,1810015,shopping,1,True,1,19,16,171036535,shopping,,9,WALK,-2.394141994327624
 1368292285,4171622,1810015,shopping,1,False,1,16,19,171036535,home,,15,WALK,-2.4219133842589526
-1368292377,4171623,1810015,atwork,1,True,1,9,21,171036547,atwork,,10,WALK_LOC,11.325349584465323
-1368292381,4171623,1810015,atwork,1,False,2,6,9,171036547,othmaint,58.62927983645812,10,WALK,11.51994996841233
-1368292382,4171623,1810015,atwork,2,False,2,21,6,171036547,work,,10,WALK_LOC,13.150719673582849
+1368292377,4171623,1810015,atwork,1,True,1,7,21,171036547,atwork,,10,WALK,13.897946303660285
+1368292381,4171623,1810015,atwork,1,False,2,6,7,171036547,othmaint,62.239483838845736,10,WALK,14.364186248721689
+1368292382,4171623,1810015,atwork,2,False,2,21,6,171036547,work,,10,WALK,12.200629295549986
 1368292657,4171623,1810015,work,1,True,2,25,16,171036582,escort,30.234430836012045,8,WALK,9.029527074456235
 1368292658,4171623,1810015,work,2,True,2,21,25,171036582,work,,8,WALK,2.001441630738205
 1368292661,4171623,1810015,work,1,False,2,7,21,171036582,work,34.72578612209499,23,WALK,2.5646380272501803
diff --git a/activitysim/examples/example_multiple_zone/configs_2_zone/accessibility.csv b/activitysim/examples/example_multiple_zone/configs_2_zone/accessibility.csv
index 621387555..db2275546 100644
--- a/activitysim/examples/example_multiple_zone/configs_2_zone/accessibility.csv
+++ b/activitysim/examples/example_multiple_zone/configs_2_zone/accessibility.csv
@@ -21,12 +21,12 @@ auto off-peak total,auOpTotal,df.TOTEMP * _decay
 #,, assume peak outbound transit occurs in AM
 o-d peak transit ivt,_inVehicleTime,"skim_od[('WLK_TRN_WLK_IVT', 'AM')]"
 o-d peak transit ovt,_outOfVehicleTime,"skim_od[('WLK_TRN_WLK_IWAIT', 'AM')] + skim_od[('WLK_TRN_WLK_XWAIT', 'AM')] + skim_od[('WLK_TRN_WLK_WACC', 'AM')] + skim_od[('WLK_TRN_WLK_WAUX', 'AM')] + skim_od[('WLK_TRN_WLK_WEGR', 'AM')]"
-o-d peak transit time,_trPkTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
+o-d peak transit time,_trPkTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
 #,, assume peak inbound transit occurs in PM
 d-o peak transit ivt,_inVehicleTime,"skim_do[('WLK_TRN_WLK_IVT', 'PM')]"
 d-o peak transit ovt,_outOfVehicleTime,"skim_do[('WLK_TRN_WLK_IWAIT', 'PM')] + skim_do[('WLK_TRN_WLK_XWAIT', 'PM')] + skim_do[('WLK_TRN_WLK_WACC', 'PM')] + skim_do[('WLK_TRN_WLK_WAUX', 'PM')] + skim_do[('WLK_TRN_WLK_WEGR', 'PM')]"
-d-o peak transit time,_trPkTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
-peak transit time,_trPkTime,_trPkTime_od + _trPkTime_do
+d-o peak transit time,_trPkTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
+peak transit time,_trPkTime,(_trPkTime_od + _trPkTime_do).clip(0)
 round trip path is available,_rt_available,(_trPkTime_od > 0) & (_trPkTime_do > 0)
 decay function,_decay,_rt_available * exp(_trPkTime * dispersion_parameter_transit)
 transit peak retail,trPkRetail,df.RETEMPN * _decay
@@ -37,12 +37,12 @@ transit peak total,trPkTotal,df.TOTEMP * _decay
 #,, assume off-peak outbound transit occurs in the MD time period
 o-d off-peak transit ivt,_inVehicleTime,"skim_od[('WLK_TRN_WLK_IVT', 'MD')]"
 o-d off-peak transit ovt,_outOfVehicleTime,"skim_od[('WLK_TRN_WLK_IWAIT', 'MD')] + skim_od[('WLK_TRN_WLK_XWAIT', 'MD')] + skim_od[('WLK_TRN_WLK_WACC', 'MD')] + skim_od[('WLK_TRN_WLK_WAUX', 'MD')] + skim_od[('WLK_TRN_WLK_WEGR', 'MD')]"
-o-d off-peak transit time,_trOpTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
+o-d off-peak transit time,_trOpTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
 #,, assume off-peak inbound transit occurs in the MD time period
 d-o off-peak transit ivt,_inVehicleTime,"skim_do[('WLK_TRN_WLK_IVT', 'MD')]"
 d-o off-peak transit ovt,_outOfVehicleTime,"skim_do[('WLK_TRN_WLK_IWAIT', 'MD')] + skim_do[('WLK_TRN_WLK_XWAIT', 'MD')] + skim_do[('WLK_TRN_WLK_WACC', 'MD')] + skim_do[('WLK_TRN_WLK_WAUX', 'MD')] + skim_do[('WLK_TRN_WLK_WEGR', 'MD')]"
-d-o off-peak transit time,_trOpTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
-peak transit time,_trOpTime,_trOpTime_od + _trOpTime_do
+d-o off-peak transit time,_trOpTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
+peak transit time,_trOpTime,(_trOpTime_od + _trOpTime_do).clip(0)
 #,,FIXME - _rt_available calculation appears to be wrong in mtctm1 accessibility.job
 #round trip path is available,_rt_available,(_trOpTime > 0)
 round trip path is available,_rt_available,(_trOpTime_od > 0) & (_trOpTime_do > 0)
diff --git a/activitysim/examples/example_multiple_zone/configs_3_zone/accessibility.csv b/activitysim/examples/example_multiple_zone/configs_3_zone/accessibility.csv
index a14048401..4ce6c0f01 100644
--- a/activitysim/examples/example_multiple_zone/configs_3_zone/accessibility.csv
+++ b/activitysim/examples/example_multiple_zone/configs_3_zone/accessibility.csv
@@ -23,7 +23,7 @@ auto off-peak total,auOpTotal,df.TOTEMP * _decay
 o-d peak transit time,_trPkTime_od,"tvpb.get_tvpb_best_transit_time(orig=df.orig, dest=df.dest, tod='AM')"
 #,, assume peak inbound transit occurs in PM
 o-d peak transit time,_trPkTime_do,"tvpb.get_tvpb_best_transit_time(orig=df.dest, dest=df.orig, tod='PM')"
-peak transit time,_trPkTime,_trPkTime_od + _trPkTime_do
+peak transit time,_trPkTime,(_trPkTime_od + _trPkTime_do).clip(0)
 round trip path is available,_rt_available,(_trPkTime_od > 0) & (_trPkTime_do > 0)
 decay function,_decay,_rt_available * exp(_trPkTime * dispersion_parameter_transit)
 transit peak retail,trPkRetail,df.RETEMPN * _decay
@@ -34,7 +34,7 @@ transit peak total,trPkTotal,df.TOTEMP * _decay
 ####,, assume off-peak inbound and outbound transit occurs in the MD time period
 o-d off-peak transit time,_trOpTime_od,"tvpb.get_tvpb_best_transit_time(orig=df.orig, dest=df.dest, tod='MD')"
 d-o off-peak transit time,_trOpTime_do,"tvpb.get_tvpb_best_transit_time(orig=df.dest, dest=df.orig, tod='MD')"
-off-peak transit time,_trOpTime,_trOpTime_od + _trPkTime_do
+off-peak transit time,_trOpTime,(_trOpTime_od + _trPkTime_do).clip(0)
 round trip path is available,_rt_available,(_trOpTime_od > 0) & (_trOpTime_do > 0)
 decay function,_decay,_rt_available * exp(_trOpTime * dispersion_parameter_transit)
 transit off-peak retail,trOpRetail,df.RETEMPN * _decay
diff --git a/activitysim/examples/example_multiple_zone/configs_3_zone/annotate_persons_workplace.csv b/activitysim/examples/example_multiple_zone/configs_3_zone/annotate_persons_workplace.csv
index 2779b8a25..0a3f574c2 100644
--- a/activitysim/examples/example_multiple_zone/configs_3_zone/annotate_persons_workplace.csv
+++ b/activitysim/examples/example_multiple_zone/configs_3_zone/annotate_persons_workplace.csv
@@ -17,19 +17,19 @@ work_zone_area_type,work_zone_area_type,"reindex(land_use.area_type, persons.wor
 ,_roundtrip_walk_time_to_work,"np.where(_work_walk_available, _walk_time_home_to_work + _walk_time_work_to_home, _MAX_TIME_TO_WORK)"
 #,,_roundtrip_transit_time_to_work
 ##### ,_IVT_SKIM,"skim_dict.get(('WLK_TRN_WLK_IVT', 'MD'))"
-##### ,_transit_ivt_home_to_work,"_IVT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100"
-##### ,_transit_ivt_work_to_home,"_IVT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_ivt_home_to_work,"_IVT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR"
+##### ,_transit_ivt_work_to_home,"_IVT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_work_transit_available,(_transit_ivt_home_to_work > 0) & (_transit_ivt_work_to_home > 0)
 ##### ,_IWAIT_SKIM,"skim_dict.get(('WLK_TRN_WLK_IWAIT', 'MD'))"
-##### ,_transit_iwait,"_IWAIT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _IWAIT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_iwait,"_IWAIT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _IWAIT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_XWAIT_SKIM,"skim_dict.get(('WLK_TRN_WLK_XWAIT', 'MD'))"
-##### ,_transit_xwait,"_XWAIT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _XWAIT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_xwait,"_XWAIT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _XWAIT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_WAUX_SKIM,"skim_dict.get(('WLK_TRN_WLK_WAUX', 'MD'))"
-##### ,_transit_waux,"_WAUX_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _WAUX_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_waux,"_WAUX_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _WAUX_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_WACC_SKIM,"skim_dict.get(('WLK_TRN_WLK_WACC', 'MD'))"
-##### ,_transit_wacc,"_WACC_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _WACC_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_wacc,"_WACC_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _WACC_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_WEGR_SKIM,"skim_dict.get(('WLK_TRN_WLK_WEGR', 'MD'))"
-##### ,_transit_wegr,"_WEGR_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _WEGR_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_wegr,"_WEGR_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _WEGR_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_roundtrip_transit_time_to_work,_transit_ivt_home_to_work + _transit_ivt_work_to_home + _transit_iwait + _transit_xwait + _transit_waux + _transit_wacc + _transit_wegr
 ##### #,,work_auto_savings_ratio
 ##### ,_min_work_walk_transit,"np.where(_work_transit_available, np.minimum(_roundtrip_transit_time_to_work, _roundtrip_walk_time_to_work), _roundtrip_walk_time_to_work)"
diff --git a/activitysim/examples/example_multiple_zone/configs_3_zone/tour_mode_choice_annotate_choosers_preprocessor.csv b/activitysim/examples/example_multiple_zone/configs_3_zone/tour_mode_choice_annotate_choosers_preprocessor.csv
index 351227284..7400587b6 100644
--- a/activitysim/examples/example_multiple_zone/configs_3_zone/tour_mode_choice_annotate_choosers_preprocessor.csv
+++ b/activitysim/examples/example_multiple_zone/configs_3_zone/tour_mode_choice_annotate_choosers_preprocessor.csv
@@ -78,18 +78,18 @@ local,_DF_IS_TOUR,'tour_type' in df.columns
 ,hov2toll_available,(odt_skims['HOV2TOLL_VTOLL'] + dot_skims['HOV2TOLL_VTOLL'])>0
 ,hov3_available,(odt_skims['HOV3_TIME']>0) & (dot_skims['HOV3_TIME']>0)
 ,hov3toll_available,(odt_skims['HOV3TOLL_VTOLL'] + dot_skims['HOV3TOLL_VTOLL'])>0
-#,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LOC_WLK_TOTIVT']/100>0)
-#,walk_commuter_available,walk_transit_available & (odt_skims['WLK_COM_WLK_TOTIVT']/100>0) & (dot_skims['WLK_COM_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_WLK_KEYIVT']/100)>0)
-#,walk_express_available,walk_transit_available & (odt_skims['WLK_EXP_WLK_TOTIVT']/100>0) & (dot_skims['WLK_EXP_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_WLK_KEYIVT']/100)>0)
-#,walk_heavyrail_available,walk_transit_available & (odt_skims['WLK_HVY_WLK_TOTIVT']/100>0) & (dot_skims['WLK_HVY_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_WLK_KEYIVT']/100)>0)
-#,walk_lrf_available,walk_transit_available & (odt_skims['WLK_LRF_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LRF_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_WLK_KEYIVT']/100)>0)
-#,walk_ferry_available,walk_lrf_available & ((odt_skims['WLK_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100)>0)
-#,drive_local_available,drive_transit_available & (odt_skims['DRV_LOC_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LOC_DRV_TOTIVT']/100>0)
-#,drive_commuter_available,drive_transit_available & (odt_skims['DRV_COM_WLK_TOTIVT']/100>0) & (dot_skims['WLK_COM_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_DRV_KEYIVT']/100)>0)
-#,drive_express_available,drive_transit_available & (odt_skims['DRV_EXP_WLK_TOTIVT']/100>0) & (dot_skims['WLK_EXP_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_DRV_KEYIVT']/100)>0)
-#,drive_heavyrail_available,drive_transit_available & (odt_skims['DRV_HVY_WLK_TOTIVT']/100>0) & (dot_skims['WLK_HVY_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_DRV_KEYIVT']/100)>0)
-#,drive_lrf_available,drive_transit_available & (odt_skims['DRV_LRF_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LRF_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_DRV_KEYIVT']/100)>0)
-#,drive_ferry_available,drive_lrf_available & ((odt_skims['DRV_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100)>0)
+#,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_commuter_available,walk_transit_available & (odt_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,walk_express_available,walk_transit_available & (odt_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,walk_heavyrail_available,walk_transit_available & (odt_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,walk_lrf_available,walk_transit_available & (odt_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,walk_ferry_available,walk_lrf_available & ((odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_local_available,drive_transit_available & (odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_commuter_available,drive_transit_available & (odt_skims['DRV_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_COM_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_express_available,drive_transit_available & (odt_skims['DRV_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_EXP_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_heavyrail_available,drive_transit_available & (odt_skims['DRV_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_HVY_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_lrf_available,drive_transit_available & (odt_skims['DRV_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LRF_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_ferry_available,drive_lrf_available & ((odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR)>0)
 ,walk_transit_available,True
 ,drive_transit_available,True
 #,,
diff --git a/activitysim/examples/example_multiple_zone/configs_3_zone/trip_mode_choice_annotate_trips_preprocessor.csv b/activitysim/examples/example_multiple_zone/configs_3_zone/trip_mode_choice_annotate_trips_preprocessor.csv
index 7cbc61621..4d0e2f39c 100644
--- a/activitysim/examples/example_multiple_zone/configs_3_zone/trip_mode_choice_annotate_trips_preprocessor.csv
+++ b/activitysim/examples/example_multiple_zone/configs_3_zone/trip_mode_choice_annotate_trips_preprocessor.csv
@@ -81,24 +81,24 @@ dest terminal time not counted at home,_dest_terminal_time,"np.where(inbound & l
 ,sovtoll_available,odt_skims['SOVTOLL_VTOLL']>0
 ,hov2toll_available,odt_skims['HOV2TOLL_VTOLL']>0
 ,hov3toll_available,odt_skims['HOV3TOLL_VTOLL']>0
-#,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/100>0)
-#,walk_lrf_available,walk_transit_available & (i_tour_mode >= 10) & (odt_skims['WLK_LRF_WLK_KEYIVT']/100>0)
-#,walk_express_available,walk_transit_available & (i_tour_mode >= 11) & (odt_skims['WLK_EXP_WLK_KEYIVT']/100>0)
-#,walk_heavyrail_available,walk_transit_available & (i_tour_mode >= 12) & (odt_skims['WLK_HVY_WLK_KEYIVT']/100>0)
-#,walk_commuter_available,walk_transit_available & (i_tour_mode >= 13) & (odt_skims['WLK_COM_WLK_KEYIVT']/100>0)
-#,drive_local_available_outbound,drive_transit_available & df.outbound & (odt_skims['DRV_LOC_WLK_TOTIVT']/100>0)
-#,drive_local_available_inbound,drive_transit_available & ~df.outbound & (odt_skims['WLK_LOC_DRV_TOTIVT']/100>0)
-#,drive_lrf_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 15) & (odt_skims['DRV_LRF_WLK_KEYIVT']/100>0)
-#,drive_lrf_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 15) & (odt_skims['WLK_LRF_DRV_KEYIVT']/100>0)
-#,drive_express_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 16) & (odt_skims['DRV_EXP_WLK_KEYIVT']/100>0)
-#,drive_express_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 16) & (odt_skims['WLK_EXP_DRV_KEYIVT']/100>0)
-#,drive_heavyrail_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 17) & (odt_skims['DRV_HVY_WLK_KEYIVT']/100>0)
-#,drive_heavyrail_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 17) & (odt_skims['WLK_HVY_DRV_KEYIVT']/100>0)
-#,drive_commuter_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 18) & (odt_skims['DRV_COM_WLK_KEYIVT']/100>0)
-#,drive_commuter_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 18) & (odt_skims['WLK_COM_DRV_KEYIVT']/100>0)
-#,walk_ferry_available,walk_lrf_available & (odt_skims['WLK_LRF_WLK_FERRYIVT']/100>0)
-#,_drive_ferry_available_outbound,drive_lrf_available_outbound & (odt_skims['DRV_LRF_WLK_FERRYIVT']/100>0)
-#,_drive_ferry_available_inbound,drive_lrf_available_inbound & (odt_skims['WLK_LRF_DRV_FERRYIVT']/100>0)
+#,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_lrf_available,walk_transit_available & (i_tour_mode >= 10) & (odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_express_available,walk_transit_available & (i_tour_mode >= 11) & (odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_heavyrail_available,walk_transit_available & (i_tour_mode >= 12) & (odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_commuter_available,walk_transit_available & (i_tour_mode >= 13) & (odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_local_available_outbound,drive_transit_available & df.outbound & (odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_local_available_inbound,drive_transit_available & ~df.outbound & (odt_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_lrf_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 15) & (odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_lrf_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 15) & (odt_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_express_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 16) & (odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_express_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 16) & (odt_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_heavyrail_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 17) & (odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_heavyrail_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 17) & (odt_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_commuter_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 18) & (odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_commuter_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 18) & (odt_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_ferry_available,walk_lrf_available & (odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,_drive_ferry_available_outbound,drive_lrf_available_outbound & (odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,_drive_ferry_available_inbound,drive_lrf_available_inbound & (odt_skims['WLK_LRF_DRV_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
 #,drive_ferry_available,"np.where(df.outbound, _drive_ferry_available_outbound, _drive_ferry_available_inbound)"
 #,od_dist_walk,od_skims['DISTWALK']
 #,do_dist_walk,od_skims.reverse('DISTWALK')
diff --git a/activitysim/examples/example_multiple_zone/configs_3_zone/tvpb_accessibility_tap_tap_.csv b/activitysim/examples/example_multiple_zone/configs_3_zone/tvpb_accessibility_tap_tap_.csv
index 2572c99d9..a1a6e63b0 100644
--- a/activitysim/examples/example_multiple_zone/configs_3_zone/tvpb_accessibility_tap_tap_.csv
+++ b/activitysim/examples/example_multiple_zone/configs_3_zone/tvpb_accessibility_tap_tap_.csv
@@ -5,4 +5,4 @@ Description,Target,Expression
 ,_xwait,"out_of_vehicle_wait_time_weight * los.get_tappairs3d(df.btap, df.atap, df.tod, 'TRN_XWAIT_FAST')"
 ,_waux,"out_of_vehicle_walk_time_weight * los.get_tappairs3d(df.btap, df.atap, df.tod, 'TRN_WAUX_FAST')"
 ,_outOfVehicleTime,_iwait + _xwait + _waux
-,transit_time,(_inVehicleTime + _outOfVehicleTime) / 100.0
+,transit_time,(_inVehicleTime + _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
diff --git a/activitysim/examples/example_multiple_zone/test/regress/final_tours_2_zone.csv b/activitysim/examples/example_multiple_zone/test/regress/final_tours_2_zone.csv
index aa9af99e9..38d480be5 100644
--- a/activitysim/examples/example_multiple_zone/test/regress/final_tours_2_zone.csv
+++ b/activitysim/examples/example_multiple_zone/test/regress/final_tours_2_zone.csv
@@ -1,115 +1,115 @@
 tour_id,person_id,tour_type,tour_type_count,tour_type_num,tour_num,tour_count,tour_category,number_of_participants,destination,origin,household_id,tdd,start,end,duration,composition,destination_logsum,tour_mode,mode_choice_logsum,atwork_subtour_frequency,parent_tour_id,stop_frequency,primary_purpose
-1094132,26686,eatout,1,1,2,2,non_mandatory,1,7000.0,8000.0,26686,175.0,19.0,19.0,0.0,,15.629062503460995,WALK,4.871994501109852,,,0out_0in,eatout
-1094154,26686,othmaint,1,1,1,2,non_mandatory,1,9000.0,8000.0,26686,113.0,12.0,13.0,1.0,,14.776029862164645,BIKE,1.8681013354742215,,,0out_0in,othmaint
-1100640,26844,social,1,1,1,1,non_mandatory,1,7000.0,8000.0,26844,58.0,8.0,12.0,4.0,,14.569062067035372,WALK,2.4697470949563276,,,0out_1in,social
-1136791,27726,othdiscr,1,1,1,1,non_mandatory,1,17000.0,10000.0,27726,56.0,8.0,10.0,2.0,,15.210389207218824,WALK_LRF,1.9629437367760907,,,0out_1in,othdiscr
-1214658,29625,shopping,1,1,1,1,non_mandatory,1,16000.0,17000.0,29625,145.0,15.0,15.0,0.0,,13.917639604692425,WALK_LRF,2.3294492261730855,,,0out_0in,shopping
-4594649,112064,othdiscr,1,1,2,2,non_mandatory,1,9000.0,16000.0,112064,114.0,12.0,14.0,2.0,,13.975392118925592,DRIVEALONEFREE,-0.196980580755357,,,0out_0in,othdiscr
-4594657,112064,shopping,1,1,1,2,non_mandatory,1,11000.0,16000.0,112064,155.0,16.0,17.0,1.0,,12.654542351961295,WALK,-0.6137027897971015,,,0out_0in,shopping
-10828426,264107,work,1,1,1,1,mandatory,1,15000.0,9000.0,226869,49.0,7.0,19.0,12.0,,,WALK_LRF,5.852076021113983,no_subtours,,0out_0in,work
-10828453,264108,othdiscr,1,1,1,1,non_mandatory,1,2000.0,9000.0,226869,86.0,10.0,11.0,1.0,,15.155629215166487,WALK_LRF,2.6939204818996534,,,0out_1in,othdiscr
+1094132,26686,eatout,1,1,2,2,non_mandatory,1,7000.0,8000.0,26686,175.0,19.0,19.0,0.0,,15.571618689147394,WALK,4.696089773072796,,,0out_0in,eatout
+1094154,26686,othmaint,1,1,1,2,non_mandatory,1,9000.0,8000.0,26686,113.0,12.0,13.0,1.0,,14.768882236372544,BIKE,1.8681013354742213,,,0out_0in,othmaint
+1100640,26844,social,1,1,1,1,non_mandatory,1,7000.0,8000.0,26844,58.0,8.0,12.0,4.0,,14.566226227301671,WALK,2.3971996226244454,,,0out_1in,social
+1136791,27726,othdiscr,1,1,1,1,non_mandatory,1,17000.0,10000.0,27726,56.0,8.0,10.0,2.0,,15.219575637063269,WALK_LRF,1.962943736776091,,,0out_1in,othdiscr
+1214658,29625,shopping,1,1,1,1,non_mandatory,1,16000.0,17000.0,29625,145.0,15.0,15.0,0.0,,13.920232108204546,WALK_LRF,2.347375316107423,,,0out_0in,shopping
+4594649,112064,othdiscr,1,1,2,2,non_mandatory,1,9000.0,16000.0,112064,114.0,12.0,14.0,2.0,,13.96458148150002,DRIVEALONEFREE,-0.1912982156718468,,,0out_0in,othdiscr
+4594657,112064,shopping,1,1,1,2,non_mandatory,1,11000.0,16000.0,112064,155.0,16.0,17.0,1.0,,12.64809824515548,WALK,-0.6137027897971015,,,0out_0in,shopping
+10828426,264107,work,1,1,1,1,mandatory,1,15000.0,9000.0,226869,49.0,7.0,19.0,12.0,,,WALK_LRF,5.8471129413966,no_subtours,,0out_0in,work
+10828453,264108,othdiscr,1,1,1,1,non_mandatory,1,2000.0,9000.0,226869,86.0,10.0,11.0,1.0,,15.147286912583295,WALK_LRF,2.687064756639405,,,0out_1in,othdiscr
 13271288,323689,work,1,1,1,1,mandatory,1,12000.0,10000.0,256660,110.0,11.0,22.0,11.0,,,WALK_LRF,5.412375093576443,no_subtours,,0out_0in,work
-13342710,325431,work,1,1,1,1,mandatory,1,2000.0,16000.0,257531,47.0,7.0,17.0,10.0,,,TNC_SINGLE,5.978763988078055,no_subtours,,1out_3in,work
-13342745,325432,shopping,1,1,1,1,non_mandatory,1,16000.0,16000.0,257531,113.0,12.0,13.0,1.0,,13.946558403927142,TAXI,2.291129079425163,,,0out_0in,shopping
-24423157,595686,school,1,1,1,1,mandatory,1,8000.0,21000.0,370497,46.0,7.0,16.0,9.0,,,WALK_LOC,19.491065325432032,,,0out_0in,school
-26415929,644290,work,1,1,1,1,mandatory,1,15000.0,7000.0,386699,120.0,12.0,20.0,8.0,,,WALK_LOC,5.317189317596288,no_subtours,,0out_0in,work
-26415959,644291,othmaint,1,1,1,1,non_mandatory,1,5000.0,7000.0,386699,179.0,19.0,23.0,4.0,,14.895762633410888,TNC_SINGLE,2.2474868864771897,,,0out_0in,othmaint
-26415970,644291,work,1,1,1,1,mandatory,1,16000.0,7000.0,386699,47.0,7.0,17.0,10.0,,,WALK_LOC,5.341486030293974,no_subtours,,0out_0in,work
-26416003,644292,school,1,1,1,1,mandatory,1,8000.0,7000.0,386699,63.0,8.0,17.0,9.0,,,WALK,18.40789860586593,,,0out_1in,school
-26423525,644476,escort,1,1,1,3,non_mandatory,1,13000.0,16000.0,386761,1.0,5.0,6.0,1.0,,12.581876553213043,TNC_SINGLE,-0.46396326059485016,,,0out_0in,escort
-26423541,644476,othdiscr,1,1,3,3,non_mandatory,1,16000.0,16000.0,386761,169.0,18.0,18.0,0.0,,14.498085969309562,WALK,1.901940250188323,,,0out_0in,othdiscr
-26423544,644476,othmaint,1,1,2,3,non_mandatory,1,17000.0,16000.0,386761,170.0,18.0,19.0,1.0,,14.068392638775942,WALK,0.9056380321032911,,,0out_0in,othmaint
+13342710,325431,work,1,1,1,1,mandatory,1,2000.0,16000.0,257531,47.0,7.0,17.0,10.0,,,TNC_SINGLE,5.944780818287768,no_subtours,,1out_3in,work
+13342745,325432,shopping,1,1,1,1,non_mandatory,1,16000.0,16000.0,257531,113.0,12.0,13.0,1.0,,13.944106686960234,TAXI,2.291129079425163,,,0out_0in,shopping
+24423157,595686,school,1,1,1,1,mandatory,1,8000.0,21000.0,370497,46.0,7.0,16.0,9.0,,,WALK_LOC,19.48702945868035,,,0out_0in,school
+26415929,644290,work,1,1,1,1,mandatory,1,15000.0,7000.0,386699,120.0,12.0,20.0,8.0,,,WALK_LOC,5.334455039205838,no_subtours,,0out_0in,work
+26415959,644291,othmaint,1,1,1,1,non_mandatory,1,5000.0,7000.0,386699,179.0,19.0,23.0,4.0,,14.907716944334291,TNC_SINGLE,2.261313926535724,,,0out_0in,othmaint
+26415970,644291,work,1,1,1,1,mandatory,1,16000.0,7000.0,386699,47.0,7.0,17.0,10.0,,,BIKE,5.359690496596561,no_subtours,,0out_0in,work
+26416003,644292,school,1,1,1,1,mandatory,1,8000.0,7000.0,386699,63.0,8.0,17.0,9.0,,,WALK,18.490744676608564,,,0out_1in,school
+26423525,644476,escort,1,1,1,3,non_mandatory,1,13000.0,16000.0,386761,1.0,5.0,6.0,1.0,,12.580679005044448,TNC_SINGLE,-0.4730064864579607,,,0out_0in,escort
+26423541,644476,othdiscr,1,1,3,3,non_mandatory,1,16000.0,16000.0,386761,169.0,18.0,18.0,0.0,,14.492065906423075,WALK,1.901940250188323,,,0out_0in,othdiscr
+26423544,644476,othmaint,1,1,2,3,non_mandatory,1,17000.0,16000.0,386761,170.0,18.0,19.0,1.0,,14.044888340516325,WALK,0.8670492236443096,,,0out_0in,othmaint
 26423555,644476,work,1,1,1,1,mandatory,1,12000.0,16000.0,386761,47.0,7.0,17.0,10.0,,,SHARED3FREE,1.6248633577252904,no_subtours,,0out_0in,work
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 66923560,1632281,work,1,1,1,1,mandatory,1,14000.0,12000.0,823501,49.0,7.0,19.0,12.0,,,TNC_SINGLE,5.653100213975966,eat,,0out_0in,work
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 159535221,3891102,work,1,1,1,1,mandatory,1,16000.0,16000.0,1747467,46.0,7.0,16.0,9.0,,,WALK,6.0209119268256845,no_subtours,,0out_0in,work
-159535256,3891103,shopping,1,1,1,1,non_mandatory,1,11000.0,16000.0,1747467,127.0,13.0,16.0,3.0,,14.127933345341821,WALK,2.057932115988009,,,0out_0in,shopping
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-159535290,3891104,othdiscr,2,2,2,2,non_mandatory,1,12000.0,16000.0,1747467,159.0,16.0,21.0,5.0,,15.300736230802341,WALK,2.430809471509179,,,0out_0in,othdiscr
-159535295,3891104,school,1,1,1,1,mandatory,1,11000.0,16000.0,1747467,44.0,7.0,14.0,7.0,,,WALK_LOC,18.547431187904532,,,0out_0in,school
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-207350891,5057338,shopping,1,1,1,4,non_mandatory,1,5000.0,7000.0,2048382,184.0,21.0,21.0,0.0,,14.045243030726178,WALK,2.4767035321732807,,,0out_0in,shopping
-207350894,5057338,social,1,1,4,4,non_mandatory,1,10000.0,7000.0,2048382,170.0,18.0,19.0,1.0,,14.197665108665898,TNC_SINGLE,1.5003587157336247,,,0out_0in,social
-207350897,5057338,work,1,1,1,1,mandatory,1,4000.0,7000.0,2048382,30.0,6.0,17.0,11.0,,,WALK_HVY,6.089461732812542,no_subtours,,0out_0in,work
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-220958270,5389226,eat,1,1,1,1,atwork,1,13000.0,21000.0,2223759,124.0,13.0,13.0,0.0,,15.390793766009658,WALK,5.217176623966586,,220958305.0,0out_0in,atwork
-220958279,5389226,eatout,1,1,1,1,joint,2,16000.0,16000.0,2223759,180.0,20.0,20.0,0.0,adults,15.550443736976591,SHARED3FREE,-0.12339418016080342,,,0out_0in,eatout
-220958305,5389226,work,1,1,1,1,mandatory,1,21000.0,16000.0,2223759,79.0,9.0,18.0,9.0,,,WALK,5.594816637326808,eat,,0out_0in,work
-220958346,5389227,work,1,1,1,1,mandatory,1,23000.0,16000.0,2223759,33.0,6.0,20.0,14.0,,,WALK,5.963177339355437,no_subtours,,0out_0in,work
-299527179,7305540,work,1,1,1,1,mandatory,1,1000.0,20000.0,2727273,92.0,10.0,17.0,7.0,,,SHARED2FREE,1.5968783546169214,no_subtours,,0out_0in,work
-299527220,7305541,work,1,1,1,1,mandatory,1,2000.0,20000.0,2727273,30.0,6.0,17.0,11.0,,,WALK_LRF,1.8337919496696489,no_subtours,,0out_0in,work
-305589966,7453413,shopping,1,1,1,1,non_mandatory,1,11000.0,20000.0,2762078,154.0,16.0,16.0,0.0,,13.74349439306216,WALK,1.9460445188128115,,,0out_0in,shopping
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-307996508,7512109,work,1,1,1,1,mandatory,1,2000.0,8000.0,2820774,65.0,8.0,19.0,11.0,,,WALK,-0.6109251432310259,eat,,0out_2in,work
-308013080,7512514,eatout,1,1,2,3,non_mandatory,1,19000.0,8000.0,2821179,62.0,8.0,16.0,8.0,,15.449771888666286,WALK,2.747134675357118,,,0out_0in,eatout
-308013107,7512514,shopping,1,1,1,3,non_mandatory,1,6000.0,8000.0,2821179,164.0,17.0,19.0,2.0,,13.523855473428197,WALK,1.94763511672055,,,0out_0in,shopping
-308013110,7512514,social,1,1,3,3,non_mandatory,1,16000.0,8000.0,2821179,154.0,16.0,16.0,0.0,,13.809556083805864,WALK_LOC,0.11039708532866249,,,0out_0in,social
-308050751,7513432,work,1,1,1,1,mandatory,1,9000.0,8000.0,2822097,10.0,5.0,15.0,10.0,,,BIKE,0.15412267830481513,no_subtours,,0out_0in,work
-308055753,7513554,work,1,1,1,1,mandatory,1,7000.0,8000.0,2822219,11.0,5.0,16.0,11.0,,,WALK,5.9584484609380315,no_subtours,,0out_0in,work
-308056204,7513565,work,1,1,1,1,mandatory,1,12000.0,8000.0,2822230,82.0,9.0,21.0,12.0,,,WALK,5.826459127951694,no_subtours,,1out_1in,work
-308464222,7523517,othdiscr,1,1,1,1,non_mandatory,1,16000.0,7000.0,2832182,59.0,8.0,13.0,5.0,,14.913267787577855,WALK_LOC,1.6792639151657363,,,0out_0in,othdiscr
+207343599,5057160,work,1,1,1,1,mandatory,1,15000.0,5000.0,2048204,44.0,7.0,14.0,7.0,,,TNC_SINGLE,5.663511077411845,no_subtours,,0out_0in,work
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+207350886,5057338,othmaint,1,1,2,4,non_mandatory,1,9000.0,7000.0,2048382,169.0,18.0,18.0,0.0,,15.19204811997096,WALK,2.391154734266366,,,0out_0in,othmaint
+207350891,5057338,shopping,1,1,1,4,non_mandatory,1,5000.0,7000.0,2048382,184.0,21.0,21.0,0.0,,14.057479715828364,WALK,2.499856382786048,,,0out_0in,shopping
+207350894,5057338,social,1,1,4,4,non_mandatory,1,10000.0,7000.0,2048382,170.0,18.0,19.0,1.0,,14.209834378052138,TNC_SINGLE,1.493103756086411,,,0out_0in,social
+207350897,5057338,work,1,1,1,1,mandatory,1,4000.0,7000.0,2048382,30.0,6.0,17.0,11.0,,,WALK_HVY,6.105326000940647,no_subtours,,0out_0in,work
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+220958279,5389226,eatout,1,1,1,1,joint,2,16000.0,16000.0,2223759,180.0,20.0,20.0,0.0,adults,15.538239187772206,SHARED3FREE,-0.1233941801608034,,,0out_0in,eatout
+220958305,5389226,work,1,1,1,1,mandatory,1,21000.0,16000.0,2223759,79.0,9.0,18.0,9.0,,,WALK,5.633223787931471,eat,,0out_0in,work
+220958346,5389227,work,1,1,1,1,mandatory,1,23000.0,16000.0,2223759,33.0,6.0,20.0,14.0,,,WALK,5.94517128425738,no_subtours,,0out_0in,work
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+299527220,7305541,work,1,1,1,1,mandatory,1,2000.0,20000.0,2727273,30.0,6.0,17.0,11.0,,,WALK_LRF,1.798877801909233,no_subtours,,0out_0in,work
+305589966,7453413,shopping,1,1,1,1,non_mandatory,1,11000.0,20000.0,2762078,154.0,16.0,16.0,0.0,,13.73465020559868,WALK,1.9282735688120127,,,0out_0in,shopping
+307996473,7512109,eat,1,1,1,1,atwork,1,5000.0,2000.0,2820774,85.0,10.0,10.0,0.0,,20.4528526875155,WALK,0.144340451165291,,307996508.0,0out_1in,atwork
+307996508,7512109,work,1,1,1,1,mandatory,1,2000.0,8000.0,2820774,65.0,8.0,19.0,11.0,,,WALK,-0.63849758689409,eat,,0out_2in,work
+308013080,7512514,eatout,1,1,2,3,non_mandatory,1,19000.0,8000.0,2821179,62.0,8.0,16.0,8.0,,15.433907950780627,WALK,2.823219314447263,,,0out_0in,eatout
+308013107,7512514,shopping,1,1,1,3,non_mandatory,1,6000.0,8000.0,2821179,164.0,17.0,19.0,2.0,,13.512217317393723,WALK,1.7791394840063146,,,0out_0in,shopping
+308013110,7512514,social,1,1,3,3,non_mandatory,1,16000.0,8000.0,2821179,154.0,16.0,16.0,0.0,,13.794538448328227,WALK_LOC,0.0836844432714275,,,0out_0in,social
+308050751,7513432,work,1,1,1,1,mandatory,1,9000.0,8000.0,2822097,10.0,5.0,15.0,10.0,,,BIKE,0.1541226783048151,no_subtours,,0out_0in,work
+308055753,7513554,work,1,1,1,1,mandatory,1,7000.0,8000.0,2822219,11.0,5.0,16.0,11.0,,,WALK,5.8674311173207885,no_subtours,,0out_0in,work
+308056204,7513565,work,1,1,1,1,mandatory,1,12000.0,8000.0,2822230,82.0,9.0,21.0,12.0,,,WALK,5.818260825925703,no_subtours,,1out_1in,work
+308464222,7523517,othdiscr,1,1,1,1,non_mandatory,1,16000.0,7000.0,2832182,59.0,8.0,13.0,5.0,,14.941709019837395,WALK_LOC,1.725989964213542,,,0out_0in,othdiscr
diff --git a/activitysim/examples/example_multiple_zone/test/regress/final_tours_3_zone.csv b/activitysim/examples/example_multiple_zone/test/regress/final_tours_3_zone.csv
index bc8c884a7..f9d83aace 100644
--- a/activitysim/examples/example_multiple_zone/test/regress/final_tours_3_zone.csv
+++ b/activitysim/examples/example_multiple_zone/test/regress/final_tours_3_zone.csv
@@ -1,56 +1,56 @@
 tour_id,person_id,tour_type,tour_type_count,tour_type_num,tour_num,tour_count,tour_category,number_of_participants,destination,origin,household_id,tdd,start,end,duration,composition,destination_logsum,tour_mode,mode_choice_logsum,od_atap,od_btap,od_path_set,do_atap,do_btap,do_path_set,atwork_subtour_frequency,parent_tour_id,stop_frequency,primary_purpose
 1136791,27726,othdiscr,1,1,1,1,non_mandatory,1,13000.0,10000.0,27726,56.0,8.0,10.0,2.0,,15.594097665802533,WALK,2.065476776384414,,,,,,,,,0out_0in,othdiscr
-4594649,112064,othdiscr,1,1,2,2,non_mandatory,1,12000.0,16000.0,112064,114.0,12.0,14.0,2.0,,13.90196832766947,WALK,-0.19978895313346412,,,,,,,,,0out_0in,othdiscr
-4594657,112064,shopping,1,1,1,2,non_mandatory,1,11000.0,16000.0,112064,155.0,16.0,17.0,1.0,,12.640227542230269,WALK,-0.6420878545030504,,,,,,,,,0out_0in,shopping
+4594649,112064,othdiscr,1,1,2,2,non_mandatory,1,12000.0,16000.0,112064,114.0,12.0,14.0,2.0,,13.90196832766947,WALK,-0.1997889531334641,,,,,,,,,0out_0in,othdiscr
+4594657,112064,shopping,1,1,1,2,non_mandatory,1,11000.0,16000.0,112064,155.0,16.0,17.0,1.0,,12.640227542230267,WALK,-0.6420878545030504,,,,,,,,,0out_0in,shopping
 24423157,595686,school,1,1,1,1,mandatory,1,8000.0,21000.0,370497,46.0,7.0,16.0,9.0,,,WALK,16.647534667069763,,,,,,,,,0out_0in,school
 26423525,644476,escort,1,1,1,3,non_mandatory,1,13000.0,16000.0,386761,1.0,5.0,6.0,1.0,,12.577060490434311,TNC_SINGLE,-0.4760916910196014,,,,,,,,,0out_0in,escort
-26423541,644476,othdiscr,1,1,3,3,non_mandatory,1,16000.0,16000.0,386761,169.0,18.0,18.0,0.0,,14.293983756200822,WALK,1.9022644572358094,,,,,,,,,0out_0in,othdiscr
+26423541,644476,othdiscr,1,1,3,3,non_mandatory,1,16000.0,16000.0,386761,169.0,18.0,18.0,0.0,,14.293983756200822,WALK,1.9022644572358092,,,,,,,,,0out_0in,othdiscr
 26423544,644476,othmaint,1,1,2,3,non_mandatory,1,17000.0,16000.0,386761,170.0,18.0,19.0,1.0,,14.038653631364522,WALK,0.8559887465990159,,,,,,,,,0out_0in,othmaint
 26423555,644476,work,1,1,1,1,mandatory,1,12000.0,16000.0,386761,47.0,7.0,17.0,10.0,,,WALK,1.3476258300230164,,,,,,,no_subtours,,0out_0in,work
-26423590,644477,shopping,1,1,1,1,non_mandatory,1,12000.0,16000.0,386761,135.0,14.0,14.0,0.0,,13.60215185113449,WALK,1.1721200473268165,,,,,,,,,0out_0in,shopping
+26423590,644477,shopping,1,1,1,1,non_mandatory,1,12000.0,16000.0,386761,135.0,14.0,14.0,0.0,,13.60215185113449,WALK,1.1721200473268163,,,,,,,,,0out_0in,shopping
 26423629,644478,school,1,1,1,1,mandatory,1,25000.0,16000.0,386761,62.0,8.0,16.0,8.0,,,BIKE,1.0040421119153422,,,,,,,,,0out_0in,school
 64479052,1572659,shopping,1,1,1,1,non_mandatory,1,19000.0,6000.0,763879,50.0,7.0,20.0,13.0,,12.677909578974518,SHARED3FREE,-1.616231197958132,,,,,,,,,3out_0in,shopping
 66952506,1632987,work,1,1,1,1,mandatory,1,17000.0,18000.0,824207,153.0,15.0,23.0,8.0,,,TNC_SINGLE,5.8611730579617145,,,,,,,no_subtours,,0out_0in,work
 76904600,1875721,work,1,1,1,1,mandatory,1,4000.0,16000.0,982875,64.0,8.0,18.0,10.0,,,WALK,1.5052241256568006,,,,,,,no_subtours,,0out_0in,work
 76904608,1875722,eatout,1,1,1,1,non_mandatory,1,17000.0,16000.0,982875,91.0,10.0,16.0,6.0,,14.140172741499743,WALK,2.395595382646947,,,,,,,,,1out_0in,eatout
 88521376,2159057,work,1,1,1,1,mandatory,1,21000.0,20000.0,1099626,48.0,7.0,18.0,11.0,,,DRIVEALONEFREE,-0.3153677819844578,,,,,,,no_subtours,,0out_3in,work
-88521409,2159058,school,1,1,1,1,mandatory,1,10000.0,20000.0,1099626,145.0,15.0,15.0,0.0,,,DRIVEALONEFREE,0.4811821103637486,,,,,,,,,0out_0in,univ
+88521409,2159058,school,1,1,1,1,mandatory,1,10000.0,20000.0,1099626,145.0,15.0,15.0,0.0,,,DRIVEALONEFREE,0.4811821103637484,,,,,,,,,0out_0in,univ
 88521450,2159059,school,1,1,1,1,mandatory,1,11000.0,20000.0,1099626,58.0,8.0,12.0,4.0,,,WALK,-0.8314959414195158,,,,,,,,,0out_0in,school
 100798519,2458502,shopping,1,1,1,1,joint,2,5000.0,8000.0,1173905,54.0,8.0,8.0,0.0,children,12.841661180218818,SHARED2FREE,-0.5111781689711135,,,,,,,,,0out_0in,shopping
-100798528,2458500,othmaint,1,1,1,1,non_mandatory,1,9000.0,8000.0,1173905,120.0,12.0,20.0,8.0,,13.897809230924173,WALK,-0.10722510977471159,,,,,,,,,0out_0in,othmaint
+100798528,2458500,othmaint,1,1,1,1,non_mandatory,1,9000.0,8000.0,1173905,120.0,12.0,20.0,8.0,,13.897809230924173,WALK,-0.1072251097747115,,,,,,,,,0out_0in,othmaint
 100798550,2458501,escort,1,1,1,1,non_mandatory,1,17000.0,8000.0,1173905,146.0,15.0,16.0,1.0,,12.4507509504386,WALK,-2.059329270226747,,,,,,,,,0out_0in,escort
 100798613,2458502,school,1,1,1,1,mandatory,1,8000.0,8000.0,1173905,64.0,8.0,18.0,10.0,,,WALK,0.2004682500962975,,,,,,,,,1out_0in,school
 100798654,2458503,school,1,1,1,1,mandatory,1,8000.0,8000.0,1173905,60.0,8.0,14.0,6.0,,,WALK,0.2158669940821465,,,,,,,,,0out_0in,school
 105234657,2566698,work,1,1,1,1,mandatory,1,4000.0,25000.0,1196298,31.0,6.0,18.0,12.0,,,WALK,5.795454735883026,,,,,,,no_subtours,,0out_0in,work
 105234731,2566700,school,1,1,1,1,mandatory,1,6000.0,25000.0,1196298,45.0,7.0,15.0,8.0,,,WALK,17.13022184716841,,,,,,,,,0out_0in,school
 105234772,2566701,school,1,1,1,1,mandatory,1,8000.0,25000.0,1196298,59.0,8.0,13.0,5.0,,,WALK,16.148071382762,,,,,,,,,0out_0in,school
-105234813,2566702,school,1,1,1,1,mandatory,1,25000.0,25000.0,1196298,120.0,12.0,20.0,8.0,,,WALK,18.288899012151962,,,,,,,,,0out_0in,school
+105234813,2566702,school,1,1,1,1,mandatory,1,25000.0,25000.0,1196298,120.0,12.0,20.0,8.0,,,WALK,18.28889901215196,,,,,,,,,0out_0in,school
 120410774,2936848,eatout,1,1,2,2,non_mandatory,1,6000.0,11000.0,1286557,136.0,14.0,15.0,1.0,,13.36987778840149,BIKE,0.5241078468963517,,,,,,,,,0out_0in,eatout
-120410793,2936848,othdiscr,1,1,1,2,non_mandatory,1,25000.0,11000.0,1286557,146.0,15.0,16.0,1.0,,13.966689174541301,WALK,0.012362324935874731,,,,,,,,,0out_0in,othdiscr
-125537687,3061894,shopping,1,1,1,1,non_mandatory,1,5000.0,24000.0,1363467,113.0,12.0,13.0,1.0,,12.664750271989753,SHARED3FREE,0.14699044649529297,,,,,,,,,0out_0in,shopping
+120410793,2936848,othdiscr,1,1,1,2,non_mandatory,1,25000.0,11000.0,1286557,146.0,15.0,16.0,1.0,,13.9666891745413,WALK,0.0123623249358747,,,,,,,,,0out_0in,othdiscr
+125537687,3061894,shopping,1,1,1,1,non_mandatory,1,5000.0,24000.0,1363467,113.0,12.0,13.0,1.0,,12.664750271989751,SHARED3FREE,0.1469904464952929,,,,,,,,,0out_0in,shopping
 125537723,3061895,othmaint,1,1,1,1,non_mandatory,1,4000.0,24000.0,1363467,148.0,15.0,18.0,3.0,,13.757864551320312,DRIVEALONEFREE,0.2119390839292166,,,,,,,,,0out_0in,othmaint
-125537734,3061895,work,1,1,1,1,mandatory,1,2000.0,24000.0,1363467,27.0,6.0,14.0,8.0,,,BIKE,-0.10161215677732775,,,,,,,no_subtours,,0out_0in,work
+125537734,3061895,work,1,1,1,1,mandatory,1,2000.0,24000.0,1363467,27.0,6.0,14.0,8.0,,,BIKE,-0.1016121567773277,,,,,,,no_subtours,,0out_0in,work
 171036246,4171615,school,1,1,1,1,mandatory,1,12000.0,16000.0,1810015,124.0,13.0,13.0,0.0,,,WALK,2.7875704923197806,,,,,,,,,0out_0in,univ
-171036284,4171616,othmaint,1,1,1,1,non_mandatory,1,16000.0,16000.0,1810015,72.0,9.0,11.0,2.0,,14.048331037883719,WALK,0.9584746360827197,,,,,,,,,0out_0in,othmaint
+171036284,4171616,othmaint,1,1,1,1,non_mandatory,1,16000.0,16000.0,1810015,72.0,9.0,11.0,2.0,,14.04833103788372,WALK,0.9584746360827197,,,,,,,,,0out_0in,othmaint
 171036336,4171617,work,1,1,1,1,mandatory,1,14000.0,16000.0,1810015,79.0,9.0,18.0,9.0,,,WALK,1.5999891985673405,,,,,,,no_subtours,,1out_0in,work
 171036412,4171619,shopping,1,1,1,1,non_mandatory,1,16000.0,16000.0,1810015,126.0,13.0,15.0,2.0,,13.393258348224926,WALK,1.7788864832580635,,,,,,,,,0out_1in,shopping
 171036451,4171620,school,1,1,1,1,mandatory,1,16000.0,16000.0,1810015,45.0,7.0,15.0,8.0,,,WALK,2.547353634153898,,,,,,,,,0out_0in,school
-171036535,4171622,shopping,1,1,1,1,non_mandatory,1,23000.0,16000.0,1810015,76.0,9.0,15.0,6.0,,13.411461181311836,TNC_SHARED,0.49949121416688186,,,,,,,,,0out_0in,shopping
-171036547,4171623,eat,1,1,1,1,atwork,1,1000.0,24000.0,1810015,85.0,10.0,10.0,0.0,,12.741496895467327,WALK,0.1219360412944585,,,,,,,,171036582.0,0out_1in,atwork
+171036535,4171622,shopping,1,1,1,1,non_mandatory,1,23000.0,16000.0,1810015,76.0,9.0,15.0,6.0,,13.411461181311836,TNC_SHARED,0.4994912141668818,,,,,,,,,0out_0in,shopping
+171036547,4171623,eat,1,1,1,1,atwork,1,1000.0,24000.0,1810015,85.0,10.0,10.0,0.0,,12.741496895467328,WALK,0.1219360412944585,,,,,,,,171036582.0,0out_1in,atwork
 171036582,4171623,work,1,1,1,1,mandatory,1,24000.0,16000.0,1810015,68.0,8.0,22.0,14.0,,,WALK,1.3582411459531345,,,,,,,eat,,1out_1in,work
-197775705,4823797,othmaint,1,1,1,1,non_mandatory,1,13000.0,14000.0,1952792,71.0,9.0,10.0,1.0,,13.806978998355872,WALK,-0.11357307167335845,,,,,,,,,0out_0in,othmaint
+197775705,4823797,othmaint,1,1,1,1,non_mandatory,1,13000.0,14000.0,1952792,71.0,9.0,10.0,1.0,,13.806978998355872,WALK,-0.1135730716733584,,,,,,,,,0out_0in,othmaint
 197775716,4823797,work,1,1,1,1,mandatory,1,14000.0,14000.0,1952792,106.0,11.0,18.0,7.0,,,WALK,-0.5344528628897721,,,,,,,no_subtours,,0out_0in,work
 220898281,5387762,work,1,1,1,1,mandatory,1,23000.0,9000.0,2223027,47.0,7.0,17.0,10.0,,,TNC_SINGLE,3.8857326280519513,,,,,,,no_subtours,,0out_0in,work
 220898322,5387763,work,1,1,1,1,mandatory,1,5000.0,9000.0,2223027,63.0,8.0,17.0,9.0,,,WALK,5.300836464088856,,,,,,,no_subtours,,0out_3in,work
 220958270,5389226,eat,1,1,1,1,atwork,1,13000.0,21000.0,2223759,124.0,13.0,13.0,0.0,,15.351749667298796,WALK,5.201699768874482,,,,,,,,220958305.0,0out_0in,atwork
-220958279,5389226,eatout,1,1,1,1,joint,2,16000.0,16000.0,2223759,184.0,21.0,21.0,0.0,adults,15.465406223823532,SHARED3FREE,-0.12339417809063187,,,,,,,,,0out_0in,eatout
+220958279,5389226,eatout,1,1,1,1,joint,2,16000.0,16000.0,2223759,184.0,21.0,21.0,0.0,adults,15.465406223823532,SHARED3FREE,-0.1233941780906318,,,,,,,,,0out_0in,eatout
 220958305,5389226,work,1,1,1,1,mandatory,1,21000.0,16000.0,2223759,79.0,9.0,18.0,9.0,,,TNC_SINGLE,5.319455769031263,,,,,,,eat,,0out_1in,work
 220958346,5389227,work,1,1,1,1,mandatory,1,23000.0,16000.0,2223759,34.0,6.0,21.0,15.0,,,TNC_SINGLE,5.139246648693768,,,,,,,no_subtours,,0out_1in,work
 299527179,7305540,work,1,1,1,1,mandatory,1,1000.0,20000.0,2727273,94.0,10.0,19.0,9.0,,,SHARED2FREE,0.3063757736281831,,,,,,,no_subtours,,0out_0in,work
 299527220,7305541,work,1,1,1,1,mandatory,1,5000.0,20000.0,2727273,31.0,6.0,18.0,12.0,,,WALK,1.2334944217411743,,,,,,,no_subtours,,0out_0in,work
-305589966,7453413,shopping,1,1,1,1,non_mandatory,1,13000.0,20000.0,2762078,154.0,16.0,16.0,0.0,,13.304041130785397,SHARED2FREE,0.25627499017538097,,,,,,,,,0out_0in,shopping
-308013080,7512514,eatout,1,1,2,3,non_mandatory,1,19000.0,8000.0,2821179,62.0,8.0,16.0,8.0,,15.421103335257841,WALK,2.8152299951807986,,,,,,,,,0out_0in,eatout
+305589966,7453413,shopping,1,1,1,1,non_mandatory,1,13000.0,20000.0,2762078,154.0,16.0,16.0,0.0,,13.304041130785397,SHARED2FREE,0.2562749901753809,,,,,,,,,0out_0in,shopping
+308013080,7512514,eatout,1,1,2,3,non_mandatory,1,19000.0,8000.0,2821179,62.0,8.0,16.0,8.0,,15.42110333525784,WALK,2.815229995180798,,,,,,,,,0out_0in,eatout
 308013107,7512514,shopping,1,1,1,3,non_mandatory,1,6000.0,8000.0,2821179,164.0,17.0,19.0,2.0,,13.490189175869636,WALK,1.8186055749755816,,,,,,,,,0out_0in,shopping
 308013110,7512514,social,1,1,3,3,non_mandatory,1,12000.0,8000.0,2821179,154.0,16.0,16.0,0.0,,13.697747127579213,WALK,0.5229748996141723,,,,,,,,,0out_0in,social
 308056204,7513565,work,1,1,1,1,mandatory,1,12000.0,8000.0,2822230,82.0,9.0,21.0,12.0,,,TNC_SINGLE,5.403217136871605,,,,,,,no_subtours,,1out_2in,work
-308464222,7523517,othdiscr,1,1,1,1,non_mandatory,1,16000.0,7000.0,2832182,59.0,8.0,13.0,5.0,,15.601891670337523,WALK,2.59495659641145,,,,,,,,,0out_0in,othdiscr
+308464222,7523517,othdiscr,1,1,1,1,non_mandatory,1,16000.0,7000.0,2832182,59.0,8.0,13.0,5.0,,15.601891670337524,WALK,2.59495659641145,,,,,,,,,0out_0in,othdiscr
diff --git a/activitysim/examples/example_multiple_zone/test/regress/final_trips_2_zone.csv b/activitysim/examples/example_multiple_zone/test/regress/final_trips_2_zone.csv
index 986afb54c..a26e48e7b 100644
--- a/activitysim/examples/example_multiple_zone/test/regress/final_trips_2_zone.csv
+++ b/activitysim/examples/example_multiple_zone/test/regress/final_trips_2_zone.csv
@@ -7,50 +7,50 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 8805125,26844,26844,social,1,False,2,7000,7000,1100640,othmaint,43.21727834653041,12,WALK,9.041583184270134
 8805126,26844,26844,social,2,False,2,8000,7000,1100640,home,,12,WALK,8.789583223221504
 9094329,27726,27726,othdiscr,1,True,1,17000,10000,1136791,othdiscr,,8,WALK_LRF,6.246319410004664
-9094333,27726,27726,othdiscr,1,False,2,7000,17000,1136791,othmaint,45.878812809837484,10,WALK_LOC,5.420568603137892
+9094333,27726,27726,othdiscr,1,False,2,7000,17000,1136791,othmaint,45.87881280983749,10,WALK_LOC,5.420568603137892
 9094334,27726,27726,othdiscr,2,False,2,10000,7000,1136791,home,,10,WALK,14.0446786870029
-9717265,29625,29625,shopping,1,True,1,16000,17000,1214658,shopping,,15,WALK_LRF,7.7227647817392215
+9717265,29625,29625,shopping,1,True,1,16000,17000,1214658,shopping,,15,WALK_LRF,7.722764781739221
 9717269,29625,29625,shopping,1,False,1,17000,16000,1214658,home,,15,WALK_LRF,7.750777336471436
 36757193,112064,112064,othdiscr,1,True,1,9000,16000,4594649,othdiscr,,12,WALK,6.334866199627338
 36757197,112064,112064,othdiscr,1,False,1,16000,9000,4594649,home,,14,WALK,6.41776041987002
 36757257,112064,112064,shopping,1,True,1,11000,16000,4594657,shopping,,16,WALK,3.964291128688904
-36757261,112064,112064,shopping,1,False,1,16000,11000,4594657,home,,17,WALK,3.9642911737175996
+36757261,112064,112064,shopping,1,False,1,16000,11000,4594657,home,,17,WALK,3.9642911737176
 86627409,264107,226869,work,1,True,1,15000,9000,10828426,work,,7,WALK_LRF,1.451342899763582
 86627413,264107,226869,work,1,False,1,9000,15000,10828426,home,,19,WALK_LRF,1.4433154732713112
 86627625,264108,226869,othdiscr,1,True,1,2000,9000,10828453,othdiscr,,10,WALK_LRF,0.8013218089436901
-86627629,264108,226869,othdiscr,1,False,2,25000,2000,10828453,escort,32.83572582954258,11,WALK,0.13356568233554925
-86627630,264108,226869,othdiscr,2,False,2,9000,25000,10828453,home,,11,WALK_LOC,12.099030970556205
+86627629,264108,226869,othdiscr,1,False,2,25000,2000,10828453,escort,32.83572582954258,11,WALK,0.1335656823355492
+86627630,264108,226869,othdiscr,2,False,2,9000,25000,10828453,home,,11,WALK_LOC,12.099030970556203
 106170305,323689,256660,work,1,True,1,12000,10000,13271288,work,,11,WALK_LOC,3.790246557613184
 106170309,323689,256660,work,1,False,1,10000,12000,13271288,home,,22,WALK,4.748576623945167
 106741681,325431,257531,work,1,True,2,9000,16000,13342710,shopping,25.31057249036081,7,WALK_LOC,8.098099269775245
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@@ -59,9 +59,9 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
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@@ -71,11 +71,11 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
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@@ -85,33 +85,33 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
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@@ -120,20 +120,20 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
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@@ -141,11 +141,11 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
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-1060575585,3233462,1445222,eatout,1,True,1,13000,17000,132571948,eatout,,15,WALK,-1.1160192989307063
+1045823393,3188485,1402945,work,1,True,2,7000,25000,130727924,escort,30.71610667465545,10,WALK_LOC,11.388230172922947
+1045823394,3188485,1402945,work,2,True,2,1000,7000,130727924,work,,12,WALK,-0.1910319526120294
+1045823397,3188485,1402945,work,1,False,2,7000,1000,130727924,eatout,30.600694971829377,20,WALK_LOC,-0.1403015748111612
+1045823398,3188485,1402945,work,2,False,2,25000,7000,130727924,home,,21,WALK_LOC,11.127235612355737
+1060575585,3233462,1445222,eatout,1,True,1,13000,17000,132571948,eatout,,15,WALK,-1.1160192989307065
 1060575589,3233462,1445222,eatout,1,False,1,17000,13000,132571948,home,,16,WALK,-0.9879831518349294
 1060575801,3233462,1445222,shopping,1,True,1,16000,17000,132571975,shopping,,17,WALK,7.877905760508009
 1060575805,3233462,1445222,shopping,1,False,1,17000,16000,132571975,home,,17,WALK_LRF,7.904087004402969
@@ -175,7 +175,7 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 1179607662,3596364,1645132,shopping,2,False,3,9000,6000,147450957,eatout,53.25987044962454,20,WALK_LOC,12.56862958476763
 1179607663,3596364,1645132,shopping,3,False,3,9000,9000,147450957,home,,20,WALK,10.764874611342488
 1179608009,3596365,1645132,social,1,True,1,2000,9000,147451001,social,,7,WALK_LRF,0.9214229436290624
-1179608013,3596365,1645132,social,1,False,1,9000,2000,147451001,home,,18,WALK_LRF,0.9093976853000073
+1179608013,3596365,1645132,social,1,False,1,9000,2000,147451001,home,,18,WALK_LRF,0.9093976853000072
 1276281769,3891102,1747467,work,1,True,1,16000,16000,159535221,work,,7,WALK,5.450624849962253
 1276281773,3891102,1747467,work,1,False,1,16000,16000,159535221,home,,16,WALK,5.450624852553868
 1276282049,3891103,1747467,shopping,1,True,1,11000,16000,159535256,shopping,,13,WALK,3.964301596438192
@@ -190,12 +190,12 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 1368289973,4171615,1810015,univ,1,False,1,16000,12000,171036246,home,,13,WALK,4.06117926693834
 1368290273,4171616,1810015,othmaint,1,True,1,16000,16000,171036284,othmaint,,9,WALK,4.598226175910151
 1368290277,4171616,1810015,othmaint,1,False,1,16000,16000,171036284,home,,11,WALK,4.598226175910151
-1368290689,4171617,1810015,work,1,True,2,8000,16000,171036336,social,22.030187912204873,9,WALK,7.896576327414681
-1368290690,4171617,1810015,work,2,True,2,13000,8000,171036336,work,,12,WALK,-1.5549473695247127
+1368290689,4171617,1810015,work,1,True,2,8000,16000,171036336,social,22.030187912204877,9,WALK,7.896576327414681
+1368290690,4171617,1810015,work,2,True,2,13000,8000,171036336,work,,12,WALK,-1.554947369524713
 1368290693,4171617,1810015,work,1,False,1,16000,13000,171036336,home,,18,WALK,-0.8614634025483249
-1368291297,4171619,1810015,shopping,1,True,1,16000,16000,171036412,shopping,,13,WALK,7.3308794494701575
-1368291301,4171619,1810015,shopping,1,False,2,16000,16000,171036412,shopping,38.87236684267602,14,WALK,7.3308794494701575
-1368291302,4171619,1810015,shopping,2,False,2,16000,16000,171036412,home,,15,WALK,7.3308794494701575
+1368291297,4171619,1810015,shopping,1,True,1,16000,16000,171036412,shopping,,13,WALK,7.330879449470157
+1368291301,4171619,1810015,shopping,1,False,2,16000,16000,171036412,shopping,38.87236684267602,14,WALK,7.330879449470157
+1368291302,4171619,1810015,shopping,2,False,2,16000,16000,171036412,home,,15,WALK,7.330879449470157
 1368291609,4171620,1810015,school,1,True,1,16000,16000,171036451,school,,7,WALK,6.71417537165923
 1368291613,4171620,1810015,school,1,False,1,16000,16000,171036451,home,,15,WALK,6.714175372080282
 1368292281,4171622,1810015,shopping,1,True,1,23000,16000,171036535,shopping,,9,WALK,1.3728419142672188
@@ -203,15 +203,15 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 1368292377,4171623,1810015,atwork,1,True,1,1000,24000,171036547,atwork,,10,WALK,-0.804377917423612
 1368292381,4171623,1810015,atwork,1,False,2,7000,1000,171036547,othmaint,33.332645871938475,10,WALK,-1.0994814321154591
 1368292382,4171623,1810015,atwork,2,False,2,24000,7000,171036547,work,,10,WALK,13.272266227205533
-1368292657,4171623,1810015,work,1,True,2,25000,16000,171036582,escort,29.668944086836447,8,WALK,9.029527074456235
-1368292658,4171623,1810015,work,2,True,2,24000,25000,171036582,work,,8,WALK,2.1089396574220873
+1368292657,4171623,1810015,work,1,True,2,25000,16000,171036582,escort,29.668944086836447,8,WALK,9.029527074456237
+1368292658,4171623,1810015,work,2,True,2,24000,25000,171036582,work,,8,WALK,2.1089396574220878
 1368292661,4171623,1810015,work,1,False,2,6000,24000,171036582,work,30.576087536065494,22,WALK,1.4313475247835998
 1368292662,4171623,1810015,work,2,False,2,16000,6000,171036582,home,,22,WALK,8.45354298496514
-1582205641,4823797,1952792,othmaint,1,True,1,13000,14000,197775705,othmaint,,9,WALK,-0.23926045274160404
-1582205645,4823797,1952792,othmaint,1,False,1,14000,13000,197775705,home,,10,WALK,-0.23926045274160404
+1582205641,4823797,1952792,othmaint,1,True,1,13000,14000,197775705,othmaint,,9,WALK,-0.239260452741604
+1582205645,4823797,1952792,othmaint,1,False,1,14000,13000,197775705,home,,10,WALK,-0.239260452741604
 1582205729,4823797,1952792,work,1,True,1,14000,14000,197775716,work,,11,WALK,0.7266921244277498
 1582205733,4823797,1952792,work,1,False,1,14000,14000,197775716,home,,18,WALK,0.7266921244277498
-1658748793,5057160,2048204,work,1,True,1,15000,5000,207343599,work,,7,WALK_LOC,1.3170017699096879
+1658748793,5057160,2048204,work,1,True,1,15000,5000,207343599,work,,7,WALK_LOC,1.317001769909688
 1658748797,5057160,2048204,work,1,False,1,5000,15000,207343599,home,,14,WALK_LOC,1.3015181390621686
 1658806913,5057338,2048382,eatout,1,True,1,9000,7000,207350864,eatout,,20,WALK,10.189133613409494
 1658806917,5057338,2048382,eatout,1,False,1,7000,9000,207350864,home,,20,WALK,10.345373617887216
@@ -228,7 +228,7 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 1767186577,5387763,2223027,work,1,True,2,7000,9000,220898322,escort,38.55185637940535,8,WALK,11.363681052923477
 1767186578,5387763,2223027,work,2,True,2,5000,7000,220898322,work,,8,WALK,4.031252242930563
 1767186581,5387763,2223027,work,1,False,2,8000,5000,220898322,othmaint,36.964562786529065,17,WALK,3.9594482660927697
-1767186582,5387763,2223027,work,2,False,2,9000,8000,220898322,home,,17,WALK,10.001230529962585
+1767186582,5387763,2223027,work,2,False,2,9000,8000,220898322,home,,17,WALK,10.001230529962584
 1767666161,5389226,2223759,atwork,1,True,1,13000,21000,220958270,atwork,,13,WALK,-0.8469767119587287
 1767666165,5389226,2223759,atwork,1,False,1,21000,13000,220958270,work,,13,WALK,-0.8469846953017646
 1767666233,5389226,2223759,eatout,1,True,1,16000,16000,220958279,eatout,,20,WALK,6.618624772185435
@@ -236,10 +236,10 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 1767666441,5389226,2223759,work,1,True,1,21000,16000,220958305,work,,9,WALK,2.520654632402534
 1767666445,5389226,2223759,work,1,False,1,16000,21000,220958305,home,,18,WALK,2.7406511441212484
 1767666769,5389227,2223759,work,1,True,1,23000,16000,220958346,work,,6,WALK,0.7526669094549486
-1767666773,5389227,2223759,work,1,False,1,16000,23000,220958346,home,,20,WALK,0.40072258181021503
-2396217433,7305540,2727273,work,1,True,1,1000,20000,299527179,work,,10,SHARED2FREE,0.17663861858229693
+1767666773,5389227,2223759,work,1,False,1,16000,23000,220958346,home,,20,WALK,0.400722581810215
+2396217433,7305540,2727273,work,1,True,1,1000,20000,299527179,work,,10,SHARED2FREE,0.1766386185822969
 2396217437,7305540,2727273,work,1,False,1,20000,1000,299527179,home,,17,SHARED2FREE,-0.4071724372157053
-2396217761,7305541,2727273,work,1,True,1,2000,20000,299527220,work,,6,WALK_LRF,0.37731213442716816
+2396217761,7305541,2727273,work,1,True,1,2000,20000,299527220,work,,6,WALK_LRF,0.3773121344271681
 2396217765,7305541,2727273,work,1,False,1,20000,2000,299527220,home,,17,WALK_LRF,0.4522229209355942
 2444719729,7453413,2762078,shopping,1,True,1,11000,20000,305589966,shopping,,16,WALK,4.72875300127406
 2444719733,7453413,2762078,shopping,1,False,1,20000,11000,305589966,home,,16,WALK,4.63947306542404
@@ -260,9 +260,9 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 2464406013,7513432,2822097,work,1,False,1,8000,9000,308050751,home,,15,BIKE,8.061419249304613
 2464446025,7513554,2822219,work,1,True,1,7000,8000,308055753,work,,5,WALK,10.948561445815672
 2464446029,7513554,2822219,work,1,False,1,8000,7000,308055753,home,,16,WALK,10.71976145528291
-2464449633,7513565,2822230,work,1,True,2,9000,8000,308056204,univ,29.551049635153966,9,WALK,7.9948426686587775
+2464449633,7513565,2822230,work,1,True,2,9000,8000,308056204,univ,29.55104963515397,9,WALK,7.9948426686587775
 2464449634,7513565,2822230,work,2,True,2,12000,9000,308056204,work,,9,WALK,2.6765203030859817
 2464449637,7513565,2822230,work,1,False,2,6000,12000,308056204,escort,33.34376957078302,12,WALK,3.1913129432158387
-2464449638,7513565,2822230,work,2,False,2,8000,6000,308056204,home,,21,WALK,9.386342851961201
+2464449638,7513565,2822230,work,2,False,2,8000,6000,308056204,home,,21,WALK,9.3863428519612
 2467713777,7523517,2832182,othdiscr,1,True,1,16000,7000,308464222,othdiscr,,8,WALK,6.612046694416055
 2467713781,7523517,2832182,othdiscr,1,False,1,7000,16000,308464222,home,,13,WALK_LOC,6.681639068176178
diff --git a/activitysim/examples/example_multiple_zone/test/regress/final_trips_3_zone.csv b/activitysim/examples/example_multiple_zone/test/regress/final_trips_3_zone.csv
index d04463662..ddfef6071 100644
--- a/activitysim/examples/example_multiple_zone/test/regress/final_trips_3_zone.csv
+++ b/activitysim/examples/example_multiple_zone/test/regress/final_trips_3_zone.csv
@@ -4,14 +4,14 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 36757193,112064,112064,othdiscr,1,True,1,12000,16000,4594649,othdiscr,,12,WALK,4.599564723581695,,,
 36757197,112064,112064,othdiscr,1,False,1,16000,12000,4594649,home,,14,WALK,4.599564716687014,,,
 36757257,112064,112064,shopping,1,True,1,11000,16000,4594657,shopping,,16,WALK,3.964291128688904,,,
-36757261,112064,112064,shopping,1,False,1,16000,11000,4594657,home,,17,WALK,3.9642911737175996,,,
+36757261,112064,112064,shopping,1,False,1,16000,11000,4594657,home,,17,WALK,3.9642911737176,,,
 195385257,595686,370497,school,1,True,1,8000,21000,24423157,school,,7,WALK,11.080195241803462,,,
 195385261,595686,370497,school,1,False,1,21000,8000,24423157,home,,16,WALK,11.036835230556166,,,
 211388201,644476,386761,escort,1,True,1,13000,16000,26423525,escort,,5,TNC_SHARED,-1.1876146394641565,,,
 211388205,644476,386761,escort,1,False,1,16000,13000,26423525,home,,6,WALK_TRANSIT,-0.7683292874254523,90016.0,90012.0,shortest
 211388329,644476,386761,othdiscr,1,True,1,16000,16000,26423541,othdiscr,,18,WALK,7.330879513166791,,,
 211388333,644476,386761,othdiscr,1,False,1,16000,16000,26423541,home,,18,WALK,7.330879513166791,,,
-211388353,644476,386761,othmaint,1,True,1,17000,16000,26423544,othmaint,,18,WALK,3.7063285513759268,,,
+211388353,644476,386761,othmaint,1,True,1,17000,16000,26423544,othmaint,,18,WALK,3.706328551375927,,,
 211388357,644476,386761,othmaint,1,False,1,16000,17000,26423544,home,,19,WALK,3.6962483059869946,,,
 211388441,644476,386761,work,1,True,1,12000,16000,26423555,work,,7,WALK,3.2969072197129083,,,
 211388445,644476,386761,work,1,False,1,16000,12000,26423555,home,,17,WALK,3.29690716940968,,,
@@ -20,103 +20,103 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 211389033,644478,386761,school,1,True,1,25000,16000,26423629,school,,8,BIKE,12.194765926599858,,,
 211389037,644478,386761,school,1,False,1,16000,25000,26423629,home,,16,BIKE,12.150807255895982,,,
 515832417,1572659,763879,shopping,1,True,4,7000,6000,64479052,othmaint,36.40832148098153,7,WALK,13.734545920861262,,,
-515832418,1572659,763879,shopping,2,True,4,7000,7000,64479052,escort,36.068441476486534,12,WALK,13.906967145498491,,,
+515832418,1572659,763879,shopping,2,True,4,7000,7000,64479052,escort,36.06844147648653,12,WALK,13.906967145498491,,,
 515832419,1572659,763879,shopping,3,True,4,7000,7000,64479052,shopping,34.83041114804465,17,WALK,13.906967145498491,,,
-515832420,1572659,763879,shopping,4,True,4,19000,7000,64479052,shopping,,17,SHARED2FREE,0.14611235046745477,,,
+515832420,1572659,763879,shopping,4,True,4,19000,7000,64479052,shopping,,17,SHARED2FREE,0.1461123504674547,,,
 515832421,1572659,763879,shopping,1,False,1,6000,19000,64479052,home,,20,SHARED3FREE,-0.5904843626610963,,,
 535620049,1632987,824207,work,1,True,1,17000,18000,66952506,work,,15,WALK,4.628394719363547,,,
 535620053,1632987,824207,work,1,False,1,18000,17000,66952506,home,,23,WALK,4.625280982482905,,,
 615236801,1875721,982875,work,1,True,1,4000,16000,76904600,work,,8,WALK,-0.3775561543634698,,,
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-615236866,1875722,982875,eatout,2,True,2,17000,7000,76904608,eatout,,13,WALK,3.9052660376990707,,,
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 615236869,1875722,982875,eatout,1,False,1,16000,17000,76904608,home,,16,WALK,5.892858627625031,,,
 708171009,2159057,1099626,work,1,True,1,21000,20000,88521376,work,,7,WALK,2.0808019898702543,,,
 708171013,2159057,1099626,work,1,False,4,7000,21000,88521376,shopping,28.898833214113047,18,WALK,1.765359539694954,,,
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 708171016,2159057,1099626,work,4,False,4,20000,7000,88521376,home,,18,WALK,8.964803895928217,,,
 708171273,2159058,1099626,univ,1,True,1,10000,20000,88521409,univ,,15,WALK,8.039212343802607,,,
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 806388157,2458502,1173905,shopping,1,False,1,8000,5000,100798519,home,,8,SHARED2FREE,0.1684460835975957,,,
 806388225,2458500,1173905,othmaint,1,True,1,9000,8000,100798528,othmaint,,12,WALK,6.622034247453799,,,
 806388229,2458500,1173905,othmaint,1,False,1,8000,9000,100798528,home,,20,WALK,6.622034247453799,,,
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 806388405,2458501,1173905,escort,1,False,1,8000,17000,100798550,home,,16,WALK,3.737863102378973,,,
 806388905,2458502,1173905,school,1,True,2,7000,8000,100798613,social,55.78907965405994,8,WALK,13.34853579117717,,,
-806388906,2458502,1173905,school,2,True,2,8000,7000,100798613,school,,8,WALK,11.526586427366201,,,
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 963286345,2936848,1286557,othdiscr,1,True,1,25000,11000,120410793,othdiscr,,15,WALK,12.064881587083146,,,
 963286349,2936848,1286557,othdiscr,1,False,1,11000,25000,120410793,home,,16,WALK,12.232281768298204,,,
 1004301497,3061894,1363467,shopping,1,True,1,5000,24000,125537687,shopping,,12,WALK,3.7130274821126257,,,
 1004301501,3061894,1363467,shopping,1,False,1,24000,5000,125537687,home,,13,SHARED3FREE,3.6933876094578046,,,
 1004301785,3061895,1363467,othmaint,1,True,1,4000,24000,125537723,othmaint,,15,DRIVEALONEFREE,0.6604943570038814,,,
-1004301789,3061895,1363467,othmaint,1,False,1,24000,4000,125537723,home,,18,WALK,0.44072321723820845,,,
-1004301873,3061895,1363467,work,1,True,1,2000,24000,125537734,work,,6,BIKE,0.01737658712885891,,,
-1004301877,3061895,1363467,work,1,False,1,24000,2000,125537734,home,,14,BIKE,0.004666558564732578,,,
+1004301789,3061895,1363467,othmaint,1,False,1,24000,4000,125537723,home,,18,WALK,0.4407232172382084,,,
+1004301873,3061895,1363467,work,1,True,1,2000,24000,125537734,work,,6,BIKE,0.0173765871288589,,,
+1004301877,3061895,1363467,work,1,False,1,24000,2000,125537734,home,,14,BIKE,0.0046665585647325,,,
 1368289969,4171615,1810015,univ,1,True,1,12000,16000,171036246,univ,,13,WALK,4.061179288088942,,,
 1368289973,4171615,1810015,univ,1,False,1,16000,12000,171036246,home,,13,WALK,4.06117926693834,,,
 1368290273,4171616,1810015,othmaint,1,True,1,16000,16000,171036284,othmaint,,9,WALK,4.598226175910151,,,
 1368290277,4171616,1810015,othmaint,1,False,1,16000,16000,171036284,home,,11,WALK,4.598226175910151,,,
 1368290689,4171617,1810015,work,1,True,2,8000,16000,171036336,social,24.27202534866615,9,WALK,7.896576327414681,,,
-1368290690,4171617,1810015,work,2,True,2,14000,8000,171036336,work,,12,WALK,-0.32042542069485463,,,
-1368290693,4171617,1810015,work,1,False,1,16000,14000,171036336,home,,18,WALK,0.49247462099988193,,,
-1368291297,4171619,1810015,shopping,1,True,1,16000,16000,171036412,shopping,,13,WALK,7.3308794494701575,,,
-1368291301,4171619,1810015,shopping,1,False,2,16000,16000,171036412,shopping,38.872404599185785,14,WALK,7.3308794494701575,,,
-1368291302,4171619,1810015,shopping,2,False,2,16000,16000,171036412,home,,15,WALK,7.3308794494701575,,,
+1368290690,4171617,1810015,work,2,True,2,14000,8000,171036336,work,,12,WALK,-0.3204254206948546,,,
+1368290693,4171617,1810015,work,1,False,1,16000,14000,171036336,home,,18,WALK,0.4924746209998819,,,
+1368291297,4171619,1810015,shopping,1,True,1,16000,16000,171036412,shopping,,13,WALK,7.330879449470157,,,
+1368291301,4171619,1810015,shopping,1,False,2,16000,16000,171036412,shopping,38.872404599185785,14,WALK,7.330879449470157,,,
+1368291302,4171619,1810015,shopping,2,False,2,16000,16000,171036412,home,,15,WALK,7.330879449470157,,,
 1368291609,4171620,1810015,school,1,True,1,16000,16000,171036451,school,,7,WALK,6.71417537165923,,,
 1368291613,4171620,1810015,school,1,False,1,16000,16000,171036451,home,,15,WALK,6.714175372080282,,,
 1368292281,4171622,1810015,shopping,1,True,1,23000,16000,171036535,shopping,,9,TNC_SINGLE,-1.940742218542811,,,
 1368292285,4171622,1810015,shopping,1,False,1,16000,23000,171036535,home,,15,WALK_TRANSIT,0.8849710286454233,90016.0,90014.0,shortest
 1368292377,4171623,1810015,atwork,1,True,1,1000,24000,171036547,atwork,,10,WALK,-0.7715288559756663,,,
-1368292381,4171623,1810015,atwork,1,False,2,7000,1000,171036547,othmaint,33.333383755513104,10,WALK,-1.0979780611969903,,,
+1368292381,4171623,1810015,atwork,1,False,2,7000,1000,171036547,othmaint,33.333383755513104,10,WALK,-1.0979780611969905,,,
 1368292382,4171623,1810015,atwork,2,False,2,24000,7000,171036547,work,,10,WALK,13.272266227205533,,,
-1368292657,4171623,1810015,work,1,True,2,25000,16000,171036582,escort,29.66682818863834,8,WALK,9.029527074456235,,,
+1368292657,4171623,1810015,work,1,True,2,25000,16000,171036582,escort,29.66682818863834,8,WALK,9.029527074456237,,,
 1368292658,4171623,1810015,work,2,True,2,24000,25000,171036582,work,,8,WALK,2.100139875317927,,,
 1368292661,4171623,1810015,work,1,False,2,6000,24000,171036582,work,30.57845053157008,22,WALK,1.4313475247835998,,,
 1368292662,4171623,1810015,work,2,False,2,16000,6000,171036582,home,,22,WALK,8.45354298496514,,,
-1582205641,4823797,1952792,othmaint,1,True,1,13000,14000,197775705,othmaint,,9,WALK,-0.23926045274160404,,,
-1582205645,4823797,1952792,othmaint,1,False,1,14000,13000,197775705,home,,10,WALK,-0.23926045274160404,,,
+1582205641,4823797,1952792,othmaint,1,True,1,13000,14000,197775705,othmaint,,9,WALK,-0.239260452741604,,,
+1582205645,4823797,1952792,othmaint,1,False,1,14000,13000,197775705,home,,10,WALK,-0.239260452741604,,,
 1582205729,4823797,1952792,work,1,True,1,14000,14000,197775716,work,,11,WALK,0.7266921244277498,,,
 1582205733,4823797,1952792,work,1,False,1,14000,14000,197775716,home,,18,WALK,0.7266921244277498,,,
 1767186249,5387762,2223027,work,1,True,1,23000,9000,220898281,work,,7,TNC_SINGLE,-0.4139608727894769,,,
-1767186253,5387762,2223027,work,1,False,1,9000,23000,220898281,home,,17,TNC_SINGLE,-0.44333544644494455,,,
+1767186253,5387762,2223027,work,1,False,1,9000,23000,220898281,home,,17,TNC_SINGLE,-0.4433354464449445,,,
 1767186577,5387763,2223027,work,1,True,1,5000,9000,220898322,work,,8,WALK,2.744924666835035,,,
 1767186581,5387763,2223027,work,1,False,4,8000,5000,220898322,othmaint,34.17929500173492,16,WALK,3.1849202269264563,,,
-1767186582,5387763,2223027,work,2,False,4,7000,8000,220898322,eatout,46.64761595302997,17,WALK,9.302464236178993,,,
-1767186583,5387763,2223027,work,3,False,4,7000,7000,220898322,escort,48.67457288689701,17,WALK,11.036561449169515,,,
-1767186584,5387763,2223027,work,4,False,4,9000,7000,220898322,home,,17,WALK,10.446257354558641,,,
-1767666161,5389226,2223759,atwork,1,True,1,13000,21000,220958270,atwork,,13,WALK,-0.8469767119587291,,,
-1767666165,5389226,2223759,atwork,1,False,1,21000,13000,220958270,work,,13,WALK,-0.8469846953017649,,,
+1767186582,5387763,2223027,work,2,False,4,7000,8000,220898322,eatout,46.64761595302997,17,WALK,9.302464236178992,,,
+1767186583,5387763,2223027,work,3,False,4,7000,7000,220898322,escort,48.67457288689701,17,WALK,11.036561449169517,,,
+1767186584,5387763,2223027,work,4,False,4,9000,7000,220898322,home,,17,WALK,10.44625735455864,,,
+1767666161,5389226,2223759,atwork,1,True,1,13000,21000,220958270,atwork,,13,WALK,-0.8469767119587287,,,
+1767666165,5389226,2223759,atwork,1,False,1,21000,13000,220958270,work,,13,WALK,-0.8469846953017646,,,
 1767666233,5389226,2223759,eatout,1,True,1,16000,16000,220958279,eatout,,21,WALK,6.618624772185435,,,
 1767666237,5389226,2223759,eatout,1,False,1,16000,16000,220958279,home,,21,WALK,6.618624772185435,,,
 1767666441,5389226,2223759,work,1,True,1,21000,16000,220958305,work,,9,WALK,2.906524628265906,,,
 1767666445,5389226,2223759,work,1,False,2,6000,21000,220958305,shopping,30.066410398011204,17,WALK,3.4789233361104035,,,
 1767666446,5389226,2223759,work,2,False,2,16000,6000,220958305,home,,18,WALK,8.739519226829522,,,
 1767666769,5389227,2223759,work,1,True,1,23000,16000,220958346,work,,6,WALK,1.2012359354121191,,,
-1767666773,5389227,2223759,work,1,False,2,25000,23000,220958346,shopping,29.351341238160156,13,WALK,2.305499981110482,,,
+1767666773,5389227,2223759,work,1,False,2,25000,23000,220958346,shopping,29.35134123816016,13,WALK,2.305499981110482,,,
 1767666774,5389227,2223759,work,2,False,2,16000,25000,220958346,home,,21,WALK,9.513365015972848,,,
-2396217433,7305540,2727273,work,1,True,1,1000,20000,299527179,work,,10,DRIVEALONEFREE,0.17663861858229693,,,
+2396217433,7305540,2727273,work,1,True,1,1000,20000,299527179,work,,10,DRIVEALONEFREE,0.1766386185822969,,,
 2396217437,7305540,2727273,work,1,False,1,20000,1000,299527179,home,,19,DRIVEALONEFREE,-0.5570738654464363,,,
 2396217761,7305541,2727273,work,1,True,1,5000,20000,299527220,work,,6,WALK,2.21697661171345,,,
 2396217765,7305541,2727273,work,1,False,1,20000,5000,299527220,home,,18,WALK,2.1289822455493645,,,
-2444719729,7453413,2762078,shopping,1,True,1,13000,20000,305589966,shopping,,16,SHARED2FREE,0.19082308611408758,,,
-2444719733,7453413,2762078,shopping,1,False,1,20000,13000,305589966,home,,16,SHARED2FREE,0.15835153702639948,,,
+2444719729,7453413,2762078,shopping,1,True,1,13000,20000,305589966,shopping,,16,SHARED2FREE,0.1908230861140875,,,
+2444719733,7453413,2762078,shopping,1,False,1,20000,13000,305589966,home,,16,SHARED2FREE,0.1583515370263994,,,
 2464104641,7512514,2821179,eatout,1,True,1,19000,8000,308013080,eatout,,8,WALK,-1.7812103759630349,,,
 2464104645,7512514,2821179,eatout,1,False,1,8000,19000,308013080,home,,16,WALK,-1.474310526482455,,,
 2464104857,7512514,2821179,shopping,1,True,1,6000,8000,308013107,shopping,,17,WALK,12.522299462021278,,,
@@ -127,6 +127,6 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 2464449634,7513565,2822230,work,2,True,2,12000,9000,308056204,work,,9,WALK,3.0831344184199936,,,
 2464449637,7513565,2822230,work,1,False,3,6000,12000,308056204,escort,36.01475569138399,12,WALK_TRANSIT,5.825660206518803,90005.0,90012.0,shortest
 2464449638,7513565,2822230,work,2,False,3,6000,6000,308056204,eatout,46.45753059535832,21,WALK,10.192910221586306,,,
-2464449639,7513565,2822230,work,3,False,3,8000,6000,308056204,home,,21,WALK,9.805039232241185,,,
+2464449639,7513565,2822230,work,3,False,3,8000,6000,308056204,home,,21,WALK,9.805039232241183,,,
 2467713777,7523517,2832182,othdiscr,1,True,1,16000,7000,308464222,othdiscr,,8,WALK,5.511799505181132,,,
 2467713781,7523517,2832182,othdiscr,1,False,1,7000,16000,308464222,home,,13,WALK,5.790799498423691,,,
diff --git a/activitysim/examples/example_multiple_zone/test/test_multiple_zone.py b/activitysim/examples/example_multiple_zone/test/test_multiple_zone.py
index 6f7aeef36..ec400c3fd 100644
--- a/activitysim/examples/example_multiple_zone/test/test_multiple_zone.py
+++ b/activitysim/examples/example_multiple_zone/test/test_multiple_zone.py
@@ -48,12 +48,14 @@ def regress(zone):
         # regress tours
         regress_tours_df = pd.read_csv(test_path(f'regress/final_tours_{zone}_zone.csv'))
         tours_df = pd.read_csv(test_path('output/final_tours.csv'))
+        tours_df.to_csv(test_path(f'regress/final_tours_{zone}_zone_last_run.csv'), index=False)
         print(f"regress tours")
         pdt.assert_frame_equal(tours_df, regress_tours_df, rtol=1e-03)
 
         # regress trips
         regress_trips_df = pd.read_csv(test_path(f'regress/final_trips_{zone}_zone.csv'))
         trips_df = pd.read_csv(test_path('output/final_trips.csv'))
+        trips_df.to_csv(test_path(f'regress/final_trips_{zone}_zone_last_run.csv'), index=False)
         print(f"regress trips")
         pdt.assert_frame_equal(trips_df, regress_trips_df, rtol=1e-03)
 
diff --git a/activitysim/examples/example_psrc/configs/accessibility.csv b/activitysim/examples/example_psrc/configs/accessibility.csv
index adeb3a0c0..c40a672b1 100755
--- a/activitysim/examples/example_psrc/configs/accessibility.csv
+++ b/activitysim/examples/example_psrc/configs/accessibility.csv
@@ -21,12 +21,12 @@ auto off-peak total,auOpTotal,df.TOTEMP * _decay
 #,, assume peak outbound transit occurs in AM
 o-d peak transit ivt,_inVehicleTime,"skim_od[('WLK_TRN_WLK_IVT', 'AM')]"
 o-d peak transit ovt,_outOfVehicleTime,"skim_od[('WLK_TRN_WLK_IWAIT', 'AM')] + skim_od[('WLK_TRN_WLK_XWAIT', 'AM')] + skim_od[('WLK_TRN_WLK_WACC', 'AM')] + skim_od[('WLK_TRN_WLK_WAUX', 'AM')] + skim_od[('WLK_TRN_WLK_WEGR', 'AM')]"
-o-d peak transit time,_trPkTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
+o-d peak transit time,_trPkTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
 #,, assume peak inbound transit occurs in PM
 d-o peak transit ivt,_inVehicleTime,"skim_do[('WLK_TRN_WLK_IVT', 'PM')]"
 d-o peak transit ovt,_outOfVehicleTime,"skim_do[('WLK_TRN_WLK_IWAIT', 'PM')] + skim_do[('WLK_TRN_WLK_XWAIT', 'PM')] + skim_do[('WLK_TRN_WLK_WACC', 'PM')] + skim_do[('WLK_TRN_WLK_WAUX', 'PM')] + skim_do[('WLK_TRN_WLK_WEGR', 'PM')]"
-d-o peak transit time,_trPkTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
-peak transit time,_trPkTime,_trPkTime_od + _trPkTime_do
+d-o peak transit time,_trPkTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
+peak transit time,_trPkTime,(_trPkTime_od + _trPkTime_do).clip(0)
 round trip path is available,_rt_available,(_trPkTime_od > 0) & (_trPkTime_do > 0)
 decay function,_decay,_rt_available * exp(_trPkTime * dispersion_parameter_transit)
 transit peak retail,trPkRetail,df.RETEMPN * _decay
@@ -37,12 +37,12 @@ transit peak total,trPkTotal,df.TOTEMP * _decay
 #,, assume off-peak outbound transit occurs in the MD time period
 o-d off-peak transit ivt,_inVehicleTime,"skim_od[('WLK_TRN_WLK_IVT', 'MD')]"
 o-d off-peak transit ovt,_outOfVehicleTime,"skim_od[('WLK_TRN_WLK_IWAIT', 'MD')] + skim_od[('WLK_TRN_WLK_XWAIT', 'MD')] + skim_od[('WLK_TRN_WLK_WACC', 'MD')] + skim_od[('WLK_TRN_WLK_WAUX', 'MD')] + skim_od[('WLK_TRN_WLK_WEGR', 'MD')]"
-o-d off-peak transit time,_trOpTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
+o-d off-peak transit time,_trOpTime_od,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
 #,, assume off-peak inbound transit occurs in the MD time period
 d-o off-peak transit ivt,_inVehicleTime,"skim_do[('WLK_TRN_WLK_IVT', 'MD')]"
 d-o off-peak transit ovt,_outOfVehicleTime,"skim_do[('WLK_TRN_WLK_IWAIT', 'MD')] + skim_do[('WLK_TRN_WLK_XWAIT', 'MD')] + skim_do[('WLK_TRN_WLK_WACC', 'MD')] + skim_do[('WLK_TRN_WLK_WAUX', 'MD')] + skim_do[('WLK_TRN_WLK_WEGR', 'MD')]"
-d-o off-peak transit time,_trOpTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / 100.0
-peak transit time,_trOpTime,_trOpTime_od + _trOpTime_do
+d-o off-peak transit time,_trOpTime_do,(_inVehicleTime + out_of_vehicle_time_weight * _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
+peak transit time,_trOpTime,(_trOpTime_od + _trOpTime_do).clip(0)
 #,,FIXME - _rt_available calculation appears to be wrong in mtctm1 accessibility.job
 #round trip path is available,_rt_available,(_trOpTime > 0)
 round trip path is available,_rt_available,(_trOpTime_od > 0) & (_trOpTime_do > 0)
diff --git a/activitysim/examples/example_psrc/configs/annotate_persons_workplace.csv b/activitysim/examples/example_psrc/configs/annotate_persons_workplace.csv
index b382ed07d..f215886a5 100755
--- a/activitysim/examples/example_psrc/configs/annotate_persons_workplace.csv
+++ b/activitysim/examples/example_psrc/configs/annotate_persons_workplace.csv
@@ -16,14 +16,14 @@ work_zone_area_type,work_zone_area_type,"reindex(land_use.area_type, persons.wor
 ,_work_walk_available,(_walk_time_home_to_work > 0) & (_walk_time_work_to_home > 0)
 ,_roundtrip_walk_time_to_work,"np.where(_work_walk_available, _walk_time_home_to_work + _walk_time_work_to_home, _MAX_TIME_TO_WORK)"
 #,,_roundtrip_transit_time_to_work
-,_transit_ivt_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))/100"
-,_transit_ivt_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))/100"
+,_transit_ivt_home_to_work,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_ivt_work_to_home,"skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_IVT', 'MD'))/TRANSIT_SCALE_FACTOR"
 ,_work_transit_available,(_transit_ivt_home_to_work > 0) & (_transit_ivt_work_to_home > 0)
-,_transit_iwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_IWAIT', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_IWAIT', 'MD'))/100"
-,_transit_xwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_XWAIT', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_XWAIT', 'MD'))/100"
-,_transit_waux,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WAUX', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WAUX', 'MD'))/100"
-,_transit_wacc,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WACC', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WACC', 'MD'))/100"
-,_transit_wegr,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WEGR', 'MD'))/100 + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WEGR', 'MD'))/100"
+,_transit_iwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_IWAIT', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_IWAIT', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_xwait,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_XWAIT', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_XWAIT', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_waux,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WAUX', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WAUX', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_wacc,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WACC', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WACC', 'MD'))/TRANSIT_SCALE_FACTOR"
+,_transit_wegr,"skim_dict.lookup(persons.home_zone_id, persons.workplace_zone_id, ('WLK_TRN_WLK_WEGR', 'MD'))/TRANSIT_SCALE_FACTOR + skim_dict.lookup(persons.workplace_zone_id, persons.home_zone_id, ('WLK_TRN_WLK_WEGR', 'MD'))/TRANSIT_SCALE_FACTOR"
 ,_roundtrip_transit_time_to_work,_transit_ivt_home_to_work + _transit_ivt_work_to_home + _transit_iwait + _transit_xwait + _transit_waux + _transit_wacc + _transit_wegr
 #,,work_auto_savings_ratio
 ,_min_work_walk_transit,"np.where(_work_transit_available, np.minimum(_roundtrip_transit_time_to_work, _roundtrip_walk_time_to_work), _roundtrip_walk_time_to_work)"
diff --git a/activitysim/examples/example_psrc/configs/constants.yaml b/activitysim/examples/example_psrc/configs/constants.yaml
index 68313e53d..b2896e464 100755
--- a/activitysim/examples/example_psrc/configs/constants.yaml
+++ b/activitysim/examples/example_psrc/configs/constants.yaml
@@ -61,3 +61,8 @@ PTYPE_NAME:
 CDAP_ACTIVITY_MANDATORY: M
 CDAP_ACTIVITY_NONMANDATORY: N
 CDAP_ACTIVITY_HOME: H
+
+# Correction for transit skim expressions
+# e.g. MTC transit skims (Cube TRANPLAN skims) use scaled ints and
+# therefore need to be divided by the scale factor if used in expressions
+TRANSIT_SCALE_FACTOR: 100
diff --git a/activitysim/examples/example_psrc/configs/tour_mode_choice.csv b/activitysim/examples/example_psrc/configs/tour_mode_choice.csv
index fe63e28b4..e1b04fbcd 100755
--- a/activitysim/examples/example_psrc/configs/tour_mode_choice.csv
+++ b/activitysim/examples/example_psrc/configs/tour_mode_choice.csv
@@ -70,89 +70,89 @@ util_SHARED3PAY_Two_person_household,SHARED3PAY - Two person household,@(df.hhsi
 util_SHARED3PAY_Person_is_16_years_old_or_older,SHARED3PAY - Person is 16 years old or older,@(df.age >= 16),,,,,,coef_age16p_sr_multiplier,,,,,,,,,,,,,,,
 #,Walk,,,,,,,,,,,,,,,,,,,,,,
 #,FIXME - skims aren't symmetrical,so we have to make sure they can get back,,,,,,,,,,,,,,,,,,,,,
-util_WALK_Time_up_to_2_miles,WALK - Time up to 2 miles,@walktimeshort_multiplier * (df.distance_walk_od.clip(upper=walkThresh) + df.distance_walk_od.clip(upper=walkThresh))*60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
-util_WALK_Time_beyond_2_of_a_miles,WALK - Time beyond 2 of a miles,@walktimelong_multiplier * ((df.distance_walk_od - walkThresh).clip(lower=0) + (df.distance_walk_od - walkThresh).clip(lower=0))*60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
+util_WALK_Time_up_to_2_miles,WALK - Time up to 2 miles,@walktimeshort_multiplier * (od_skims['DISTWALK'].clip(upper=walkThresh) + od_skims.reverse('DISTWALK').clip(upper=walkThresh))*60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
+util_WALK_Time_beyond_2_of_a_miles,WALK - Time beyond 2 of a miles,@walktimelong_multiplier * ((od_skims['DISTWALK'] - walkThresh).clip(lower=0) + (od_skims.reverse('DISTWALK') - walkThresh).clip(lower=0))*60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
 util_WALK_Destination_zone_densityIndex,WALK - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,coef_ivt,,,,,,,,,,,,,,
 util_WALK_Topology,WALK - Topology,@coef_topology_walk_multiplier * df.dest_topology,,,,,,,coef_ivt,,,,,,,,,,,,,,
 #,Bike,,,,,,,,,,,,,,,,,,,,,,
 #,FIXME - skims aren't symmetrical,so we have to make sure they can get back,,,,,,,,,,,,,,,,,,,,,
 util_BIKE_Unavailable_if_didn't_bike_to_work,BIKE - Unavailable if didn't bike to work,is_atwork_subtour & ~work_tour_is_bike,,,,,,,,-999,,,,,,,,,,,,,
-util_BIKE_Time_up_to_6_miles,BIKE - Time up to 6 miles,@biketimeshort_multiplier * (df.distance_bike_od.clip(upper=bikeThresh) + df.distance_bike_od.clip(upper=bikeThresh))*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
-util_BIKE_Time_beyond_6_of_a_miles,BIKE - Time beyond 6 of a miles,@biketimelong_multiplier * ((df.distance_bike_od-bikeThresh).clip(lower=0) + (df.distance_bike_od-bikeThresh).clip(lower=0))*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
+util_BIKE_Time_up_to_6_miles,BIKE - Time up to 6 miles,@biketimeshort_multiplier * (od_skims['DISTBIKE'].clip(upper=bikeThresh) + od_skims.reverse('DISTBIKE').clip(upper=bikeThresh))*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
+util_BIKE_Time_beyond_6_of_a_miles,BIKE - Time beyond 6 of a miles,@biketimelong_multiplier * ((od_skims['DISTBIKE']-bikeThresh).clip(lower=0) + (od_skims.reverse('DISTBIKE')-bikeThresh).clip(lower=0))*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
 util_BIKE_Destination_zone_densityIndex,BIKE - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,coef_ivt,,,,,,,,,,,,,
 util_BIKE_Topology,BIKE - Topology,@coef_topology_bike_multiplier * df.dest_topology,,,,,,,,coef_ivt,,,,,,,,,,,,,
 #,Walk to Local,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_LOC_Unavailable,WALK_LOC - Unavailable,walk_local_available == False,,,,,,,,,-999,,,,,,,,,,,,
-util_WALK_LOC_In_vehicle_time,WALK_LOC - In-vehicle time,@(odt_skims['WLK_LOC_WLK_TOTIVT']/100 + dot_skims['WLK_LOC_WLK_TOTIVT']/100),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Short_iwait_time,WALK_LOC - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_LOC_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_LOC_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Long_iwait_time,WALK_LOC - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_LOC_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_LOC_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_transfer_wait_time,WALK_LOC - transfer wait time,@xwait_multiplier * (odt_skims['WLK_LOC_WLK_XWAIT']/100 + dot_skims['WLK_LOC_WLK_XWAIT']/100),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_In_vehicle_time,WALK_LOC - In-vehicle time,@(odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Short_iwait_time,WALK_LOC - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Long_iwait_time,WALK_LOC - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_transfer_wait_time,WALK_LOC - transfer wait time,@xwait_multiplier * (odt_skims['WLK_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_number_of_transfers,WALK_LOC - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_LOC_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_LOC_WLK_BOARDS']-1).clip(0)),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Walk_access_time,WALK_LOC - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Walk_egress_time,WALK_LOC - Walk egress time,@2 * wegr_multiplier * df.destination_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Walk_other_time,WALK_LOC - Walk other time,@waux_multiplier * (odt_skims['WLK_LOC_WLK_WAUX']/100 + dot_skims['WLK_LOC_WLK_WAUX']/100),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Walk_other_time,WALK_LOC - Walk other time,@waux_multiplier * (odt_skims['WLK_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Fare,WALK_LOC - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LOC_WLK_FAR'] + dot_skims['WLK_LOC_WLK_FAR']),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Destination_zone_densityIndex,WALK_LOC - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Topology,WALK_LOC - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Person_is_less_than_10_years_old,WALK_LOC - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,coef_age010_trn_multiplier,,,,,,,,,,,,
 #,Walk to Light rail/Ferry,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_LRF_Unavailable,WALK_LRF - Unavailable,walk_lrf_available == False,,,,,,,,,,-999,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time,WALK_LRF - In-vehicle time,@(odt_skims['WLK_LRF_WLK_TOTIVT']/100 + dot_skims['WLK_LRF_WLK_TOTIVT']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time,WALK_LRF - In-vehicle time,@(odt_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
 #, FIXME coefficients below are wrong or needlessly complex? could be re-expressed to avoid subtract?,,,,,,,,,,,,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time_on_Light_Rail,WALK_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(ivt_lrt_multiplier-1)*(odt_skims['WLK_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_WLK_KEYIVT']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time_on_Ferry,WALK_LRF - In-vehicle time on Ferry (incremental w/keyivt),@(ivt_ferry_multiplier-ivt_lrt_multiplier)*(odt_skims['WLK_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Short_iwait_time,WALK_LRF - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_LRF_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_LRF_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Long_iwait_time,WALK_LRF - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_LRF_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_LRF_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_transfer_wait_time,WALK_LRF - transfer wait time,@xwait_multiplier * (odt_skims['WLK_LRF_WLK_XWAIT']/100 + dot_skims['WLK_LRF_WLK_XWAIT']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time_on_Light_Rail,WALK_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(ivt_lrt_multiplier-1)*(odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time_on_Ferry,WALK_LRF - In-vehicle time on Ferry (incremental w/keyivt),@(ivt_ferry_multiplier-ivt_lrt_multiplier)*(odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Short_iwait_time,WALK_LRF - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Long_iwait_time,WALK_LRF - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_transfer_wait_time,WALK_LRF - transfer wait time,@xwait_multiplier * (odt_skims['WLK_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_number_of_transfers,WALK_LRF - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_LRF_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_LRF_WLK_BOARDS']-1).clip(0)),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Walk_access_time,WALK_LRF - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Walk_egress_time,WALK_LRF - Walk egress time,@2 * wegr_multiplier * df.destination_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Walk_other_time,WALK_LRF - Walk other time,@waux_multiplier * (odt_skims['WLK_LRF_WLK_WAUX']/100 + dot_skims['WLK_LRF_WLK_WAUX']/100),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Walk_other_time,WALK_LRF - Walk other time,@waux_multiplier * (odt_skims['WLK_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Fare,WALK_LRF - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LRF_WLK_FAR'] + dot_skims['WLK_LRF_WLK_FAR']),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Destination_zone_densityIndex,WALK_LRF - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Topology,WALK_LRF - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Person_is_less_than_10_years_old,WALK_LRF - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,coef_age010_trn_multiplier,,,,,,,,,,,
 #,Walk to Express bus,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_EXP_Unavailable,WALK_EXP - Unavailable,walk_express_available == False,,,,,,,,,,,-999,,,,,,,,,,
-util_WALK_EXP_In_vehicle_time,WALK_EXP - In-vehicle time,@(odt_skims['WLK_EXP_WLK_TOTIVT']/100 + dot_skims['WLK_EXP_WLK_TOTIVT']/100),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_In_vehicle_time_on_Express_bus,WALK_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier - 1)*(odt_skims['WLK_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_WLK_KEYIVT']/100),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Short_iwait_time,WALK_EXP - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_EXP_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_EXP_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Long_iwait_time,WALK_EXP - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_EXP_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_EXP_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_transfer_wait_time,WALK_EXP - transfer wait time,@xwait_multiplier * (odt_skims['WLK_EXP_WLK_XWAIT']/100 + dot_skims['WLK_EXP_WLK_XWAIT']/100),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_In_vehicle_time,WALK_EXP - In-vehicle time,@(odt_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_In_vehicle_time_on_Express_bus,WALK_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier - 1)*(odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Short_iwait_time,WALK_EXP - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Long_iwait_time,WALK_EXP - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_transfer_wait_time,WALK_EXP - transfer wait time,@xwait_multiplier * (odt_skims['WLK_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_number_of_transfers,WALK_EXP - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_EXP_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_EXP_WLK_BOARDS']-1).clip(0)),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Walk_access_time,WALK_EXP - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Walk_egress_time,WALK_EXP - Walk egress time,@2 * wegr_multiplier * df.destination_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Walk_other_time,WALK_EXP - Walk other time,@waux_multiplier * (odt_skims['WLK_EXP_WLK_WAUX']/100 + dot_skims['WLK_EXP_WLK_WAUX']/100),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Walk_other_time,WALK_EXP - Walk other time,@waux_multiplier * (odt_skims['WLK_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Fare,WALK_EXP - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_EXP_WLK_FAR'] + dot_skims['WLK_EXP_WLK_FAR']),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Destination_zone_densityIndex,WALK_EXP - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Topology,WALK_EXP - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Person_is_less_than_10_years_old,WALK_EXP - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,,coef_age010_trn_multiplier,,,,,,,,,,
 #,Walk to Heavy Rail,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_HVY_Unavailable,WALK_HVY - Unavailable,walk_heavyrail_available == False,,,,,,,,,,,,-999,,,,,,,,,
-util_WALK_HVY_In_vehicle_time,WALK_HVY - In-vehicle time,@(odt_skims['WLK_HVY_WLK_TOTIVT']/100 + dot_skims['WLK_HVY_WLK_TOTIVT']/100),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_In_vehicle_time_on_heavy_rail,WALK_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * (odt_skims['WLK_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_WLK_KEYIVT']/100),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Short_iwait_time,WALK_HVY - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_HVY_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_HVY_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Long_iwait_time,WALK_HVY - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_HVY_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_HVY_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_transfer_wait_time,WALK_HVY - transfer wait time,@xwait_multiplier * (odt_skims['WLK_HVY_WLK_XWAIT']/100 + dot_skims['WLK_HVY_WLK_XWAIT']/100),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_In_vehicle_time,WALK_HVY - In-vehicle time,@(odt_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_In_vehicle_time_on_heavy_rail,WALK_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * (odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Short_iwait_time,WALK_HVY - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Long_iwait_time,WALK_HVY - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_transfer_wait_time,WALK_HVY - transfer wait time,@xwait_multiplier * (odt_skims['WLK_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_number_of_transfers,WALK_HVY - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_HVY_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_HVY_WLK_BOARDS']-1).clip(0)),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Walk_access_time,WALK_HVY - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Walk_egress_time,WALK_HVY - Walk egress time,@wegr_multiplier * 2 *df.destination_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Walk_other_time,WALK_HVY - Walk other time,@waux_multiplier * (odt_skims['WLK_HVY_WLK_WAUX']/100 + dot_skims['WLK_HVY_WLK_WAUX']/100),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Walk_other_time,WALK_HVY - Walk other time,@waux_multiplier * (odt_skims['WLK_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Fare,WALK_HVY - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_HVY_WLK_FAR'] + dot_skims['WLK_HVY_WLK_FAR']),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Destination_zone_densityIndex,WALK_HVY - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Topology,WALK_HVY - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Person_is_less_than_10_years_old,WALK_HVY - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,,,coef_age010_trn_multiplier,,,,,,,,,
 #,Walk to Commuter rail,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_COM_Unavailable,WALK_COM - Unavailable,walk_commuter_available == False,,,,,,,,,,,,,-999,,,,,,,,
-util_WALK_COM_In_vehicle_time,WALK_COM - In-vehicle time,@(odt_skims['WLK_COM_WLK_TOTIVT']/100 + dot_skims['WLK_COM_WLK_TOTIVT']/100),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_In_vehicle_time_on_commuter_rail,WALK_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * (odt_skims['WLK_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_WLK_KEYIVT']/100),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Short_iwait_time,WALK_COM - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_COM_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_COM_WLK_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Long_iwait_time,WALK_COM - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_COM_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_COM_WLK_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_transfer_wait_time,WALK_COM - transfer wait time,@xwait_multiplier * (odt_skims['WLK_COM_WLK_XWAIT']/100 + dot_skims['WLK_COM_WLK_XWAIT']/100),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_In_vehicle_time,WALK_COM - In-vehicle time,@(odt_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_In_vehicle_time_on_commuter_rail,WALK_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * (odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Short_iwait_time,WALK_COM - Short iwait time,@short_i_wait_multiplier * ((odt_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Long_iwait_time,WALK_COM - Long iwait time,@long_i_wait_multiplier * ((odt_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_transfer_wait_time,WALK_COM - transfer wait time,@xwait_multiplier * (odt_skims['WLK_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_number_of_transfers,WALK_COM - number of transfers,@xfers_wlk_multiplier * ((odt_skims['WLK_COM_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_COM_WLK_BOARDS']-1).clip(0)),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Walk_access_time,WALK_COM - Walk access time,@2 * wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Walk_egress_time,WALK_COM - Walk egress time,@2 * wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Walk_other_time,WALK_COM - Walk other time,@waux_multiplier * (odt_skims['WLK_COM_WLK_WAUX']/100 + dot_skims['WLK_COM_WLK_WAUX']/100),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Walk_other_time,WALK_COM - Walk other time,@waux_multiplier * (odt_skims['WLK_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Fare,WALK_COM - Fare,@ivt_cost_multiplier * df.ivot * (odt_skims['WLK_COM_WLK_FAR'] + dot_skims['WLK_COM_WLK_FAR']),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Destination_zone_densityIndex,WALK_COM - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Topology,WALK_COM - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,coef_ivt,,,,,,,,
@@ -161,17 +161,17 @@ util_WALK_COM_Person_is_less_than_10_years_old,WALK_COM - Person is less than 10
 util_DRIVE_LOC_Unavailable,DRIVE_LOC - Unavailable,drive_local_available == False,,,,,,,,,,,,,,-999,,,,,,,
 util_DRIVE_LOC_Unavailable_for_zero_auto_households,DRIVE_LOC - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,-999,,,,,,,
 util_DRIVE_LOC_Unavailable_for_persons_less_than_16,DRIVE_LOC - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,-999,,,,,,,
-util_DRIVE_LOC_In_vehicle_time,DRIVE_LOC - In-vehicle time,@(odt_skims['DRV_LOC_WLK_TOTIVT']/100 + dot_skims['WLK_LOC_DRV_TOTIVT']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Short_iwait_time,DRIVE_LOC - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_LOC_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_LOC_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Long_iwait_time,DRIVE_LOC - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_LOC_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_LOC_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_transfer_wait_time,DRIVE_LOC - transfer wait time,@xwait_multiplier * (odt_skims['DRV_LOC_WLK_XWAIT']/100 + dot_skims['WLK_LOC_DRV_XWAIT']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_In_vehicle_time,DRIVE_LOC - In-vehicle time,@(odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Short_iwait_time,DRIVE_LOC - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_LOC_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Long_iwait_time,DRIVE_LOC - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_LOC_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_transfer_wait_time,DRIVE_LOC - transfer wait time,@xwait_multiplier * (odt_skims['DRV_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_number_of_transfers,DRIVE_LOC - number of transfers,@xfers_wlk_multiplier * ((odt_skims['DRV_LOC_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_LOC_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Drive_time,DRIVE_LOC - Drive time,@dtim_multiplier * (odt_skims['DRV_LOC_WLK_DTIM']/100 + dot_skims['WLK_LOC_DRV_DTIM']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Drive_time,DRIVE_LOC - Drive time,@dtim_multiplier * (odt_skims['DRV_LOC_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Walk_access_time,DRIVE_LOC - Walk access time,@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Walk_egress_time,DRIVE_LOC - Walk egress time (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Walk_other_time,DRIVE_LOC - Walk other time,@waux_multiplier * (odt_skims['DRV_LOC_WLK_WAUX']/100 + dot_skims['WLK_LOC_DRV_WAUX']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Fare_and_operating_cost,DRIVE_LOC - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_LOC_WLK_FAR'] + dot_skims['WLK_LOC_DRV_FAR']) + ((odt_skims['DRV_LOC_WLK_DDIST']/100+dot_skims['WLK_LOC_DRV_DDIST']/100) * costPerMile)),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_LOC_WLK_DDIST']/100+ dot_skims['WLK_LOC_DRV_DDIST']/100)/ (df.distance*2)),,,,,,,,,,,,,,1,,,,,,,
+util_DRIVE_LOC_Walk_other_time,DRIVE_LOC - Walk other time,@waux_multiplier * (odt_skims['DRV_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LOC_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Fare_and_operating_cost,DRIVE_LOC - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_LOC_WLK_FAR'] + dot_skims['WLK_LOC_DRV_FAR']) + ((odt_skims['DRV_LOC_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_LOC_DRV_DDIST']/TRANSIT_SCALE_FACTOR) * costPerMile)),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_LOC_WLK_DDIST']/TRANSIT_SCALE_FACTOR+ dot_skims['WLK_LOC_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']*2)),,,,,,,,,,,,,,1,,,,,,,
 util_DRIVE_LOC_Destination_zone_densityIndex,DRIVE_LOC - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Topology,DRIVE_LOC - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Person_is_less_than_10_years_old,DRIVE_LOC - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,coef_age010_trn_multiplier,,,,,,,
@@ -179,19 +179,19 @@ util_DRIVE_LOC_Person_is_less_than_10_years_old,DRIVE_LOC - Person is less than
 util_DRIVE_LRF_Unavailable,DRIVE_LRF - Unavailable,drive_lrf_available == False,,,,,,,,,,,,,,,-999,,,,,,
 util_DRIVE_LRF_Unavailable_for_zero_auto_households,DRIVE_LRF - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,-999,,,,,,
 util_DRIVE_LRF_Unavailable_for_persons_less_than_16,DRIVE_LRF - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,-999,,,,,,
-util_DRIVE_LRF_In_vehicle_time,DRIVE_LRF - In-vehicle time,@(odt_skims['DRV_LRF_WLK_TOTIVT']/100 + dot_skims['WLK_LRF_DRV_TOTIVT']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_In_vehicle_time_on_Light_Rail,DRIVE_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(ivt_lrt_multiplier-1) * (odt_skims['DRV_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_DRV_KEYIVT']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_In_vehicle_time_on_Ferry,DRIVE_LRF - In-vehicle time on Ferry (incremental w/ keyivt),@(ivt_ferry_multiplier-ivt_lrt_multiplier)*(odt_skims['DRV_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_DRV_FERRYIVT']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Short_iwait_time,DRIVE_LRF - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_LRF_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_LRF_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Long_iwait_time,DRIVE_LRF - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_LRF_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_LRF_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_transfer_wait_time,DRIVE_LRF - transfer wait time,@xwait_multiplier * (odt_skims['DRV_LRF_WLK_XWAIT']/100 + dot_skims['WLK_LRF_DRV_XWAIT']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_In_vehicle_time,DRIVE_LRF - In-vehicle time,@(odt_skims['DRV_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_In_vehicle_time_on_Light_Rail,DRIVE_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(ivt_lrt_multiplier-1) * (odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_In_vehicle_time_on_Ferry,DRIVE_LRF - In-vehicle time on Ferry (incremental w/ keyivt),@(ivt_ferry_multiplier-ivt_lrt_multiplier)*(odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_FERRYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Short_iwait_time,DRIVE_LRF - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_LRF_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Long_iwait_time,DRIVE_LRF - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_LRF_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_transfer_wait_time,DRIVE_LRF - transfer wait time,@xwait_multiplier * (odt_skims['DRV_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_number_of_transfers,DRIVE_LRF - number of transfers,@xfers_drv_multiplier * ((odt_skims['DRV_LRF_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_LRF_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Drive_time,DRIVE_LRF - Drive time,@dtim_multiplier * (odt_skims['DRV_LRF_WLK_DTIM']/100 + dot_skims['WLK_LRF_DRV_DTIM']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Drive_time,DRIVE_LRF - Drive time,@dtim_multiplier * (odt_skims['DRV_LRF_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Walk_access_time,DRIVE_LRF - Walk access time (at attraction end),@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Walk_egress_time,DRIVE_LRF - Walk egress time (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Walk_other_time,DRIVE_LRF - Walk other time,@waux_multiplier * (odt_skims['DRV_LRF_WLK_WAUX']/100 + dot_skims['WLK_LRF_DRV_WAUX']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Fare_and_operating_cost,DRIVE_LRF - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_LRF_WLK_FAR']+dot_skims['WLK_LRF_DRV_FAR']) + ((odt_skims['DRV_LRF_WLK_DDIST']/100+dot_skims['WLK_LRF_DRV_DDIST']/100) *costPerMile)),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_LRF_WLK_DDIST']/100+ dot_skims['WLK_LRF_DRV_DDIST']/100)/ (df.distance*2)),,,,,,,,,,,,,,,1,,,,,,
+util_DRIVE_LRF_Walk_other_time,DRIVE_LRF - Walk other time,@waux_multiplier * (odt_skims['DRV_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Fare_and_operating_cost,DRIVE_LRF - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_LRF_WLK_FAR']+dot_skims['WLK_LRF_DRV_FAR']) + ((odt_skims['DRV_LRF_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_LRF_DRV_DDIST']/TRANSIT_SCALE_FACTOR) *costPerMile)),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_LRF_WLK_DDIST']/TRANSIT_SCALE_FACTOR+ dot_skims['WLK_LRF_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']*2)),,,,,,,,,,,,,,,1,,,,,,
 util_DRIVE_LRF_Destination_zone_densityIndex,DRIVE_LRF - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Topology,DRIVE_LRF - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Person_is_less_than_10_years_old,DRIVE_LRF - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,coef_age010_trn_multiplier,,,,,,
@@ -199,18 +199,18 @@ util_DRIVE_LRF_Person_is_less_than_10_years_old,DRIVE_LRF - Person is less than
 util_DRIVE_EXP_Unavailable,DRIVE_EXP - Unavailable,drive_express_available == False,,,,,,,,,,,,,,,,-999,,,,,
 util_DRIVE_EXP_Unavailable_for_zero_auto_households,DRIVE_EXP - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,-999,,,,,
 util_DRIVE_EXP_Unavailable_for_persons_less_than_16,DRIVE_EXP - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,-999,,,,,
-util_DRIVE_EXP_In_vehicle_time,DRIVE_EXP - In-vehicle time,@(odt_skims['DRV_EXP_WLK_TOTIVT']/100 + dot_skims['WLK_EXP_DRV_TOTIVT']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_In_vehicle_time_on_Express_bus,DRIVE_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier-1) * (odt_skims['DRV_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_DRV_KEYIVT']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Short_iwait_time,DRIVE_EXP - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_EXP_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_EXP_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Long_iwait_time,DRIVE_EXP - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_EXP_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_EXP_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_transfer_wait_time,DRIVE_EXP - transfer wait time,@xwait_multiplier * (odt_skims['DRV_EXP_WLK_XWAIT']/100 + dot_skims['WLK_EXP_DRV_XWAIT']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_In_vehicle_time,DRIVE_EXP - In-vehicle time,@(odt_skims['DRV_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_In_vehicle_time_on_Express_bus,DRIVE_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier-1) * (odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Short_iwait_time,DRIVE_EXP - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_EXP_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Long_iwait_time,DRIVE_EXP - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_EXP_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_transfer_wait_time,DRIVE_EXP - transfer wait time,@xwait_multiplier * (odt_skims['DRV_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_number_of_transfers,DRIVE_EXP - number of transfers,@xfers_drv_multiplier * ((odt_skims['DRV_EXP_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_EXP_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Drive_time,DRIVE_EXP - Drive time,@dtim_multiplier * (odt_skims['DRV_EXP_WLK_DTIM']/100 + dot_skims['WLK_EXP_DRV_DTIM']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Drive_time,DRIVE_EXP - Drive time,@dtim_multiplier * (odt_skims['DRV_EXP_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Walk_access_time,DRIVE_EXP - Walk access time (at attraction end),@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Walk_egress_ime,DRIVE_EXP - Walk egress ime (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Walk_other_time,DRIVE_EXP - Walk other time,@waux_multiplier * (odt_skims['DRV_EXP_WLK_WAUX']/100 + dot_skims['WLK_EXP_DRV_WAUX']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Fare_and_operating_cost,DRIVE_EXP - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_EXP_WLK_FAR']+dot_skims['WLK_EXP_DRV_FAR']) + ((odt_skims['DRV_EXP_WLK_DDIST']/100+dot_skims['WLK_EXP_DRV_DDIST']/100) *costPerMile)),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_EXP_WLK_DDIST']/100+ dot_skims['WLK_EXP_DRV_DDIST']/100)/ (df.distance*2)),,,,,,,,,,,,,,,,1,,,,,
+util_DRIVE_EXP_Walk_other_time,DRIVE_EXP - Walk other time,@waux_multiplier * (odt_skims['DRV_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Fare_and_operating_cost,DRIVE_EXP - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_EXP_WLK_FAR']+dot_skims['WLK_EXP_DRV_FAR']) + ((odt_skims['DRV_EXP_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_EXP_DRV_DDIST']/TRANSIT_SCALE_FACTOR) *costPerMile)),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_EXP_WLK_DDIST']/TRANSIT_SCALE_FACTOR+ dot_skims['WLK_EXP_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']*2)),,,,,,,,,,,,,,,,1,,,,,
 util_DRIVE_EXP_Destination_zone_densityIndex,DRIVE_EXP - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Topology,DRIVE_EXP - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Person_is_less_than_10_years_old,DRIVE_EXP - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,coef_age010_trn_multiplier,,,,,
@@ -218,18 +218,18 @@ util_DRIVE_EXP_Person_is_less_than_10_years_old,DRIVE_EXP - Person is less than
 util_DRIVE_HVY_Unavailable,DRIVE_HVY - Unavailable,drive_heavyrail_available == False,,,,,,,,,,,,,,,,,-999,,,,
 util_DRIVE_HVY_Unavailable_for_zero_auto_households,DRIVE_HVY - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,,-999,,,,
 util_DRIVE_HVY_Unavailable_for_persons_less_than_16,DRIVE_HVY - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,-999,,,,
-util_DRIVE_HVY_In_vehicle_time,DRIVE_HVY - In-vehicle time,@(odt_skims['DRV_HVY_WLK_TOTIVT']/100 + dot_skims['WLK_HVY_DRV_TOTIVT']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_In_vehicle_time_on_heavy_rail,DRIVE_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * (odt_skims['DRV_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_DRV_KEYIVT']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Short_iwait_time,DRIVE_HVY - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_HVY_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_HVY_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Long_iwait_time,DRIVE_HVY - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_HVY_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_HVY_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_transfer_wait_time,DRIVE_HVY - transfer wait time,@xwait_multiplier * (odt_skims['DRV_HVY_WLK_XWAIT']/100 + dot_skims['WLK_HVY_DRV_XWAIT']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_In_vehicle_time,DRIVE_HVY - In-vehicle time,@(odt_skims['DRV_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_In_vehicle_time_on_heavy_rail,DRIVE_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * (odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Short_iwait_time,DRIVE_HVY - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_HVY_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Long_iwait_time,DRIVE_HVY - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_HVY_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_transfer_wait_time,DRIVE_HVY - transfer wait time,@xwait_multiplier * (odt_skims['DRV_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_number_of_transfers,DRIVE_HVY - number of transfers,@xfers_drv_multiplier * ((odt_skims['DRV_HVY_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_HVY_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Drive_time,DRIVE_HVY - Drive time,@dtim_multiplier * (odt_skims['DRV_HVY_WLK_DTIM']/100 + dot_skims['WLK_HVY_DRV_DTIM']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Drive_time,DRIVE_HVY - Drive time,@dtim_multiplier * (odt_skims['DRV_HVY_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Walk_access_time,DRIVE_HVY - Walk access time (at attraction end),@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Walk_egress_time,DRIVE_HVY - Walk egress time (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Walk_other_time,DRIVE_HVY - Walk other time,@waux_multiplier * (odt_skims['DRV_HVY_WLK_WAUX']/100 + dot_skims['WLK_HVY_DRV_WAUX']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Fare_and_operating_cost,DRIVE_HVY - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_HVY_WLK_FAR']+dot_skims['WLK_HVY_DRV_FAR']) + ((odt_skims['DRV_HVY_WLK_DDIST']/100+dot_skims['WLK_HVY_DRV_DDIST']/100) *costPerMile)),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY - Ratio of drive access distance to OD distance,@dacc_ratio * (odt_skims['DRV_HVY_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,,1,,,,
+util_DRIVE_HVY_Walk_other_time,DRIVE_HVY - Walk other time,@waux_multiplier * (odt_skims['DRV_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Fare_and_operating_cost,DRIVE_HVY - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_HVY_WLK_FAR']+dot_skims['WLK_HVY_DRV_FAR']) + ((odt_skims['DRV_HVY_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_HVY_DRV_DDIST']/TRANSIT_SCALE_FACTOR) *costPerMile)),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY - Ratio of drive access distance to OD distance,@dacc_ratio * (odt_skims['DRV_HVY_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,,1,,,,
 util_DRIVE_HVY_Destination_zone_densityIndex,DRIVE_HVY - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Topology,DRIVE_HVY - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Person_is_less_than_10_years_old,DRIVE_HVY - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,,coef_age010_trn_multiplier,,,,
@@ -237,18 +237,18 @@ util_DRIVE_HVY_Person_is_less_than_10_years_old,DRIVE_HVY - Person is less than
 util_DRIVE_COM_Unavailable,DRIVE_COM - Unavailable,drive_commuter_available == False,,,,,,,,,,,,,,,,,,-999,,,
 util_DRIVE_COM_Unavailable_for_zero_auto_households,DRIVE_COM - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,,,-999,,,
 util_DRIVE_COM_Unavailable_for_persons_less_than_16,DRIVE_COM - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,,-999,,,
-util_DRIVE_COM_In_vehicle_time,DRIVE_COM - In-vehicle time,@(odt_skims['DRV_COM_WLK_TOTIVT']/100 + dot_skims['WLK_COM_DRV_TOTIVT']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_In_vehicle_time_on_commuter_rail,DRIVE_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * (odt_skims['DRV_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_DRV_KEYIVT']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Short_iwait_time,DRIVE_COM - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_COM_WLK_IWAIT']/100).clip(upper=waitThresh) + (dot_skims['WLK_COM_DRV_IWAIT']/100).clip(upper=waitThresh)),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Long_iwait_time,DRIVE_COM - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_COM_WLK_IWAIT']/100-waitThresh).clip(0) + (dot_skims['WLK_COM_DRV_IWAIT']/100-waitThresh).clip(0)),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_transfer_wait_time,DRIVE_COM - transfer wait time,@xwait_multiplier * (odt_skims['DRV_COM_WLK_XWAIT']/100 + dot_skims['WLK_COM_DRV_XWAIT']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_In_vehicle_time,DRIVE_COM - In-vehicle time,@(odt_skims['DRV_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_In_vehicle_time_on_commuter_rail,DRIVE_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * (odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Short_iwait_time,DRIVE_COM - Short iwait time,@short_i_wait_multiplier * ((odt_skims['DRV_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh) + (dot_skims['WLK_COM_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh)),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Long_iwait_time,DRIVE_COM - Long iwait time,@long_i_wait_multiplier * ((odt_skims['DRV_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0) + (dot_skims['WLK_COM_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0)),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_transfer_wait_time,DRIVE_COM - transfer wait time,@xwait_multiplier * (odt_skims['DRV_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_XWAIT']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_number_of_transfers,DRIVE_COM - number of transfers,@xfers_drv_multiplier * ((odt_skims['DRV_COM_WLK_BOARDS']-1).clip(0) + (dot_skims['WLK_COM_DRV_BOARDS']-1).clip(0)),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Drive_time,DRIVE_COM - Drive time,@dtim_multiplier * (odt_skims['DRV_COM_WLK_DTIM']/100 + dot_skims['WLK_COM_DRV_DTIM']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Drive_time,DRIVE_COM - Drive time,@dtim_multiplier * (odt_skims['DRV_COM_WLK_DTIM']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_DTIM']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Walk_access_time,DRIVE_COM - Walk access time (at attraction end),@wacc_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Walk_egress_time,DRIVE_COM - Walk egress time (at attraction end),@wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Walk_other_time,DRIVE_COM - Walk other time,@waux_multiplier * (odt_skims['DRV_COM_WLK_WAUX']/100 + dot_skims['WLK_COM_DRV_WAUX']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Fare_and_operating_cost,DRIVE_COM - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_COM_WLK_FAR']+dot_skims['WLK_COM_DRV_FAR']) + ((odt_skims['DRV_COM_WLK_DDIST']/100+dot_skims['WLK_COM_DRV_DDIST']/100) *costPerMile)),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_COM_WLK_DDIST']/100 + dot_skims['WLK_COM_DRV_DDIST']/100)/ (df.distance*2)),,,,,,,,,,,,,,,,,,1,,,
+util_DRIVE_COM_Walk_other_time,DRIVE_COM - Walk other time,@waux_multiplier * (odt_skims['DRV_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_WAUX']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Fare_and_operating_cost,DRIVE_COM - Fare and operating cost,@ivt_cost_multiplier * df.ivot * ((odt_skims['DRV_COM_WLK_FAR']+dot_skims['WLK_COM_DRV_FAR']) + ((odt_skims['DRV_COM_WLK_DDIST']/TRANSIT_SCALE_FACTOR+dot_skims['WLK_COM_DRV_DDIST']/TRANSIT_SCALE_FACTOR) *costPerMile)),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM - Ratio of drive access distance to OD distance,@dacc_ratio * ((odt_skims['DRV_COM_WLK_DDIST']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']*2)),,,,,,,,,,,,,,,,,,1,,,
 util_DRIVE_COM_Destination_zone_densityIndex,DRIVE_COM - Destination zone densityIndex,@density_index_multiplier * df.dest_density_index,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Topology,DRIVE_COM - Topology,@coef_topology_trn_multiplier * df.dest_topology,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Person_is_less_than_10_years_old,DRIVE_COM - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,,,coef_age010_trn_multiplier,,,
@@ -338,9 +338,9 @@ util_Heavy_Rail_ASC,Heavy Rail ASC,1,,,,,,,,,,,,heavy_rail_ASC,,,,,heavy_rail_AS
 util_Commuter_Rail,Commuter Rail,1,,,,,,,,,,,,,commuter_rail_ASC,,,,,commuter_rail_ASC,,,
 util_Walk_to_Transit_dest_CBD,Walk to Transit dest CBD,@df.destination_in_cbd,,,,,,,,,walk_transit_CBD_ASC,walk_transit_CBD_ASC,walk_transit_CBD_ASC,walk_transit_CBD_ASC,walk_transit_CBD_ASC,,,,,,,,
 util_Drive_to_Transit_dest_CBD,Drive to Transit dest CBD,@df.destination_in_cbd,,,,,,,,,,,,,,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,drive_transit_CBD_ASC,,,
-util_Drive_to_Transit_distance_penalty,Drive to Transit - distance penalty,@drvtrn_distpen_0_multiplier * (1-df.distance/drvtrn_distpen_max).clip(lower=0),,,,,,,,,,,,,,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,,,
+util_Drive_to_Transit_distance_penalty,Drive to Transit - distance penalty,@drvtrn_distpen_0_multiplier * (1-od_skims['DIST']/drvtrn_distpen_max).clip(lower=0),,,,,,,,,,,,,,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,,,
 #, FIXME - skims aren't symmetrical,so we have to make sure they can get back,,,,,,,,,,,,,,,,,,,,,
-util_Walk_not_available_for_long_distances,Walk not available for long distances,@df.distance_walk_od > 3,,,,,,,-999,,,,,,,,,,,,,,
-util_Bike_not_available_for_long_distances,Bike not available for long distances,@df.distance_bike_od > 8,,,,,,,,-999,,,,,,,,,,,,,
+util_Walk_not_available_for_long_distances,Walk not available for long distances,@od_skims.max('DISTWALK') > 3,,,,,,,-999,,,,,,,,,,,,,,
+util_Bike_not_available_for_long_distances,Bike not available for long distances,@od_skims.max('DISTBIKE') > 8,,,,,,,,-999,,,,,,,,,,,,,
 util_Drive_alone_not_available_for_escort_tours,Drive alone not available for escort tours,is_escort,-999,-999,,,,,,,,,,,,,,,,,,,
 #, max(c_densityIndexOrigin*originDensityIndex,originDensityIndexMax),,,,,,,,,1,1,1,1,1,1,1,,,,,,
diff --git a/activitysim/examples/example_psrc/configs/tour_mode_choice_annotate_choosers_preprocessor.csv b/activitysim/examples/example_psrc/configs/tour_mode_choice_annotate_choosers_preprocessor.csv
index 9d205debb..121a90888 100755
--- a/activitysim/examples/example_psrc/configs/tour_mode_choice_annotate_choosers_preprocessor.csv
+++ b/activitysim/examples/example_psrc/configs/tour_mode_choice_annotate_choosers_preprocessor.csv
@@ -75,18 +75,18 @@ local,_DF_IS_TOUR,'tour_type' in df.columns
 ,hov2toll_available,(odt_skims['HOV2TOLL_VTOLL'] + dot_skims['HOV2TOLL_VTOLL'])>0
 ,hov3_available,(odt_skims['HOV3_TIME']>0) & (dot_skims['HOV3_TIME']>0)
 ,hov3toll_available,(odt_skims['HOV3TOLL_VTOLL'] + dot_skims['HOV3TOLL_VTOLL'])>0
-,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LOC_WLK_TOTIVT']/100>0)
-,walk_commuter_available,walk_transit_available & (odt_skims['WLK_COM_WLK_TOTIVT']/100>0) & (dot_skims['WLK_COM_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_WLK_KEYIVT']/100)>0)
-,walk_express_available,walk_transit_available & (odt_skims['WLK_EXP_WLK_TOTIVT']/100>0) & (dot_skims['WLK_EXP_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_WLK_KEYIVT']/100)>0)
-,walk_heavyrail_available,walk_transit_available & (odt_skims['WLK_HVY_WLK_TOTIVT']/100>0) & (dot_skims['WLK_HVY_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_WLK_KEYIVT']/100)>0)
-,walk_lrf_available,walk_transit_available & (odt_skims['WLK_LRF_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LRF_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_WLK_KEYIVT']/100)>0)
-,walk_ferry_available,walk_lrf_available & ((odt_skims['WLK_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100)>0)
-,drive_local_available,drive_transit_available & (odt_skims['DRV_LOC_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LOC_DRV_TOTIVT']/100>0)
-,drive_commuter_available,drive_transit_available & (odt_skims['DRV_COM_WLK_TOTIVT']/100>0) & (dot_skims['WLK_COM_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_DRV_KEYIVT']/100)>0)
-,drive_express_available,drive_transit_available & (odt_skims['DRV_EXP_WLK_TOTIVT']/100>0) & (dot_skims['WLK_EXP_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_DRV_KEYIVT']/100)>0)
-,drive_heavyrail_available,drive_transit_available & (odt_skims['DRV_HVY_WLK_TOTIVT']/100>0) & (dot_skims['WLK_HVY_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_DRV_KEYIVT']/100)>0)
-,drive_lrf_available,drive_transit_available & (odt_skims['DRV_LRF_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LRF_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_DRV_KEYIVT']/100)>0)
-,drive_ferry_available,drive_lrf_available & ((odt_skims['DRV_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100)>0)
+,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_commuter_available,walk_transit_available & (odt_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,walk_express_available,walk_transit_available & (odt_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,walk_heavyrail_available,walk_transit_available & (odt_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,walk_lrf_available,walk_transit_available & (odt_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,walk_ferry_available,walk_lrf_available & ((odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_local_available,drive_transit_available & (odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_commuter_available,drive_transit_available & (odt_skims['DRV_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_COM_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_express_available,drive_transit_available & (odt_skims['DRV_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_EXP_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_heavyrail_available,drive_transit_available & (odt_skims['DRV_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_HVY_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_lrf_available,drive_transit_available & (odt_skims['DRV_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LRF_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+,drive_ferry_available,drive_lrf_available & ((odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR)>0)
 #,,
 destination in central business district,destination_in_cbd,"(reindex(land_use.area_type, df[dest_col_name]) < setting('cbd_threshold')) * 1"
 #,,FIXME diagnostic
diff --git a/activitysim/examples/example_psrc/configs/trip_destination.yaml b/activitysim/examples/example_psrc/configs/trip_destination.yaml
index 0ebe89683..4165986d7 100644
--- a/activitysim/examples/example_psrc/configs/trip_destination.yaml
+++ b/activitysim/examples/example_psrc/configs/trip_destination.yaml
@@ -15,7 +15,7 @@ DEST_CHOICE_SAMPLE_TABLE_NAME: trip_destination_sample
 # model-specific logsum-related settings
 TRIP_ORIGIN: origin
 ALT_DEST_COL_NAME: alt_dest
-PRIMARY_DEST: destination
+PRIMARY_DEST: tour_leg_dest # must be created in preprocessor
 
 REDUNDANT_TOURS_MERGED_CHOOSER_COLUMNS:
   - tour_mode
diff --git a/activitysim/examples/example_psrc/configs/trip_destination_annotate_trips_preprocessor.csv b/activitysim/examples/example_psrc/configs/trip_destination_annotate_trips_preprocessor.csv
index 0e5e80100..e4317d8e8 100755
--- a/activitysim/examples/example_psrc/configs/trip_destination_annotate_trips_preprocessor.csv
+++ b/activitysim/examples/example_psrc/configs/trip_destination_annotate_trips_preprocessor.csv
@@ -7,3 +7,4 @@ Description,Target,Expression
 #,,not needed as school is not chosen as an intermediate trip destination
 #,_grade_school,"(df.primary_purpose == 'school') & reindex(persons.is_gradeschool, df.person_id)"
 #,size_segment,"df.primary_purpose.where(df.primary_purpose != 'school', np.where(_grade_school,'gradeschool', 'highschool'))"
+,tour_leg_dest,"np.where(df.outbound,reindex(tours.destination, df.tour_id), reindex(tours.origin, df.tour_id))"
\ No newline at end of file
diff --git a/activitysim/examples/example_psrc/configs/trip_mode_choice.csv b/activitysim/examples/example_psrc/configs/trip_mode_choice.csv
index 7e15afc03..2da242e95 100644
--- a/activitysim/examples/example_psrc/configs/trip_mode_choice.csv
+++ b/activitysim/examples/example_psrc/configs/trip_mode_choice.csv
@@ -69,87 +69,87 @@ util_SHARED3PAY_One_person_household,SHARED3PAY - One person household,@(df.hhsi
 util_SHARED3PAY_Two_person_household,SHARED3PAY - Two person household,@(df.hhsize == 2),,,,,,coef_hhsize2_sr,,,,,,,,,,,,,,,
 util_SHARED3PAY_Person_is_16_years_old_or_older,SHARED3PAY - Person is 16 years old or older,@(df.age >= 16),,,,,,coef_age16p_sr,,,,,,,,,,,,,,,
 #,Walk,,,,,,,,,,,,,,,,,,,,,,
-util_WALK_Time_up_to_2_miles,WALK - Time up to 2 miles,@coef_walktimeshort_multiplier * df.distance_walk_od.clip(upper=walkThresh) * 60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
-util_WALK_Time_beyond_2_of_a_miles,WALK - Time beyond 2 of a miles,@walktimelong_multiplier * (df.distance_walk_od - walkThresh).clip(lower=0) * 60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
+util_WALK_Time_up_to_2_miles,WALK - Time up to 2 miles,@coef_walktimeshort_multiplier * od_skims['DISTWALK'].clip(upper=walkThresh) * 60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
+util_WALK_Time_beyond_2_of_a_miles,WALK - Time beyond 2 of a miles,@walktimelong_multiplier * (od_skims['DISTWALK'] - walkThresh).clip(lower=0) * 60/walkSpeed,,,,,,,coef_ivt,,,,,,,,,,,,,,
 util_WALK_Destination_zone_densityIndex,WALK - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,coef_ivt,,,,,,,,,,,,,,
 util_WALK_Topology,WALK - Topology,@topology_walk_multiplier * df.trip_topology,,,,,,,coef_ivt,,,,,,,,,,,,,,
 #,Bike,,,,,,,,,,,,,,,,,,,,,,
 util_BIKE_Unavailable_if_didn't_bike_to_work,BIKE - Unavailable if didn't bike to work,is_atwork_subtour & ~work_tour_is_bike,,,,,,,,-999,,,,,,,,,,,,,
-util_BIKE_Time_up_to_6_miles,BIKE - Time up to 6 miles,@coef_biketimeshort_multiplier * df.distance_bike_od.clip(upper=bikeThresh)*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
-util_BIKE_Time_beyond_6_of_a_miles,BIKE - Time beyond 6 of a miles,@coef_biketimeshort_multiplier * biketimelong_multiplier * (df.distance_bike_od-bikeThresh).clip(lower=0)*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
+util_BIKE_Time_up_to_6_miles,BIKE - Time up to 6 miles,@coef_biketimeshort_multiplier * od_skims['DISTBIKE'].clip(upper=bikeThresh)*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
+util_BIKE_Time_beyond_6_of_a_miles,BIKE - Time beyond 6 of a miles,@coef_biketimeshort_multiplier * biketimelong_multiplier * (od_skims['DISTBIKE']-bikeThresh).clip(lower=0)*60/bikeSpeed,,,,,,,,coef_ivt,,,,,,,,,,,,,
 util_BIKE_Destination_zone_densityIndex,BIKE - Destination zone densityIndex,@density_index_multiplier*df.density_index,,,,,,,,coef_ivt,,,,,,,,,,,,,
 util_BIKE_Topology,BIKE - Topology,@topology_bike_multiplier * df.trip_topology,,,,,,,,coef_ivt,,,,,,,,,,,,,
 #,Walk to Local,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_LOC_Unavailable,WALK_LOC - Unavailable,walk_local_available == False,,,,,,,,,-999,,,,,,,,,,,,
-util_WALK_LOC_In_vehicle_time,WALK_LOC - In-vehicle time,@odt_skims['WLK_LOC_WLK_TOTIVT']/100,,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Short_iwait_time,WALK_LOC - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_LOC_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Long_iwait_time,WALK_LOC - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_LOC_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_transfer_wait_time,WALK_LOC - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_LOC_WLK_XWAIT']/100,,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_In_vehicle_time,WALK_LOC - In-vehicle time,@odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Short_iwait_time,WALK_LOC - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Long_iwait_time,WALK_LOC - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_transfer_wait_time,WALK_LOC - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_number_of_transfers,WALK_LOC - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_LOC_WLK_BOARDS']-1).clip(0),,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Walk_access_time,WALK_LOC - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Walk_egress_time,WALK_LOC - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,coef_ivt,,,,,,,,,,,,
-util_WALK_LOC_Walk_other_time,WALK_LOC - Walk other time,@coef_waux_multiplier * odt_skims['WLK_LOC_WLK_WAUX']/100,,,,,,,,,coef_ivt,,,,,,,,,,,,
+util_WALK_LOC_Walk_other_time,WALK_LOC - Walk other time,@coef_waux_multiplier * odt_skims['WLK_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Fare,WALK_LOC - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_LOC_WLK_FAR'],,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Destination_zone_densityIndex,WALK_LOC - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Topology,WALK_LOC - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,coef_ivt,,,,,,,,,,,,
 util_WALK_LOC_Person_is_less_than_10_years_old,WALK_LOC - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,coef_age010_trn,,,,,,,,,,,,
 #,Walk to Light rail/Ferry,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_LRF_Unavailable,WALK_LRF - Unavailable,walk_lrf_available == False,,,,,,,,,,-999,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time,WALK_LRF - In-vehicle time,@odt_skims['WLK_LRF_WLK_TOTIVT']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time_on_Light_Rail,WALK_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(coef_ivt_lrt_multiplier-1) * odt_skims['WLK_LRF_WLK_KEYIVT']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_In_vehicle_time_on_Ferry,WALK_LRF - In-vehicle time on Ferry (incremental w/keyivt),@(coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier) * odt_skims['WLK_LRF_WLK_FERRYIVT']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Short_iwait_time,WALK_LRF - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_LRF_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Long_iwait_time,WALK_LRF - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_LRF_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_transfer_wait_time,WALK_LRF - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_LRF_WLK_XWAIT']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time,WALK_LRF - In-vehicle time,@odt_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time_on_Light_Rail,WALK_LRF - In-vehicle time on Light Rail (incremental w/ ivt),@(coef_ivt_lrt_multiplier-1) * odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_In_vehicle_time_on_Ferry,WALK_LRF - In-vehicle time on Ferry (incremental w/keyivt),@(coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier) * odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Short_iwait_time,WALK_LRF - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Long_iwait_time,WALK_LRF - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_transfer_wait_time,WALK_LRF - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_number_of_transfers,WALK_LRF - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_LRF_WLK_BOARDS']-1).clip(0),,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Walk_access_time,WALK_LRF - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Walk_egress_time,WALK_LRF - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,coef_ivt,,,,,,,,,,,
-util_WALK_LRF_Walk_other_time,WALK_LRF - Walk otherLight rail/Ferry time,@coef_waux_multiplier * odt_skims['WLK_LRF_WLK_WAUX']/100,,,,,,,,,,coef_ivt,,,,,,,,,,,
+util_WALK_LRF_Walk_other_time,WALK_LRF - Walk otherLight rail/Ferry time,@coef_waux_multiplier * odt_skims['WLK_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Fare,WALK_LRF - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_LRF_WLK_FAR'],,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Destination_zone_densityIndex,WALK_LRF - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Topology,WALK_LRF - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,coef_ivt,,,,,,,,,,,
 util_WALK_LRF_Person_is_less_than_10_years_old,WALK_LRF - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,coef_age010_trn,,,,,,,,,,,
 #,Walk to Express bus,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_EXP_Unavailable,WALK_EXP - Unavailable,walk_express_available == False,,,,,,,,,,,-999,,,,,,,,,,
-util_WALK_EXP_In_vehicle_time,WALK_EXP - In-vehicle time,@odt_skims['WLK_EXP_WLK_TOTIVT']/100,,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_In_vehicle_time_on_Express_bus,WALK_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier - 1) * odt_skims['WLK_EXP_WLK_KEYIVT']/100,,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Short_iwait_time,WALK_EXP - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_EXP_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Long_iwait_time,WALK_EXP - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_EXP_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_transfer_wait_time,WALK_EXP - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_EXP_WLK_XWAIT']/100,,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_In_vehicle_time,WALK_EXP - In-vehicle time,@odt_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_In_vehicle_time_on_Express_bus,WALK_EXP - In-vehicle time on Express bus (incremental w/ ivt),@(ivt_exp_multiplier - 1) * odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Short_iwait_time,WALK_EXP - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Long_iwait_time,WALK_EXP - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_transfer_wait_time,WALK_EXP - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_number_of_transfers,WALK_EXP - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_EXP_WLK_BOARDS']-1).clip(0),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Walk_access_time,WALK_EXP - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Walk_egress_time,WALK_EXP - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,coef_ivt,,,,,,,,,,
-util_WALK_EXP_Walk_other_time,WALK_EXP - Walk other time,@coef_waux_multiplier * odt_skims['WLK_EXP_WLK_WAUX']/100,,,,,,,,,,,coef_ivt,,,,,,,,,,
+util_WALK_EXP_Walk_other_time,WALK_EXP - Walk other time,@coef_waux_multiplier * odt_skims['WLK_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Fare,WALK_EXP - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_EXP_WLK_FAR'],,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Destination_zone_densityIndex,WALK_EXP - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Topology,WALK_EXP - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_WALK_EXP_Person_is_less_than_10_years_old,WALK_EXP - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,,coef_age010_trn,,,,,,,,,,
 #,Walk to Heavy Rail,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_HVY_Unavailable,WALK_HVY - Unavailable,walk_heavyrail_available == False,,,,,,,,,,,,-999,,,,,,,,,
-util_WALK_HVY_In_vehicle_time,WALK_HVY - In-vehicle time,@odt_skims['WLK_HVY_WLK_TOTIVT']/100,,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_In_vehicle_time_on_heavy_rail,WALK_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * odt_skims['WLK_HVY_WLK_KEYIVT']/100,,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Short_iwait_time,WALK_HVY - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_HVY_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Long_iwait_time,WALK_HVY - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_HVY_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_transfer_wait_time,WALK_HVY - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_HVY_WLK_XWAIT']/100,,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_In_vehicle_time,WALK_HVY - In-vehicle time,@odt_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_In_vehicle_time_on_heavy_rail,WALK_HVY - In-vehicle time on heavy rail (incremental w/ ivt),@(ivt_hvy_multiplier-1) * odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Short_iwait_time,WALK_HVY - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Long_iwait_time,WALK_HVY - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_transfer_wait_time,WALK_HVY - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_number_of_transfers,WALK_HVY - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_HVY_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Walk_access_time,WALK_HVY - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Walk_egress_time,WALK_HVY - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,coef_ivt,,,,,,,,,
-util_WALK_HVY_Walk_other_time,WALK_HVY - Walk other time,@coef_waux_multiplier * odt_skims['WLK_HVY_WLK_WAUX']/100,,,,,,,,,,,,coef_ivt,,,,,,,,,
+util_WALK_HVY_Walk_other_time,WALK_HVY - Walk other time,@coef_waux_multiplier * odt_skims['WLK_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Fare,WALK_HVY - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_HVY_WLK_FAR'],,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Destination_zone_densityIndex,WALK_HVY - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Topology,WALK_HVY - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,coef_ivt,,,,,,,,,
 util_WALK_HVY_Person_is_less_than_10_years_old,WALK_HVY - Person is less than 10 years old,@(df.age <= 10),,,,,,,,,,,,coef_age010_trn,,,,,,,,,
 #,Walk to Commuter rail,,,,,,,,,,,,,,,,,,,,,,
 util_WALK_COM_Unavailable,WALK_COM - Unavailable,walk_commuter_available == False,,,,,,,,,,,,,-999,,,,,,,,
-util_WALK_COM_In_vehicle_time,WALK_COM - In-vehicle time,@odt_skims['WLK_COM_WLK_TOTIVT']/100,,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_In_vehicle_time_on_commuter_rail,WALK_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * odt_skims['WLK_COM_WLK_KEYIVT']/100,,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Short_iwait_time,WALK_COM - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_COM_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Long_iwait_time,WALK_COM - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_COM_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_transfer_wait_time,WALK_COM - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_COM_WLK_XWAIT']/100,,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_In_vehicle_time,WALK_COM - In-vehicle time,@odt_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_In_vehicle_time_on_commuter_rail,WALK_COM - In-vehicle time on commuter rail (incremental w/ ivt),@(ivt_com_multiplier - 1) * odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Short_iwait_time,WALK_COM - Short iwait time,@coef_short_iwait_multiplier * (odt_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Long_iwait_time,WALK_COM - Long iwait time,@coef_long_iwait_multiplier * (odt_skims['WLK_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_transfer_wait_time,WALK_COM - transfer wait time,@coef_xwait_multiplier * odt_skims['WLK_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_number_of_transfers,WALK_COM - number of transfers,@xfers_wlk_multiplier * (odt_skims['WLK_COM_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Walk_access_time,WALK_COM - Walk access time,@coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Walk_egress_time,WALK_COM - Walk egress time,@coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,coef_ivt,,,,,,,,
-util_WALK_COM_Walk_other_time,WALK_COM - Walk other time,@coef_waux_multiplier * odt_skims['WLK_COM_WLK_WAUX']/100,,,,,,,,,,,,,coef_ivt,,,,,,,,
+util_WALK_COM_Walk_other_time,WALK_COM - Walk other time,@coef_waux_multiplier * odt_skims['WLK_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Fare,WALK_COM - Fare,@ivt_cost_multiplier * df.ivot * odt_skims['WLK_COM_WLK_FAR'],,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Destination_zone_densityIndex,WALK_COM - Destination zone densityIndex,@density_index_multiplier * df.density_index,,,,,,,,,,,,,coef_ivt,,,,,,,,
 util_WALK_COM_Topology,WALK_COM - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,coef_ivt,,,,,,,,
@@ -161,27 +161,27 @@ util_DRIVE_LOC_Destination_zone_densityIndex,DRIVE_LOC - Destination zone densit
 util_DRIVE_LOC_Topology,DRIVE_LOC - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_Person_is_less_than_10_years_old,DRIVE_LOC - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,coef_age010_trn,,,,,,,
 util_DRIVE_LOC_outbound_Unavailable,DRIVE_LOC outbound - Unavailable,outbound & ~drive_local_available_outbound,,,,,,,,,,,,,,-999,,,,,,,
-util_DRIVE_LOC_outbound_In_vehicle_time,DRIVE_LOC outbound - In-vehicle time,@df.outbound * odt_skims['DRV_LOC_WLK_TOTIVT']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Short_iwait_time,DRIVE_LOC outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_LOC_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Long_iwait_time,DRIVE_LOC outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_LOC_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_transfer_wait_time,DRIVE_LOC outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_LOC_WLK_XWAIT']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_In_vehicle_time,DRIVE_LOC outbound - In-vehicle time,@df.outbound * odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Short_iwait_time,DRIVE_LOC outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Long_iwait_time,DRIVE_LOC outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_LOC_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_transfer_wait_time,DRIVE_LOC outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_LOC_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_outbound_number_of_transfers,DRIVE_LOC outbound - number of transfers,@df.outbound * xfers_wlk_multiplier * (odt_skims['DRV_LOC_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Drive_time,DRIVE_LOC outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_LOC_WLK_DTIM']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Drive_time,DRIVE_LOC outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_LOC_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_outbound_Walk_egress_time,DRIVE_LOC outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Walk_other_time,DRIVE_LOC outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_LOC_WLK_WAUX']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Fare_and_operating_cost,DRIVE_LOC outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_LOC_WLK_FAR'] + costPerMile*odt_skims['DRV_LOC_WLK_DDIST']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_LOC_WLK_DDIST']/100)/ (df.distance),,,,,,,,,,,,,,1,,,,,,,
+util_DRIVE_LOC_outbound_Walk_other_time,DRIVE_LOC outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_LOC_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Fare_and_operating_cost,DRIVE_LOC outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_LOC_WLK_FAR'] + costPerMile*odt_skims['DRV_LOC_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_LOC_WLK_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']),,,,,,,,,,,,,,1,,,,,,,
 util_DRIVE_LOC_inbound_Unavailable,DRIVE_LOC inbound - Unavailable,inbound & ~drive_local_available_inbound,,,,,,,,,,,,,,-999,,,,,,,
-util_DRIVE_LOC_inbound_In_vehicle_time,DRIVE_LOC inbound - In-vehicle time,@df.inbound * odt_skims['WLK_LOC_DRV_TOTIVT']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Short_iwait_time,DRIVE_LOC inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_LOC_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Long_iwait_time,DRIVE_LOC inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_LOC_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_transfer_wait_time,DRIVE_LOC inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_LOC_DRV_XWAIT']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_In_vehicle_time,DRIVE_LOC inbound - In-vehicle time,@df.inbound * odt_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Short_iwait_time,DRIVE_LOC inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_LOC_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Long_iwait_time,DRIVE_LOC inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_LOC_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_transfer_wait_time,DRIVE_LOC inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_LOC_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_inbound_number_of_transfers,DRIVE_LOC inbound - number of transfers,@df.inbound * xfers_wlk_multiplier * (odt_skims['WLK_LOC_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Drive_time,DRIVE_LOC inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_LOC_DRV_DTIM']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Drive_time,DRIVE_LOC inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_LOC_DRV_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
 util_DRIVE_LOC_inbound_Walk_access_time,DRIVE_LOC inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Walk_other_time,DRIVE_LOC inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_LOC_DRV_WAUX']/100,,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Fare_and_operating_cost,DRIVE_LOC inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LOC_DRV_FAR'] + costPerMile*odt_skims['WLK_LOC_DRV_DDIST']/100),,,,,,,,,,,,,,coef_ivt,,,,,,,
-util_DRIVE_LOC_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC inbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['WLK_LOC_DRV_DDIST']/100)/ (df.distance),,,,,,,,,,,,,,1,,,,,,,
+util_DRIVE_LOC_inbound_Walk_other_time,DRIVE_LOC inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_LOC_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Fare_and_operating_cost,DRIVE_LOC inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LOC_DRV_FAR'] + costPerMile*odt_skims['WLK_LOC_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,coef_ivt,,,,,,,
+util_DRIVE_LOC_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LOC inbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['WLK_LOC_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ (od_skims['DIST']),,,,,,,,,,,,,,1,,,,,,,
 #,Drive to Light Rail/Ferry,,,,,,,,,,,,,,,,,,,,,,
 util_DRIVE_LRF_Unavailable_for_zero_auto_households,DRIVE_LRF - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,-999,,,,,,
 util_DRIVE_LRF_Unavailable_for_persons_less_than_16,DRIVE_LRF - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,-999,,,,,,
@@ -189,31 +189,31 @@ util_DRIVE_LRF_Destination_zone_densityIndex,DRIVE_LRF  - Destination zone densi
 util_DRIVE_LRF_Topology,DRIVE_LRF  - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_Person_is_less_than_10_years_old,DRIVE_LRF  - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,coef_age010_trn,,,,,,
 util_DRIVE_LRF_outbound_Unavailable,DRIVE_LRF outbound - Unavailable,outbound & ~drive_lrf_available_outbound,,,,,,,,,,,,,,,-999,,,,,,
-util_DRIVE_LRF_outbound_In_vehicle_time,DRIVE_LRF outbound - In-vehicle time,@df.outbound * odt_skims['DRV_LRF_WLK_TOTIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_In_vehicle_time_on_LR,DRIVE_LRF outbound - In-vehicle time on Light Rail (incremental w/ ivt),@df.outbound * (coef_ivt_lrt_multiplier - 1)*odt_skims['DRV_LRF_WLK_KEYIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_In_vehicle_time_on_Ferry,DRIVE_LRF outbound - In-vehicle time on Ferry (incremental w/ keyivt),@df.outbound * (coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier)*odt_skims['DRV_LRF_WLK_FERRYIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Short_iwait_time,DRIVE_LRF outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_LRF_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Long_iwait_time,DRIVE_LRF outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_LRF_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_transfer_wait_time,DRIVE_LRF outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_LRF_WLK_XWAIT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_In_vehicle_time,DRIVE_LRF outbound - In-vehicle time,@df.outbound * odt_skims['DRV_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_In_vehicle_time_on_LR,DRIVE_LRF outbound - In-vehicle time on Light Rail (incremental w/ ivt),@df.outbound * (coef_ivt_lrt_multiplier - 1)*odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_In_vehicle_time_on_Ferry,DRIVE_LRF outbound - In-vehicle time on Ferry (incremental w/ keyivt),@df.outbound * (coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier)*odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Short_iwait_time,DRIVE_LRF outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Long_iwait_time,DRIVE_LRF outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_LRF_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_transfer_wait_time,DRIVE_LRF outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_LRF_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_outbound_number_of_transfers,DRIVE_LRF outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DRV_LRF_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Drive_time,DRIVE_LRF outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_LRF_WLK_DTIM']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Drive_time,DRIVE_LRF outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_LRF_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_outbound_Walk_egress_time,DRIVE_LRF outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Walk_other_time,DRIVE_LRF outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_LRF_WLK_WAUX']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Fare_and_operating_cost,DRIVE_LRF outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_LRF_WLK_FAR'] + costPerMile * odt_skims['DRV_LRF_WLK_DDIST']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_LRF_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,1,,,,,,
+util_DRIVE_LRF_outbound_Walk_other_time,DRIVE_LRF outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_LRF_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Fare_and_operating_cost,DRIVE_LRF outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_LRF_WLK_FAR'] + costPerMile * odt_skims['DRV_LRF_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_LRF_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,1,,,,,,
 util_DRIVE_LRF_inbound_Unavailable,DRIVE_LRF inbound - Unavailable,inbound & ~drive_lrf_available_inbound,,,,,,,,,,,,,,,-999,,,,,,
-util_DRIVE_LRF_inbound_In_vehicle_time,DRIVE_LRF inbound - In-vehicle time,@df.inbound * odt_skims['WLK_LRF_DRV_TOTIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_In_vehicle_time_on_LR,DRIVE_LRF inbound - In-vehicle time on Light Rail (incremental w/ ivt),@df.inbound * (coef_ivt_lrt_multiplier - 1)*odt_skims['WLK_LRF_DRV_KEYIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_In_vehicle_time_on_Ferry,DRIVE_LRF inbound - In-vehicle time on Ferry (incremental w/ keyivt),@df.inbound * (coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier)*odt_skims['WLK_LRF_DRV_FERRYIVT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Short_iwait_time,DRIVE_LRF inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_LRF_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Long_iwait_time,DRIVE_LRF inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_LRF_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_transfer_wait_time,DRIVE_LRF inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_LRF_DRV_XWAIT']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_In_vehicle_time,DRIVE_LRF inbound - In-vehicle time,@df.inbound * odt_skims['WLK_LRF_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_In_vehicle_time_on_LR,DRIVE_LRF inbound - In-vehicle time on Light Rail (incremental w/ ivt),@df.inbound * (coef_ivt_lrt_multiplier - 1)*odt_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_In_vehicle_time_on_Ferry,DRIVE_LRF inbound - In-vehicle time on Ferry (incremental w/ keyivt),@df.inbound * (coef_ivt_ferry_multiplier-coef_ivt_lrt_multiplier)*odt_skims['WLK_LRF_DRV_FERRYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Short_iwait_time,DRIVE_LRF inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_LRF_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Long_iwait_time,DRIVE_LRF inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_LRF_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_transfer_wait_time,DRIVE_LRF inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_LRF_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_inbound_number_of_transfers,DRIVE_LRF inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WLK_LRF_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Drive_time,DRIVE_LRF inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_LRF_DRV_DTIM']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Drive_time,DRIVE_LRF inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_LRF_DRV_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
 util_DRIVE_LRF_inbound_Walk_access_time,DRIVE_LRF inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Walk_other_time,DRIVE_LRF inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_LRF_DRV_WAUX']/100,,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Fare_and_operating_cost,DRIVE_LRF inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LRF_DRV_FAR'] + costPerMile * odt_skims['WLK_LRF_DRV_DDIST']/100),,,,,,,,,,,,,,,coef_ivt,,,,,,
-util_DRIVE_LRF_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_LRF_DRV_DDIST']/100)/ df.distance,,,,,,,,,,,,,,,1,,,,,,
+util_DRIVE_LRF_inbound_Walk_other_time,DRIVE_LRF inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_LRF_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Fare_and_operating_cost,DRIVE_LRF inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_LRF_DRV_FAR'] + costPerMile * odt_skims['WLK_LRF_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,coef_ivt,,,,,,
+util_DRIVE_LRF_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_LRF inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_LRF_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ od_skims['DIST'],,,,,,,,,,,,,,,1,,,,,,
 #,Drive to Express bus,,,,,,,,,,,,,,,,,,,,,,
 util_DRIVE_EXP_Unavailable_for_zero_auto_households,DRIVE_EXP - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,-999,,,,,
 util_DRIVE_EXP_Unavailable_for_persons_less_than_16,DRIVE_EXP - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,-999,,,,,
@@ -221,29 +221,29 @@ util_DRIVE_EXP_Destination_zone_densityIndex,DRIVE_EXP - Destination zone densit
 util_DRIVE_EXP_Topology,DRIVE_EXP - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_Person_is_less_than_10_years_old,DRIVE_EXP - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,coef_age010_trn,,,,,
 util_DRIVE_EXP_outbound_Unavailable,DRIVE_EXP outbound - Unavailable,outbound & ~drive_express_available_outbound,,,,,,,,,,,,,,,,-999,,,,,
-util_DRIVE_EXP_outbound_In_vehicle_time,DRIVE_EXP outbound - In-vehicle time,@df.outbound * odt_skims['DRV_EXP_WLK_TOTIVT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_In_vehicle_time_on_EXP,DRIVE_EXP outbound - In-vehicle time on Express bus (incremental w/ ivt),@df.outbound * (ivt_exp_multiplier - 1) * odt_skims['DRV_EXP_WLK_KEYIVT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Short_iwait_time,DRIVE_EXP outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_EXP_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Long_iwait_time,DRIVE_EXP outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_EXP_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_transfer_wait_time,DRIVE_EXP outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_EXP_WLK_XWAIT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_In_vehicle_time,DRIVE_EXP outbound - In-vehicle time,@df.outbound * odt_skims['DRV_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_In_vehicle_time_on_EXP,DRIVE_EXP outbound - In-vehicle time on Express bus (incremental w/ ivt),@df.outbound * (ivt_exp_multiplier - 1) * odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Short_iwait_time,DRIVE_EXP outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Long_iwait_time,DRIVE_EXP outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_EXP_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_transfer_wait_time,DRIVE_EXP outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_EXP_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_outbound_number_of_transfers,DRIVE_EXP outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DRV_EXP_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Drive_time,DRIVE_EXP outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_EXP_WLK_DTIM']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Drive_time,DRIVE_EXP outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_EXP_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_outbound_Walk_egress_time,DRIVE_EXP outbound - Walk egress ime,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Walk_other_time,DRIVE_EXP outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_EXP_WLK_WAUX']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Fare_and_operating_cost,DRIVE_EXP outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_EXP_WLK_FAR'] + costPerMile * odt_skims['DRV_EXP_WLK_DDIST']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_EXP_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Walk_other_time,DRIVE_EXP outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_EXP_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Fare_and_operating_cost,DRIVE_EXP outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_EXP_WLK_FAR'] + costPerMile * odt_skims['DRV_EXP_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_EXP_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_inbound_Unavailable,DRIVE_EXP inbound - Unavailable,inbound & ~drive_express_available_inbound,,,,,,,,,,,,,,,,-999,,,,,
-util_DRIVE_EXP_inbound_In_vehicle_time,DRIVE_EXP inbound - In-vehicle time,@df.inbound * odt_skims['WLK_EXP_DRV_TOTIVT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_In_vehicle_time_on_EXP,DRIVE_EXP inbound - In-vehicle time on Express bus (incremental w/ ivt),@df.inbound * (ivt_exp_multiplier - 1) * odt_skims['WLK_EXP_DRV_KEYIVT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Short_iwait_time,DRIVE_EXP inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_EXP_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Long_iwait_time,DRIVE_EXP inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_EXP_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_transfer_wait_time,DRIVE_EXP inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_EXP_DRV_XWAIT']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_In_vehicle_time,DRIVE_EXP inbound - In-vehicle time,@df.inbound * odt_skims['WLK_EXP_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_In_vehicle_time_on_EXP,DRIVE_EXP inbound - In-vehicle time on Express bus (incremental w/ ivt),@df.inbound * (ivt_exp_multiplier - 1) * odt_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Short_iwait_time,DRIVE_EXP inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_EXP_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Long_iwait_time,DRIVE_EXP inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_EXP_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_transfer_wait_time,DRIVE_EXP inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_EXP_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_inbound_number_of_transfers,DRIVE_EXP inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WLK_EXP_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Drive_time,DRIVE_EXP inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_EXP_DRV_DTIM']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Drive_time,DRIVE_EXP inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_EXP_DRV_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
 util_DRIVE_EXP_inbound_Walk_access_time,DRIVE_EXP inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Walk_other_time,DRIVE_EXP inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_EXP_DRV_WAUX']/100,,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Fare_and_operating_cost,DRIVE_EXP inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_EXP_DRV_FAR'] + costPerMile * odt_skims['WLK_EXP_DRV_DDIST']/100),,,,,,,,,,,,,,,,coef_ivt,,,,,
-util_DRIVE_EXP_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_EXP_DRV_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,1,,,,,
+util_DRIVE_EXP_inbound_Walk_other_time,DRIVE_EXP inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_EXP_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Fare_and_operating_cost,DRIVE_EXP inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_EXP_DRV_FAR'] + costPerMile * odt_skims['WLK_EXP_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,coef_ivt,,,,,
+util_DRIVE_EXP_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_EXP inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_EXP_DRV_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,1,,,,,
 #,Drive to Heavy Rail,,,,,,,,,,,,,,,,,,,,,,
 util_DRIVE_HVY_Unavailable_for_zero_auto_households,DRIVE_HVY - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,,-999,,,,
 util_DRIVE_HVY_Unavailable_for_persons_less_than_16,DRIVE_HVY - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,-999,,,,
@@ -251,29 +251,29 @@ util_DRIVE_HVY_Destination_zone_densityIndex,DRIVE_HVY - Destination zone densit
 util_DRIVE_HVY_Topology,DRIVE_HVY - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_Person_is_less_than_10_years_old,DRIVE_HVY - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,,coef_age010_trn,,,,
 util_DRIVE_HVY_outbound_Unavailable,DRIVE_HVY outbound - Unavailable,outbound & ~drive_heavyrail_available_outbound,,,,,,,,,,,,,,,,,-999,,,,
-util_DRIVE_HVY_outbound_In_vehicle_time,DRIVE_HVY outbound - In-vehicle time,@df.outbound * odt_skims['DRV_HVY_WLK_TOTIVT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_In_vehicle_time_on_HVY,DRIVE_HVY outbound - In-vehicle time on heavy rail (incremental w/ ivt),@df.outbound * (ivt_hvy_multiplier - 1) * odt_skims['DRV_HVY_WLK_KEYIVT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Short_iwait_time,DRIVE_HVY outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_HVY_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Long_iwait_time,DRIVE_HVY outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_HVY_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_transfer_wait_time,DRIVE_HVY outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_HVY_WLK_XWAIT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_In_vehicle_time,DRIVE_HVY outbound - In-vehicle time,@df.outbound * odt_skims['DRV_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_In_vehicle_time_on_HVY,DRIVE_HVY outbound - In-vehicle time on heavy rail (incremental w/ ivt),@df.outbound * (ivt_hvy_multiplier - 1) * odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Short_iwait_time,DRIVE_HVY outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Long_iwait_time,DRIVE_HVY outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_HVY_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_transfer_wait_time,DRIVE_HVY outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_HVY_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_outbound_number_of_transfers,DRIVE_HVY outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DRV_HVY_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Drive_time,DRIVE_HVY outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_HVY_WLK_DTIM']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Drive_time,DRIVE_HVY outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_HVY_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_outbound_Walk_egress_time,DRIVE_HVY outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Walk_other_time,DRIVE_HVY outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_HVY_WLK_WAUX']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Fare_and_operating_cost,DRIVE_HVY outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_HVY_WLK_FAR'] + costPerMile * odt_skims['DRV_HVY_WLK_DDIST']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_HVY_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Walk_other_time,DRIVE_HVY outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_HVY_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Fare_and_operating_cost,DRIVE_HVY outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_HVY_WLK_FAR'] + costPerMile * odt_skims['DRV_HVY_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_HVY_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_inbound_Unavailable,DRIVE_HVY inbound - Unavailable,inbound & ~drive_heavyrail_available_inbound,,,,,,,,,,,,,,,,,-999,,,,
-util_DRIVE_HVY_inbound_In_vehicle_time,DRIVE_HVY inbound - In-vehicle time,@df.inbound * odt_skims['WLK_HVY_DRV_TOTIVT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_In_vehicle_time_on_HVY,DRIVE_HVY inbound - In-vehicle time on heavy rail (incremental w/ ivt),@df.inbound * (ivt_hvy_multiplier - 1) * odt_skims['WLK_HVY_DRV_KEYIVT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Short_iwait_time,DRIVE_HVY inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_HVY_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Long_iwait_time,DRIVE_HVY inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_HVY_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_transfer_wait_time,DRIVE_HVY inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_HVY_DRV_XWAIT']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_In_vehicle_time,DRIVE_HVY inbound - In-vehicle time,@df.inbound * odt_skims['WLK_HVY_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_In_vehicle_time_on_HVY,DRIVE_HVY inbound - In-vehicle time on heavy rail (incremental w/ ivt),@df.inbound * (ivt_hvy_multiplier - 1) * odt_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Short_iwait_time,DRIVE_HVY inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_HVY_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Long_iwait_time,DRIVE_HVY inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_HVY_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_transfer_wait_time,DRIVE_HVY inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_HVY_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_inbound_number_of_transfers,DRIVE_HVY inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WLK_HVY_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Drive_time,DRIVE_HVY inbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_HVY_WLK_DTIM']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Drive_time,DRIVE_HVY inbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_HVY_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
 util_DRIVE_HVY_inbound_Walk_access_time,DRIVE_HVY inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Walk_other_time,DRIVE_HVY inbound - Walk other time,@coef_waux_multiplier * odt_skims['WLK_HVY_DRV_WAUX']/100,,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Fare_and_operating_cost,DRIVE_HVY inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_HVY_DRV_FAR'] + costPerMile * odt_skims['WLK_HVY_DRV_DDIST']/100),,,,,,,,,,,,,,,,,coef_ivt,,,,
-util_DRIVE_HVY_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_HVY_DRV_DDIST']/100)/ df.distance,,,,,,,,,,,,,,,,,1,,,,
+util_DRIVE_HVY_inbound_Walk_other_time,DRIVE_HVY inbound - Walk other time,@coef_waux_multiplier * odt_skims['WLK_HVY_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Fare_and_operating_cost,DRIVE_HVY inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_HVY_DRV_FAR'] + costPerMile * odt_skims['WLK_HVY_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,coef_ivt,,,,
+util_DRIVE_HVY_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_HVY inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_HVY_DRV_DDIST']/TRANSIT_SCALE_FACTOR)/ od_skims['DIST'],,,,,,,,,,,,,,,,,1,,,,
 #,#Drive to Commuter Rail,,,,,,,,,,,,,,,,,,,,,,
 util_DRIVE_COM_Unavailable_for_zero_auto_households,DRIVE_COM - Unavailable for zero auto households,auto_ownership == 0,,,,,,,,,,,,,,,,,,-999,,,
 util_DRIVE_COM_Unavailable_for_persons_less_than_16,DRIVE_COM - Unavailable for persons less than 16,age < 16,,,,,,,,,,,,,,,,,,-999,,,
@@ -281,29 +281,29 @@ util_DRIVE_COM_Destination_zone_densityIndex,DRIVE_COM - Destination zone densit
 util_DRIVE_COM_Topology,DRIVE_COM - Topology,@topology_trn_multiplier * df.trip_topology,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_Person_is_less_than_10_years_old,DRIVE_COM - Person is less than 10 years old,@(df.age < 10),,,,,,,,,,,,,,,,,,coef_age010_trn,,,
 util_DRIVE_COM_outbound_Unavailable,DRIVE_COM outbound - Unavailable,outbound & ~drive_commuter_available_outbound,,,,,,,,,,,,,,,,,,-999,,,
-util_DRIVE_COM_outbound_In_vehicle_time,DRIVE_COM outbound - In-vehicle time,@df.outbound * odt_skims['DRV_COM_WLK_TOTIVT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_In_vehicle_time_on_COM,DRIVE_COM outbound - In-vehicle time on commuter rail (incremental w/ ivt),@df.outbound * (ivt_com_multiplier - 1) * odt_skims['DRV_COM_WLK_KEYIVT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Short_iwait_time,DRIVE_COM outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_COM_WLK_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Long_iwait_time,DRIVE_COM outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_COM_WLK_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_transfer_wait_time,DRIVE_COM outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_COM_WLK_XWAIT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_In_vehicle_time,DRIVE_COM outbound - In-vehicle time,@df.outbound * odt_skims['DRV_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_In_vehicle_time_on_COM,DRIVE_COM outbound - In-vehicle time on commuter rail (incremental w/ ivt),@df.outbound * (ivt_com_multiplier - 1) * odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Short_iwait_time,DRIVE_COM outbound - Short iwait time,@df.outbound * coef_short_iwait_multiplier * (odt_skims['DRV_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Long_iwait_time,DRIVE_COM outbound - Long iwait time,@df.outbound * coef_long_iwait_multiplier * (odt_skims['DRV_COM_WLK_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_transfer_wait_time,DRIVE_COM outbound - transfer wait time,@df.outbound * coef_xwait_multiplier * odt_skims['DRV_COM_WLK_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_outbound_number_of_transfers,DRIVE_COM outbound - number of transfers,@df.outbound * xfers_drv_multiplier * (odt_skims['DRV_COM_WLK_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Drive_time,DRIVE_COM outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_COM_WLK_DTIM']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Drive_time,DRIVE_COM outbound - Drive time,@df.outbound * coef_dtim_multiplier * odt_skims['DRV_COM_WLK_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_outbound_Walk_egress_time,DRIVE_COM outbound - Walk egress time,@df.outbound * coef_wegr_multiplier * df.destination_walk_time,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Walk_other_time,DRIVE_COM outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_COM_WLK_WAUX']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Fare_and_operating_cost,DRIVE_COM outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_COM_WLK_FAR'] + costPerMile * odt_skims['DRV_COM_WLK_DDIST']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_COM_WLK_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,,,1,,,
+util_DRIVE_COM_outbound_Walk_other_time,DRIVE_COM outbound - Walk other time,@df.outbound * coef_waux_multiplier * odt_skims['DRV_COM_WLK_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Fare_and_operating_cost,DRIVE_COM outbound - Fare and operating cost,@df.outbound * ivt_cost_multiplier * df.ivot * (odt_skims['DRV_COM_WLK_FAR'] + costPerMile * odt_skims['DRV_COM_WLK_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_outbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM outbound - Ratio of drive access distance to OD distance,@df.outbound * dacc_ratio_multiplier * (odt_skims['DRV_COM_WLK_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,,,1,,,
 util_DRIVE_COM_inbound_Unavailable,DRIVE_COM inbound - Unavailable,inbound & ~drive_commuter_available_inbound,,,,,,,,,,,,,,,,,,-999,,,
-util_DRIVE_COM_inbound_In_vehicle_time,DRIVE_COM inbound - In-vehicle time,@df.inbound * odt_skims['WLK_COM_DRV_TOTIVT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_In_vehicle_time_on_COM,DRIVE_COM inbound - In-vehicle time on commuter rail (incremental w/ ivt),@df.inbound * (ivt_com_multiplier - 1) * odt_skims['WLK_COM_DRV_KEYIVT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Short_iwait_time,DRIVE_COM inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_COM_DRV_IWAIT']/100).clip(upper=waitThresh),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Long_iwait_time,DRIVE_COM inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_COM_DRV_IWAIT']/100-waitThresh).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_transfer_wait_time,DRIVE_COM inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_COM_DRV_XWAIT']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_In_vehicle_time,DRIVE_COM inbound - In-vehicle time,@df.inbound * odt_skims['WLK_COM_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_In_vehicle_time_on_COM,DRIVE_COM inbound - In-vehicle time on commuter rail (incremental w/ ivt),@df.inbound * (ivt_com_multiplier - 1) * odt_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Short_iwait_time,DRIVE_COM inbound - Short iwait time,@df.inbound * coef_short_iwait_multiplier * (odt_skims['WLK_COM_DRV_IWAIT']/TRANSIT_SCALE_FACTOR).clip(upper=waitThresh),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Long_iwait_time,DRIVE_COM inbound - Long iwait time,@df.inbound * coef_long_iwait_multiplier * (odt_skims['WLK_COM_DRV_IWAIT']/TRANSIT_SCALE_FACTOR-waitThresh).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_transfer_wait_time,DRIVE_COM inbound - transfer wait time,@df.inbound * coef_xwait_multiplier * odt_skims['WLK_COM_DRV_XWAIT']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_inbound_number_of_transfers,DRIVE_COM inbound - number of transfers,@df.inbound * xfers_drv_multiplier * (odt_skims['WLK_COM_DRV_BOARDS']-1).clip(0),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Drive_time,DRIVE_COM inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_COM_DRV_DTIM']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Drive_time,DRIVE_COM inbound - Drive time,@df.inbound * coef_dtim_multiplier * odt_skims['WLK_COM_DRV_DTIM']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
 util_DRIVE_COM_inbound_Walk_access_time,DRIVE_COM inbound - Walk access time,@df.inbound * coef_wacc_multiplier * df.origin_walk_time,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Walk_other_time,DRIVE_COM inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_COM_DRV_WAUX']/100,,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Fare_and_operating_cost,DRIVE_COM inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_COM_DRV_FAR'] + costPerMile * odt_skims['WLK_COM_DRV_DDIST']/100),,,,,,,,,,,,,,,,,,coef_ivt,,,
-util_DRIVE_COM_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_COM_DRV_DDIST']/100) / df.distance,,,,,,,,,,,,,,,,,,1,,,
+util_DRIVE_COM_inbound_Walk_other_time,DRIVE_COM inbound - Walk other time,@df.inbound * coef_waux_multiplier * odt_skims['WLK_COM_DRV_WAUX']/TRANSIT_SCALE_FACTOR,,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Fare_and_operating_cost,DRIVE_COM inbound - Fare and operating cost,@df.inbound * ivt_cost_multiplier * df.ivot * (odt_skims['WLK_COM_DRV_FAR'] + costPerMile * odt_skims['WLK_COM_DRV_DDIST']/TRANSIT_SCALE_FACTOR),,,,,,,,,,,,,,,,,,coef_ivt,,,
+util_DRIVE_COM_inbound_Ratio_of_drive_access_distance_to_OD_distance,DRIVE_COM inbound - Ratio of drive access distance to OD distance,@df.inbound * dacc_ratio_multiplier * (odt_skims['WLK_COM_DRV_DDIST']/TRANSIT_SCALE_FACTOR) / od_skims['DIST'],,,,,,,,,,,,,,,,,,1,,,
 #,Taxi,,,,,,,,,,,,,,,,,,,,,,
 util_Taxi_In_vehicle_time,Taxi - In-vehicle time,@odt_skims['HOV2TOLL_TIME'],,,,,,,,,,,,,,,,,,,coef_ivt,,
 util_Taxi_Wait_time,Taxi - Wait time,@ridehail_wait_time_multiplier * df.origTaxiWaitTime,,,,,,,,,,,,,,,,,,,coef_ivt,,
@@ -398,8 +398,8 @@ util_joint_Ride_Hail_tour_mode_ASC_ride_hail_taxi,joint - Ride Hail tour mode AS
 util_joint_Ride_Hail_tour_mode_ASC_ride_hail_single,joint - Ride Hail tour mode ASC -- ride hail,@(df.is_joint & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,,joint_ride_hail_ASC_tnc_single,
 util_joint_Ride_Hail_tour_mode_ASC_ride_hail_shared,joint - Ride Hail tour mode ASC -- ride hail,@(df.is_joint & df.i_tour_mode.isin(I_RIDE_HAIL_MODES)),,,,,,,,,,,,,,,,,,,,,joint_ride_hail_ASC_tnc_shared
 #,#,,,,,,,,,,,,,,,,,,,,,,
-util_Walk_not_available_for_long_distances,Walk not available for long distances,@df.tour_mode_is_walk & (df.distance_walk_od > 3),,,,,,,-999,,,,,,,,,,,,,,
-util_Bike_not_available_for_long_distances,Bike not available for long distances,@df.tour_mode_is_walk & (df.distance_bike_od > 8),,,,,,,,-999,,,,,,,,,,,,,
+util_Walk_not_available_for_long_distances,Walk not available for long distances,@df.tour_mode_is_walk & (od_skims['DISTWALK'] > 3),,,,,,,-999,,,,,,,,,,,,,,
+util_Bike_not_available_for_long_distances,Bike not available for long distances,@df.tour_mode_is_walk & (od_skims['DISTBIKE'] > 8),,,,,,,,-999,,,,,,,,,,,,,
 util_origin_density_index,Origin density index,@origin_density_applied*(origin_density_index_multiplier*df.origin_density_index).clip(origin_density_index_max),,,,,,,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,coef_ivt,,,,,,,coef_ivt,coef_ivt
 util_walk_express_penalty,Walk-express penalty for intermediate stops,@walk_express_penalty * ~(df.first_trip | df.first_trip),,,,,,,,,,,coef_ivt,,,,,,,,,,
 util_adjust_tnc_shared,TNC shared adjustment,@adjust_tnc_shared,,,,,,,,,,,,,,,,,,,,,coef_ivt
diff --git a/activitysim/examples/example_psrc/configs/trip_mode_choice_annotate_trips_preprocessor.csv b/activitysim/examples/example_psrc/configs/trip_mode_choice_annotate_trips_preprocessor.csv
index 21aaee9dc..6350d71c2 100644
--- a/activitysim/examples/example_psrc/configs/trip_mode_choice_annotate_trips_preprocessor.csv
+++ b/activitysim/examples/example_psrc/configs/trip_mode_choice_annotate_trips_preprocessor.csv
@@ -64,24 +64,24 @@ dest terminal time not counted at home,_dest_terminal_time,"np.where(inbound & l
 ,sovtoll_available,odt_skims['SOVTOLL_VTOLL']>0
 ,hov2toll_available,odt_skims['HOV2TOLL_VTOLL']>0
 ,hov3toll_available,odt_skims['HOV3TOLL_VTOLL']>0
-,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/100>0)
-,walk_lrf_available,walk_transit_available & (i_tour_mode >= 10) & (odt_skims['WLK_LRF_WLK_KEYIVT']/100>0)
-,walk_express_available,walk_transit_available & (i_tour_mode >= 11) & (odt_skims['WLK_EXP_WLK_KEYIVT']/100>0)
-,walk_heavyrail_available,walk_transit_available & (i_tour_mode >= 12) & (odt_skims['WLK_HVY_WLK_KEYIVT']/100>0)
-,walk_commuter_available,walk_transit_available & (i_tour_mode >= 13) & (odt_skims['WLK_COM_WLK_KEYIVT']/100>0)
-,drive_local_available_outbound,drive_transit_available & df.outbound & (odt_skims['DRV_LOC_WLK_TOTIVT']/100>0)
-,drive_local_available_inbound,drive_transit_available & ~df.outbound & (odt_skims['WLK_LOC_DRV_TOTIVT']/100>0)
-,drive_lrf_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 15) & (odt_skims['DRV_LRF_WLK_KEYIVT']/100>0)
-,drive_lrf_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 15) & (odt_skims['WLK_LRF_DRV_KEYIVT']/100>0)
-,drive_express_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 16) & (odt_skims['DRV_EXP_WLK_KEYIVT']/100>0)
-,drive_express_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 16) & (odt_skims['WLK_EXP_DRV_KEYIVT']/100>0)
-,drive_heavyrail_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 17) & (odt_skims['DRV_HVY_WLK_KEYIVT']/100>0)
-,drive_heavyrail_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 17) & (odt_skims['WLK_HVY_DRV_KEYIVT']/100>0)
-,drive_commuter_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 18) & (odt_skims['DRV_COM_WLK_KEYIVT']/100>0)
-,drive_commuter_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 18) & (odt_skims['WLK_COM_DRV_KEYIVT']/100>0)
-,walk_ferry_available,walk_lrf_available & (odt_skims['WLK_LRF_WLK_FERRYIVT']/100>0)
-,_drive_ferry_available_outbound,drive_lrf_available_outbound & (odt_skims['DRV_LRF_WLK_FERRYIVT']/100>0)
-,_drive_ferry_available_inbound,drive_lrf_available_inbound & (odt_skims['WLK_LRF_DRV_FERRYIVT']/100>0)
+,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_lrf_available,walk_transit_available & (i_tour_mode >= 10) & (odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_express_available,walk_transit_available & (i_tour_mode >= 11) & (odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_heavyrail_available,walk_transit_available & (i_tour_mode >= 12) & (odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_commuter_available,walk_transit_available & (i_tour_mode >= 13) & (odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_local_available_outbound,drive_transit_available & df.outbound & (odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_local_available_inbound,drive_transit_available & ~df.outbound & (odt_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_lrf_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 15) & (odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_lrf_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 15) & (odt_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_express_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 16) & (odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_express_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 16) & (odt_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_heavyrail_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 17) & (odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_heavyrail_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 17) & (odt_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_commuter_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 18) & (odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,drive_commuter_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 18) & (odt_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+,walk_ferry_available,walk_lrf_available & (odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
+,_drive_ferry_available_outbound,drive_lrf_available_outbound & (odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
+,_drive_ferry_available_inbound,drive_lrf_available_inbound & (odt_skims['WLK_LRF_DRV_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
 ,drive_ferry_available,"np.where(df.outbound, _drive_ferry_available_outbound, _drive_ferry_available_inbound)"
 #,od_dist_walk,od_skims['DISTWALK']
 #,do_dist_walk,od_skims.reverse('DISTWALK')
diff --git a/activitysim/examples/example_sandag/configs_1_zone/constants.yaml b/activitysim/examples/example_sandag/configs_1_zone/constants.yaml
new file mode 100644
index 000000000..c680bc41e
--- /dev/null
+++ b/activitysim/examples/example_sandag/configs_1_zone/constants.yaml
@@ -0,0 +1,6 @@
+inherit_settings: True
+
+# Correction for transit skim expressions
+# e.g. MTC transit skims (Cube TRANPLAN skims) use scaled ints and
+# therefore need to be divided by the scale factor if used in expressions
+TRANSIT_SCALE_FACTOR: 1
diff --git a/activitysim/examples/example_sandag/configs_2_zone/constants.yaml b/activitysim/examples/example_sandag/configs_2_zone/constants.yaml
new file mode 100644
index 000000000..c680bc41e
--- /dev/null
+++ b/activitysim/examples/example_sandag/configs_2_zone/constants.yaml
@@ -0,0 +1,6 @@
+inherit_settings: True
+
+# Correction for transit skim expressions
+# e.g. MTC transit skims (Cube TRANPLAN skims) use scaled ints and
+# therefore need to be divided by the scale factor if used in expressions
+TRANSIT_SCALE_FACTOR: 1
diff --git a/activitysim/examples/example_sandag/configs_3_zone/accessibility.csv b/activitysim/examples/example_sandag/configs_3_zone/accessibility.csv
index 245d4abce..30cd16ad5 100644
--- a/activitysim/examples/example_sandag/configs_3_zone/accessibility.csv
+++ b/activitysim/examples/example_sandag/configs_3_zone/accessibility.csv
@@ -23,7 +23,7 @@ auto off-peak total,auOpTotal,df.TOTEMP * _decay
 o-d peak transit time,_trPkTime_od,"tvpb.get_tvpb_best_transit_time(orig=df.orig, dest=df.dest, tod='AM')"
 #,, assume peak inbound transit occurs in PM
 o-d peak transit time,_trPkTime_do,"tvpb.get_tvpb_best_transit_time(orig=df.dest, dest=df.orig, tod='PM')"
-peak transit time,_trPkTime,_trPkTime_od + _trPkTime_do
+peak transit time,_trPkTime,(_trPkTime_od + _trPkTime_do).clip(0)
 round trip path is available,_rt_available,(_trPkTime_od > 0) & (_trPkTime_do > 0)
 decay function,_decay,_rt_available * exp(_trPkTime * dispersion_parameter_transit)
 transit peak retail,trPkRetail,df.RETEMPN * _decay
@@ -34,7 +34,7 @@ transit peak total,trPkTotal,df.TOTEMP * _decay
 ####,, assume off-peak inbound and outbound transit occurs in the MD time period
 o-d off-peak transit time,_trOpTime_od,"tvpb.get_tvpb_best_transit_time(orig=df.orig, dest=df.dest, tod='MD')"
 d-o off-peak transit time,_trOpTime_do,"tvpb.get_tvpb_best_transit_time(orig=df.dest, dest=df.orig, tod='MD')"
-off-peak transit time,_trOpTime,_trOpTime_od + _trPkTime_do
+off-peak transit time,_trOpTime,(_trOpTime_od + _trPkTime_do).clip(0)
 round trip path is available,_rt_available,(_trOpTime_od > 0) & (_trOpTime_do > 0)
 decay function,_decay,_rt_available * exp(_trOpTime * dispersion_parameter_transit)
 transit off-peak retail,trOpRetail,df.RETEMPN * _decay
diff --git a/activitysim/examples/example_sandag/configs_3_zone/annotate_persons_workplace.csv b/activitysim/examples/example_sandag/configs_3_zone/annotate_persons_workplace.csv
index 2779b8a25..0a3f574c2 100644
--- a/activitysim/examples/example_sandag/configs_3_zone/annotate_persons_workplace.csv
+++ b/activitysim/examples/example_sandag/configs_3_zone/annotate_persons_workplace.csv
@@ -17,19 +17,19 @@ work_zone_area_type,work_zone_area_type,"reindex(land_use.area_type, persons.wor
 ,_roundtrip_walk_time_to_work,"np.where(_work_walk_available, _walk_time_home_to_work + _walk_time_work_to_home, _MAX_TIME_TO_WORK)"
 #,,_roundtrip_transit_time_to_work
 ##### ,_IVT_SKIM,"skim_dict.get(('WLK_TRN_WLK_IVT', 'MD'))"
-##### ,_transit_ivt_home_to_work,"_IVT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100"
-##### ,_transit_ivt_work_to_home,"_IVT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_ivt_home_to_work,"_IVT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR"
+##### ,_transit_ivt_work_to_home,"_IVT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_work_transit_available,(_transit_ivt_home_to_work > 0) & (_transit_ivt_work_to_home > 0)
 ##### ,_IWAIT_SKIM,"skim_dict.get(('WLK_TRN_WLK_IWAIT', 'MD'))"
-##### ,_transit_iwait,"_IWAIT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _IWAIT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_iwait,"_IWAIT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _IWAIT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_XWAIT_SKIM,"skim_dict.get(('WLK_TRN_WLK_XWAIT', 'MD'))"
-##### ,_transit_xwait,"_XWAIT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _XWAIT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_xwait,"_XWAIT_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _XWAIT_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_WAUX_SKIM,"skim_dict.get(('WLK_TRN_WLK_WAUX', 'MD'))"
-##### ,_transit_waux,"_WAUX_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _WAUX_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_waux,"_WAUX_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _WAUX_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_WACC_SKIM,"skim_dict.get(('WLK_TRN_WLK_WACC', 'MD'))"
-##### ,_transit_wacc,"_WACC_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _WACC_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_wacc,"_WACC_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _WACC_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_WEGR_SKIM,"skim_dict.get(('WLK_TRN_WLK_WEGR', 'MD'))"
-##### ,_transit_wegr,"_WEGR_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/100 + _WEGR_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/100"
+##### ,_transit_wegr,"_WEGR_SKIM.get(persons.home_zone_id, persons.workplace_zone_id)/TRANSIT_SCALE_FACTOR + _WEGR_SKIM.get(persons.workplace_zone_id, persons.home_zone_id)/TRANSIT_SCALE_FACTOR"
 ##### ,_roundtrip_transit_time_to_work,_transit_ivt_home_to_work + _transit_ivt_work_to_home + _transit_iwait + _transit_xwait + _transit_waux + _transit_wacc + _transit_wegr
 ##### #,,work_auto_savings_ratio
 ##### ,_min_work_walk_transit,"np.where(_work_transit_available, np.minimum(_roundtrip_transit_time_to_work, _roundtrip_walk_time_to_work), _roundtrip_walk_time_to_work)"
diff --git a/activitysim/examples/example_sandag/configs_3_zone/constants.yaml b/activitysim/examples/example_sandag/configs_3_zone/constants.yaml
new file mode 100644
index 000000000..c680bc41e
--- /dev/null
+++ b/activitysim/examples/example_sandag/configs_3_zone/constants.yaml
@@ -0,0 +1,6 @@
+inherit_settings: True
+
+# Correction for transit skim expressions
+# e.g. MTC transit skims (Cube TRANPLAN skims) use scaled ints and
+# therefore need to be divided by the scale factor if used in expressions
+TRANSIT_SCALE_FACTOR: 1
diff --git a/activitysim/examples/example_sandag/configs_3_zone/tour_mode_choice_annotate_choosers_preprocessor.csv b/activitysim/examples/example_sandag/configs_3_zone/tour_mode_choice_annotate_choosers_preprocessor.csv
index 9427a9345..5642857a4 100644
--- a/activitysim/examples/example_sandag/configs_3_zone/tour_mode_choice_annotate_choosers_preprocessor.csv
+++ b/activitysim/examples/example_sandag/configs_3_zone/tour_mode_choice_annotate_choosers_preprocessor.csv
@@ -81,18 +81,18 @@ local,_DF_IS_TOUR,'tour_type' in df.columns
 ,hov2toll_available,(odt_skims['HOV2TOLL_VTOLL'] + dot_skims['HOV2TOLL_VTOLL'])>0
 ,hov3_available,(odt_skims['HOV3_TIME']>0) & (dot_skims['HOV3_TIME']>0)
 ,hov3toll_available,(odt_skims['HOV3TOLL_VTOLL'] + dot_skims['HOV3TOLL_VTOLL'])>0
-#,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LOC_WLK_TOTIVT']/100>0)
-#,walk_commuter_available,walk_transit_available & (odt_skims['WLK_COM_WLK_TOTIVT']/100>0) & (dot_skims['WLK_COM_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_WLK_KEYIVT']/100)>0)
-#,walk_express_available,walk_transit_available & (odt_skims['WLK_EXP_WLK_TOTIVT']/100>0) & (dot_skims['WLK_EXP_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_WLK_KEYIVT']/100)>0)
-#,walk_heavyrail_available,walk_transit_available & (odt_skims['WLK_HVY_WLK_TOTIVT']/100>0) & (dot_skims['WLK_HVY_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_WLK_KEYIVT']/100)>0)
-#,walk_lrf_available,walk_transit_available & (odt_skims['WLK_LRF_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LRF_WLK_TOTIVT']/100>0) & ((odt_skims['WLK_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_WLK_KEYIVT']/100)>0)
-#,walk_ferry_available,walk_lrf_available & ((odt_skims['WLK_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100)>0)
-#,drive_local_available,drive_transit_available & (odt_skims['DRV_LOC_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LOC_DRV_TOTIVT']/100>0)
-#,drive_commuter_available,drive_transit_available & (odt_skims['DRV_COM_WLK_TOTIVT']/100>0) & (dot_skims['WLK_COM_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_COM_WLK_KEYIVT']/100 + dot_skims['WLK_COM_DRV_KEYIVT']/100)>0)
-#,drive_express_available,drive_transit_available & (odt_skims['DRV_EXP_WLK_TOTIVT']/100>0) & (dot_skims['WLK_EXP_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_EXP_WLK_KEYIVT']/100 + dot_skims['WLK_EXP_DRV_KEYIVT']/100)>0)
-#,drive_heavyrail_available,drive_transit_available & (odt_skims['DRV_HVY_WLK_TOTIVT']/100>0) & (dot_skims['WLK_HVY_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_HVY_WLK_KEYIVT']/100 + dot_skims['WLK_HVY_DRV_KEYIVT']/100)>0)
-#,drive_lrf_available,drive_transit_available & (odt_skims['DRV_LRF_WLK_TOTIVT']/100>0) & (dot_skims['WLK_LRF_DRV_TOTIVT']/100>0) & ((odt_skims['DRV_LRF_WLK_KEYIVT']/100 + dot_skims['WLK_LRF_DRV_KEYIVT']/100)>0)
-#,drive_ferry_available,drive_lrf_available & ((odt_skims['DRV_LRF_WLK_FERRYIVT']/100 + dot_skims['WLK_LRF_WLK_FERRYIVT']/100)>0)
+#,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_commuter_available,walk_transit_available & (odt_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,walk_express_available,walk_transit_available & (odt_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,walk_heavyrail_available,walk_transit_available & (odt_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,walk_lrf_available,walk_transit_available & (odt_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,walk_ferry_available,walk_lrf_available & ((odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_local_available,drive_transit_available & (odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_commuter_available,drive_transit_available & (odt_skims['DRV_COM_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_COM_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_express_available,drive_transit_available & (odt_skims['DRV_EXP_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_EXP_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_heavyrail_available,drive_transit_available & (odt_skims['DRV_HVY_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_HVY_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_lrf_available,drive_transit_available & (odt_skims['DRV_LRF_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & (dot_skims['WLK_LRF_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0) & ((odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR)>0)
+#,drive_ferry_available,drive_lrf_available & ((odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR + dot_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR)>0)
 ,walk_transit_available,True
 ,drive_transit_available,True
 #,,
diff --git a/activitysim/examples/example_sandag/configs_3_zone/trip_mode_choice_annotate_trips_preprocessor.csv b/activitysim/examples/example_sandag/configs_3_zone/trip_mode_choice_annotate_trips_preprocessor.csv
index 90e1f2b19..e07c28f0b 100644
--- a/activitysim/examples/example_sandag/configs_3_zone/trip_mode_choice_annotate_trips_preprocessor.csv
+++ b/activitysim/examples/example_sandag/configs_3_zone/trip_mode_choice_annotate_trips_preprocessor.csv
@@ -81,24 +81,24 @@ dest terminal time not counted at home,_dest_terminal_time,"np.where(inbound & l
 ,sovtoll_available,odt_skims['SOVTOLL_VTOLL']>0
 ,hov2toll_available,odt_skims['HOV2TOLL_VTOLL']>0
 ,hov3toll_available,odt_skims['HOV3TOLL_VTOLL']>0
-#,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/100>0)
-#,walk_lrf_available,walk_transit_available & (i_tour_mode >= 10) & (odt_skims['WLK_LRF_WLK_KEYIVT']/100>0)
-#,walk_express_available,walk_transit_available & (i_tour_mode >= 11) & (odt_skims['WLK_EXP_WLK_KEYIVT']/100>0)
-#,walk_heavyrail_available,walk_transit_available & (i_tour_mode >= 12) & (odt_skims['WLK_HVY_WLK_KEYIVT']/100>0)
-#,walk_commuter_available,walk_transit_available & (i_tour_mode >= 13) & (odt_skims['WLK_COM_WLK_KEYIVT']/100>0)
-#,drive_local_available_outbound,drive_transit_available & df.outbound & (odt_skims['DRV_LOC_WLK_TOTIVT']/100>0)
-#,drive_local_available_inbound,drive_transit_available & ~df.outbound & (odt_skims['WLK_LOC_DRV_TOTIVT']/100>0)
-#,drive_lrf_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 15) & (odt_skims['DRV_LRF_WLK_KEYIVT']/100>0)
-#,drive_lrf_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 15) & (odt_skims['WLK_LRF_DRV_KEYIVT']/100>0)
-#,drive_express_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 16) & (odt_skims['DRV_EXP_WLK_KEYIVT']/100>0)
-#,drive_express_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 16) & (odt_skims['WLK_EXP_DRV_KEYIVT']/100>0)
-#,drive_heavyrail_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 17) & (odt_skims['DRV_HVY_WLK_KEYIVT']/100>0)
-#,drive_heavyrail_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 17) & (odt_skims['WLK_HVY_DRV_KEYIVT']/100>0)
-#,drive_commuter_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 18) & (odt_skims['DRV_COM_WLK_KEYIVT']/100>0)
-#,drive_commuter_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 18) & (odt_skims['WLK_COM_DRV_KEYIVT']/100>0)
-#,walk_ferry_available,walk_lrf_available & (odt_skims['WLK_LRF_WLK_FERRYIVT']/100>0)
-#,_drive_ferry_available_outbound,drive_lrf_available_outbound & (odt_skims['DRV_LRF_WLK_FERRYIVT']/100>0)
-#,_drive_ferry_available_inbound,drive_lrf_available_inbound & (odt_skims['WLK_LRF_DRV_FERRYIVT']/100>0)
+#,walk_local_available,walk_transit_available & (odt_skims['WLK_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_lrf_available,walk_transit_available & (i_tour_mode >= 10) & (odt_skims['WLK_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_express_available,walk_transit_available & (i_tour_mode >= 11) & (odt_skims['WLK_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_heavyrail_available,walk_transit_available & (i_tour_mode >= 12) & (odt_skims['WLK_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_commuter_available,walk_transit_available & (i_tour_mode >= 13) & (odt_skims['WLK_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_local_available_outbound,drive_transit_available & df.outbound & (odt_skims['DRV_LOC_WLK_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_local_available_inbound,drive_transit_available & ~df.outbound & (odt_skims['WLK_LOC_DRV_TOTIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_lrf_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 15) & (odt_skims['DRV_LRF_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_lrf_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 15) & (odt_skims['WLK_LRF_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_express_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 16) & (odt_skims['DRV_EXP_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_express_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 16) & (odt_skims['WLK_EXP_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_heavyrail_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 17) & (odt_skims['DRV_HVY_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_heavyrail_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 17) & (odt_skims['WLK_HVY_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_commuter_available_outbound,drive_transit_available & df.outbound & (i_tour_mode >= 18) & (odt_skims['DRV_COM_WLK_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,drive_commuter_available_inbound,drive_transit_available & ~df.outbound & (i_tour_mode >= 18) & (odt_skims['WLK_COM_DRV_KEYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,walk_ferry_available,walk_lrf_available & (odt_skims['WLK_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,_drive_ferry_available_outbound,drive_lrf_available_outbound & (odt_skims['DRV_LRF_WLK_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
+#,_drive_ferry_available_inbound,drive_lrf_available_inbound & (odt_skims['WLK_LRF_DRV_FERRYIVT']/TRANSIT_SCALE_FACTOR>0)
 #,drive_ferry_available,"np.where(df.outbound, _drive_ferry_available_outbound, _drive_ferry_available_inbound)"
 #,od_dist_walk,od_skims['DISTWALK']
 #,do_dist_walk,od_skims.reverse('DISTWALK')
diff --git a/activitysim/examples/example_sandag/configs_3_zone/tvpb_accessibility_tap_tap_.csv b/activitysim/examples/example_sandag/configs_3_zone/tvpb_accessibility_tap_tap_.csv
index 160f187f8..698f2506a 100644
--- a/activitysim/examples/example_sandag/configs_3_zone/tvpb_accessibility_tap_tap_.csv
+++ b/activitysim/examples/example_sandag/configs_3_zone/tvpb_accessibility_tap_tap_.csv
@@ -5,4 +5,4 @@ Description,Target,Expression
 ,_xwait,"out_of_vehicle_wait_time_weight * los.get_tappairs3d(df.btap, df.atap, tod, 'TRN_XWAIT_FAST')"
 ,_waux,"out_of_vehicle_walk_time_weight * los.get_tappairs3d(df.btap, df.atap, tod, 'TRN_WAUX_FAST')"
 ,_outOfVehicleTime,_iwait + _xwait + _waux
-,transit_time,(_inVehicleTime + _outOfVehicleTime) / 100.0
+,transit_time,(_inVehicleTime + _outOfVehicleTime) / TRANSIT_SCALE_FACTOR
diff --git a/activitysim/examples/example_sandag/test/regress/final_1_zone_tours.csv b/activitysim/examples/example_sandag/test/regress/final_1_zone_tours.csv
index 6c4871be9..84449693e 100644
--- a/activitysim/examples/example_sandag/test/regress/final_1_zone_tours.csv
+++ b/activitysim/examples/example_sandag/test/regress/final_1_zone_tours.csv
@@ -1,72 +1,74 @@
 tour_id,person_id,tour_type,tour_type_count,tour_type_num,tour_num,tour_count,tour_category,number_of_participants,destination,origin,household_id,tdd,start,end,duration,composition,destination_logsum,tour_mode,mode_choice_logsum,atwork_subtour_frequency,parent_tour_id,stop_frequency,primary_purpose
-1359025,33146,work,1,1,1,1,mandatory,1,3131.0,3259.0,12593,11.0,5.0,16.0,11.0,,,WALK_LRF,5.332929425522752,no_subtours,,1out_3in,work
-1359066,33147,work,1,1,1,1,mandatory,1,3342.0,3259.0,12593,59.0,8.0,13.0,5.0,,,WALK_LOC,5.264068612322797,no_subtours,,0out_1in,work
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-2373841,57898,maint,1,1,1,1,atwork,1,3176.0,3278.0,20552,88.0,10.0,13.0,3.0,,11.03199025686987,DRIVEALONEFREE,-0.617424327269442,,2373857.0,0out_1in,atwork
-2373857,57898,work,1,1,1,1,mandatory,1,3278.0,3746.0,20552,96.0,10.0,21.0,11.0,,,DRIVEALONEFREE,1.1036187826205084,maint,,0out_2in,work
-2373898,57899,work,1,1,1,1,mandatory,1,3398.0,3746.0,20552,47.0,7.0,17.0,10.0,,,WALK_LOC,0.9530343832374898,no_subtours,,0out_0in,work
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-2373981,57901,work,2,2,2,2,mandatory,1,3115.0,3746.0,20552,151.0,15.0,21.0,6.0,,,BIKE,1.314291228932403,no_subtours,,0out_0in,work
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-2563821,62532,escort,1,1,1,1,non_mandatory,1,3398.0,3316.0,21869,20.0,6.0,7.0,1.0,,12.499017464316038,SHARED2FREE,-1.4604154628072699,,,0out_0in,escort
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-2563863,62533,escort,3,2,2,4,non_mandatory,1,3519.0,3316.0,21869,99.0,11.0,11.0,0.0,,12.46644244899947,SHARED2FREE,-0.9326373013150777,,,0out_0in,escort
-2563864,62533,escort,3,3,3,4,non_mandatory,1,3398.0,3316.0,21869,135.0,14.0,14.0,0.0,,12.485466861656338,SHARED3FREE,-1.4467093822325976,,,0out_0in,escort
-2563878,62533,othdiscr,1,1,4,4,non_mandatory,1,3383.0,3316.0,21869,99.0,11.0,11.0,0.0,,12.891864372541253,DRIVEALONEFREE,0.09001472929003788,,,0out_0in,othdiscr
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 2563925,62534,school,1,1,1,1,mandatory,1,3316.0,3316.0,21869,55.0,8.0,9.0,1.0,,,SHARED3FREE,0.4282867689528016,,,0out_1in,school
-2787968,67999,escort,1,1,1,2,non_mandatory,1,3410.0,3378.0,23619,124.0,13.0,13.0,0.0,,12.955551071457819,TNC_SINGLE,-0.5513480266074263,,,0out_2in,escort
-2787995,67999,social,1,1,2,2,non_mandatory,1,3400.0,3378.0,23619,165.0,17.0,20.0,3.0,,11.998372378167705,WALK,0.882911292796106,,,0out_0in,social
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 2788039,68000,work,1,1,1,1,mandatory,1,3375.0,3378.0,23619,50.0,7.0,20.0,13.0,,,WALK,0.6308240193619252,no_subtours,,0out_0in,work
 3238088,78977,school,1,1,1,1,mandatory,1,3339.0,3339.0,26897,44.0,7.0,14.0,7.0,,,WALK,2.7965374977721846,,,0out_0in,school
-52627721,1283602,work,1,1,1,1,mandatory,1,3410.0,3315.0,435012,64.0,8.0,18.0,10.0,,,WALK_LOC,4.425988113191916,no_subtours,,0out_0in,work
-52638594,1283868,eatout,1,1,1,1,non_mandatory,1,3314.0,3314.0,435278,172.0,18.0,21.0,3.0,,11.416403433450883,WALK,1.465324908192731,,,0out_0in,eatout
-52638611,1283868,maint,1,1,1,1,atwork,1,3176.0,3176.0,435278,154.0,16.0,16.0,0.0,,19.27905315079715,WALK,0.6803915404396673,,52638627.0,0out_0in,atwork
-52638627,1283868,work,1,1,1,1,mandatory,1,3176.0,3314.0,435278,79.0,9.0,18.0,9.0,,,DRIVEALONEFREE,-1.239612462446479,maint,,0out_1in,work
-52641825,1283946,work,1,1,1,1,mandatory,1,3619.0,3315.0,435356,48.0,7.0,18.0,11.0,,,TNC_SINGLE,5.484377744730576,no_subtours,,0out_0in,work
-52668557,1284598,work,1,1,1,1,mandatory,1,3464.0,3261.0,436008,79.0,9.0,18.0,9.0,,,DRIVEALONEFREE,0.23420271313164437,no_subtours,,0out_0in,work
-52734854,1286215,work,1,1,1,1,mandatory,1,3176.0,3317.0,437625,66.0,8.0,20.0,12.0,,,BIKE,5.650579292236645,no_subtours,,0out_0in,work
-52897577,1290184,shopping,2,1,1,2,non_mandatory,1,3131.0,3195.0,441594,71.0,9.0,10.0,1.0,,11.509381396876263,SHARED2FREE,-0.2342783075628714,,,0out_0in,shopping
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-52915670,1290626,eat,1,1,1,1,atwork,1,3340.0,3502.0,442036,86.0,10.0,11.0,1.0,,18.51181220560061,SHARED2FREE,-0.6360145356022849,,52915705.0,0out_0in,atwork
-52915705,1290626,work,1,1,1,1,mandatory,1,3502.0,3278.0,442036,64.0,8.0,18.0,10.0,,,WALK_LOC,0.11787689080245267,eat,,1out_0in,work
-76379130,1862905,othdiscr,1,1,1,1,non_mandatory,1,3460.0,3598.0,721960,151.0,15.0,21.0,6.0,,12.84104064319134,WALK,0.5544063596844908,,,0out_0in,othdiscr
-76379171,1862906,othdiscr,1,1,1,1,non_mandatory,1,3705.0,3598.0,721960,104.0,11.0,16.0,5.0,,12.88162617984734,WALK,0.7629838626803708,,,0out_0in,othdiscr
-80946571,1974306,othdiscr,1,1,1,1,non_mandatory,1,3176.0,3396.0,760593,59.0,8.0,13.0,5.0,,13.423159321287732,SHARED3FREE,-0.008633124487292226,,,0out_0in,othdiscr
-80946591,1974307,eat,1,1,1,1,atwork,1,3410.0,3176.0,760593,113.0,12.0,13.0,1.0,,19.366291432708355,TNC_SINGLE,-1.1897672915385515,,80946626.0,0out_0in,atwork
-80946626,1974307,work,1,1,1,1,mandatory,1,3176.0,3396.0,760593,79.0,9.0,18.0,9.0,,,WALK_LOC,-0.11609915951322775,eat,,1out_1in,work
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-81048440,1976791,escort,1,1,1,1,non_mandatory,1,3314.0,3281.0,761445,124.0,13.0,13.0,0.0,,12.689095144894772,SHARED2FREE,-0.8229389285404712,,,0out_0in,escort
-81048476,1976792,eat,1,1,1,1,atwork,1,3176.0,3176.0,761445,85.0,10.0,10.0,0.0,,19.43138006432662,DRIVEALONEFREE,0.6823981998609486,,81048511.0,0out_0in,atwork
-81048497,1976792,othdiscr,1,1,1,1,non_mandatory,1,3398.0,3281.0,761445,137.0,14.0,16.0,2.0,,12.91733770206193,DRIVEALONEFREE,0.45467384830158697,,,0out_0in,othdiscr
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-81130429,1978790,work,1,1,1,1,mandatory,1,3574.0,3598.0,762159,63.0,8.0,17.0,9.0,,,DRIVEALONEFREE,-0.14446096760223584,no_subtours,,0out_0in,work
-81130470,1978791,work,1,1,1,1,mandatory,1,3176.0,3598.0,762159,47.0,7.0,17.0,10.0,,,SHARED2FREE,-0.9916042051953946,no_subtours,,0out_0in,work
-102419958,2498047,school,1,1,1,1,mandatory,1,3340.0,3383.0,922602,77.0,9.0,16.0,7.0,,,WALK_LRF,4.963760447469427,,,0out_0in,school
-102420007,2498048,work,1,1,1,1,mandatory,1,3378.0,3383.0,922602,46.0,7.0,16.0,9.0,,,WALK,1.8550633432520427,no_subtours,,0out_0in,work
-102420048,2498049,work,1,1,1,1,mandatory,1,3115.0,3383.0,922602,29.0,6.0,16.0,10.0,,,WALK_LRF,1.3290778428425043,no_subtours,,0out_0in,work
-107509903,2622192,school,1,1,1,1,mandatory,1,3375.0,3505.0,952720,44.0,7.0,14.0,7.0,,,WALK,0.5494221161414429,,,0out_0in,school
-107509922,2622193,escort,1,1,1,2,non_mandatory,1,3376.0,3505.0,952720,19.0,6.0,6.0,0.0,,12.847613841897209,SHARED2FREE,-0.7373049086600619,,,0out_0in,escort
-107509941,2622193,othmaint,1,1,2,2,non_mandatory,1,3176.0,3505.0,952720,59.0,8.0,13.0,5.0,,12.535008296435375,SHARED2FREE,-0.415217533028431,,,0out_0in,othmaint
-107509987,2622194,shopping,1,1,1,1,non_mandatory,1,3131.0,3505.0,952720,75.0,9.0,14.0,5.0,,11.86062363278129,TAXI,-0.5943569758756476,,,0out_0in,shopping
-107510034,2622195,work,1,1,1,1,mandatory,1,3343.0,3505.0,952720,63.0,8.0,17.0,9.0,,,DRIVEALONEFREE,0.6459860283103909,no_subtours,,0out_0in,work
-116640406,2844887,work,1,1,1,1,mandatory,1,3464.0,3597.0,1028031,108.0,11.0,20.0,9.0,,,WALK,5.997890402080344,no_subtours,,0out_0in,work
-120287676,2933845,school,1,1,1,1,mandatory,1,3536.0,3134.0,1048898,122.0,12.0,22.0,10.0,,,SHARED3FREE,-1.0940025666989204,,,0out_0in,school
-120287717,2933846,school,1,1,1,1,mandatory,1,3536.0,3134.0,1048898,62.0,8.0,16.0,8.0,,,SHARED2FREE,-1.1275676916322641,,,0out_0in,school
-120287752,2933847,othdiscr,1,1,1,1,non_mandatory,1,3272.0,3134.0,1048898,42.0,7.0,12.0,5.0,,12.771420325209561,SHARED2FREE,0.5634771825641499,,,0out_1in,othdiscr
-120287807,2933848,work,1,1,1,1,mandatory,1,3536.0,3134.0,1048898,31.0,6.0,18.0,12.0,,,DRIVEALONEFREE,0.03695049800770855,no_subtours,,0out_1in,work
+52627721,1283602,work,1,1,1,1,mandatory,1,3410.0,3315.0,435012,64.0,8.0,18.0,10.0,,,DRIVEALONEFREE,-0.600552076704748,no_subtours,,0out_1in,work
+52638594,1283868,eatout,1,1,1,1,non_mandatory,1,3314.0,3314.0,435278,172.0,18.0,21.0,3.0,,11.417188649277556,WALK,1.465324908192731,,,0out_0in,eatout
+52638611,1283868,maint,1,1,1,1,atwork,1,3176.0,3176.0,435278,154.0,16.0,16.0,0.0,,19.272682099619168,WALK,0.6803915404396673,,52638627.0,0out_0in,atwork
+52638627,1283868,work,1,1,1,1,mandatory,1,3176.0,3314.0,435278,79.0,9.0,18.0,9.0,,,DRIVEALONEFREE,-1.2414138285222474,maint,,0out_1in,work
+52641825,1283946,work,1,1,1,1,mandatory,1,3619.0,3315.0,435356,48.0,7.0,18.0,11.0,,,TNC_SINGLE,-0.2085333227470863,no_subtours,,0out_0in,work
+52668557,1284598,work,1,1,1,1,mandatory,1,3464.0,3261.0,436008,79.0,9.0,18.0,9.0,,,DRIVEALONEFREE,-0.1035644293674547,no_subtours,,0out_0in,work
+52734819,1286215,eat,1,1,1,1,atwork,1,3176.0,3176.0,437625,88.0,10.0,13.0,3.0,,19.30442083196423,WALK,0.6365738436949087,,52734854.0,0out_0in,atwork
+52734854,1286215,work,1,1,1,1,mandatory,1,3176.0,3317.0,437625,65.0,8.0,19.0,11.0,,,DRIVEALONEFREE,-1.216142661769996,eat,,0out_2in,work
+52897577,1290184,shopping,2,1,1,2,non_mandatory,1,3131.0,3195.0,441594,71.0,9.0,10.0,1.0,,11.507230007796329,SHARED2FREE,-0.2424171251277307,,,0out_0in,shopping
+52897578,1290184,shopping,2,2,2,2,non_mandatory,1,3131.0,3195.0,441594,154.0,16.0,16.0,0.0,,11.519310381558869,WALK,-0.2459444422249825,,,0out_0in,shopping
+52897583,1290184,work,1,1,1,1,mandatory,1,3176.0,3195.0,441594,91.0,10.0,16.0,6.0,,,DRIVEALONEFREE,-0.4742431906622577,no_subtours,,0out_0in,work
+52915670,1290626,eat,1,1,1,1,atwork,1,3340.0,3502.0,442036,86.0,10.0,11.0,1.0,,18.513981739804255,BIKE,14.60281456532542,,52915705.0,0out_1in,atwork
+52915705,1290626,work,1,1,1,1,mandatory,1,3502.0,3278.0,442036,64.0,8.0,18.0,10.0,,,BIKE,-0.0288128226314909,eat,,0out_2in,work
+76379130,1862905,othdiscr,1,1,1,1,non_mandatory,1,3460.0,3598.0,721960,151.0,15.0,21.0,6.0,,12.841187222979508,WALK,0.5769914886883216,,,0out_0in,othdiscr
+76379171,1862906,othdiscr,1,1,1,1,non_mandatory,1,3705.0,3598.0,721960,104.0,11.0,16.0,5.0,,12.884342308539214,WALK,0.7912388057447584,,,0out_0in,othdiscr
+80946571,1974306,othdiscr,1,1,1,1,non_mandatory,1,3176.0,3396.0,760593,59.0,8.0,13.0,5.0,,13.385057255164831,SHARED2FREE,-0.2639203430422295,,,0out_0in,othdiscr
+80946591,1974307,eat,1,1,1,1,atwork,1,3574.0,3316.0,760593,113.0,12.0,13.0,1.0,,18.535862390079988,TNC_SINGLE,-1.395417499795803,,80946626.0,0out_0in,atwork
+80946626,1974307,work,1,1,1,1,mandatory,1,3316.0,3396.0,760593,78.0,9.0,17.0,8.0,,,SHARED2FREE,-0.1094760736283397,eat,,1out_1in,work
+80946637,1974308,escort,1,1,1,1,non_mandatory,1,3315.0,3396.0,760593,0.0,5.0,5.0,0.0,,12.64221480734466,WALK,-0.4993149033005503,,,0out_0in,escort
+81048440,1976791,escort,1,1,1,1,non_mandatory,1,3314.0,3281.0,761445,124.0,13.0,13.0,0.0,,12.689453354918568,SHARED2FREE,-0.8229389480344289,,,0out_0in,escort
+81048476,1976792,eat,1,1,1,1,atwork,1,3176.0,3176.0,761445,85.0,10.0,10.0,0.0,,19.43069515696065,DRIVEALONEFREE,0.6823981998609486,,81048511.0,0out_0in,atwork
+81048497,1976792,othdiscr,1,1,1,1,non_mandatory,1,3398.0,3281.0,761445,137.0,14.0,16.0,2.0,,12.916929977944218,DRIVEALONEFREE,0.4546141474460643,,,0out_0in,othdiscr
+81048511,1976792,work,1,1,1,1,mandatory,1,3176.0,3281.0,761445,9.0,5.0,14.0,9.0,,,DRIVEALONEFREE,-0.6065542396018551,eat,,0out_0in,work
+81130344,1978788,social,1,1,1,1,non_mandatory,1,3498.0,3598.0,762159,66.0,8.0,20.0,12.0,,11.919599153230113,SHARED3FREE,0.5693977967774873,,,0out_0in,social
+81130399,1978790,escort,1,1,1,1,non_mandatory,1,3410.0,3598.0,762159,54.0,8.0,8.0,0.0,,12.580660633126431,SHARED2FREE,-0.7876904915091273,,,0out_0in,escort
+81130429,1978790,work,1,1,1,1,mandatory,1,3574.0,3598.0,762159,63.0,8.0,17.0,9.0,,,DRIVEALONEFREE,-0.1419369306489097,no_subtours,,0out_0in,work
+81130470,1978791,work,1,1,1,1,mandatory,1,3176.0,3598.0,762159,47.0,7.0,17.0,10.0,,,SHARED2FREE,-0.9914397742001736,no_subtours,,0out_0in,work
+102419958,2498047,school,1,1,1,1,mandatory,1,3340.0,3383.0,922602,76.0,9.0,15.0,6.0,,,WALK_LRF,2.873022403355501,,,0out_0in,school
+102420007,2498048,work,1,1,1,1,mandatory,1,3383.0,3383.0,922602,46.0,7.0,16.0,9.0,,,WALK,2.281344345550102,no_subtours,,0out_0in,work
+102420048,2498049,work,1,1,1,1,mandatory,1,3115.0,3383.0,922602,29.0,6.0,16.0,10.0,,,BIKE,0.5927455937959631,no_subtours,,0out_0in,work
+107509903,2622192,school,1,1,1,1,mandatory,1,3378.0,3505.0,952720,44.0,7.0,14.0,7.0,,,WALK,-0.2639461480591949,,,0out_0in,school
+107509922,2622193,escort,1,1,1,2,non_mandatory,1,3376.0,3505.0,952720,19.0,6.0,6.0,0.0,,12.84512392061393,SHARED2FREE,-0.7469201256899531,,,0out_0in,escort
+107509941,2622193,othmaint,1,1,2,2,non_mandatory,1,3176.0,3505.0,952720,59.0,8.0,13.0,5.0,,12.428456977574594,DRIVEALONEFREE,-0.748210620713289,,,0out_0in,othmaint
+107509987,2622194,shopping,1,1,1,1,non_mandatory,1,3131.0,3505.0,952720,75.0,9.0,14.0,5.0,,11.82505917210944,TNC_SINGLE,-0.6891536748380889,,,0out_0in,shopping
+107510034,2622195,work,1,1,1,1,mandatory,1,3363.0,3505.0,952720,63.0,8.0,17.0,9.0,,,DRIVEALONEFREE,0.3860087172282153,no_subtours,,0out_0in,work
+116640406,2844887,work,1,1,1,1,mandatory,1,3497.0,3597.0,1028031,107.0,11.0,19.0,8.0,,,DRIVEALONEFREE,0.1107975465014056,no_subtours,,0out_1in,work
+120287676,2933845,school,1,1,1,1,mandatory,1,3536.0,3134.0,1048898,122.0,12.0,22.0,10.0,,,SHARED3FREE,-1.0938793779365912,,,0out_0in,school
+120287717,2933846,school,1,1,1,1,mandatory,1,3536.0,3134.0,1048898,62.0,8.0,16.0,8.0,,,SHARED2FREE,-1.1274402981153004,,,0out_0in,school
+120287752,2933847,othdiscr,1,1,1,1,non_mandatory,1,3272.0,3134.0,1048898,42.0,7.0,12.0,5.0,,12.770313936483376,SHARED2FREE,0.5634771825641499,,,0out_1in,othdiscr
+120287807,2933848,work,1,1,1,1,mandatory,1,3536.0,3134.0,1048898,31.0,6.0,18.0,12.0,,,DRIVEALONEFREE,0.0371166413339574,no_subtours,,0out_1in,work
 131881533,3216622,school,1,1,1,1,mandatory,1,3112.0,3098.0,1148260,138.0,14.0,17.0,3.0,,,WALK,-0.8109781504489971,,,0out_2in,univ
diff --git a/activitysim/examples/example_sandag/test/regress/final_1_zone_trips.csv b/activitysim/examples/example_sandag/test/regress/final_1_zone_trips.csv
index 8aca2ebd4..f66d5e1aa 100644
--- a/activitysim/examples/example_sandag/test/regress/final_1_zone_trips.csv
+++ b/activitysim/examples/example_sandag/test/regress/final_1_zone_trips.csv
@@ -1,17 +1,17 @@
 trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,destination,origin,tour_id,purpose,destination_logsum,depart,trip_mode,mode_choice_logsum
-10872201,33146,12593,work,1,True,2,3176,3259,1359025,escort,15.093681329288426,5,WALK_LOC,2.904328006657637
-10872202,33146,12593,work,2,True,2,3131,3176,1359025,work,,7,WALK_LOC,0.5056658694462993
-10872205,33146,12593,work,1,False,4,3176,3131,1359025,escort,16.402647719499498,15,WALK_LOC,0.3243018717455698
-10872206,33146,12593,work,2,False,4,3176,3176,1359025,eatout,22.420532374694446,16,WALK,3.553064217858107
-10872207,33146,12593,work,3,False,4,3176,3176,1359025,escort,21.72972650150269,16,WALK,3.553064217858107
-10872208,33146,12593,work,4,False,4,3259,3176,1359025,home,,16,WALK_LOC,2.903590136713069
-10872529,33147,12593,work,1,True,1,3342,3259,1359066,work,,8,WALK_LOC,0.1375834358256688
-10872533,33147,12593,work,1,False,2,3176,3342,1359066,escort,15.929187262808913,13,WALK_LOC,-0.15708206326912194
-10872534,33147,12593,work,2,False,2,3259,3176,1359066,home,,13,WALK_LOC,2.9041286537257456
+10872201,33146,12593,work,1,True,3,3290,3259,1359025,escort,12.50569587831954,5,WALK,0.8796640848644649
+10872202,33146,12593,work,2,True,3,3317,3290,1359025,escort,12.74437072347788,7,WALK,0.7528069371143918
+10872203,33146,12593,work,3,True,3,3131,3317,1359025,work,,7,SHARED2FREE,-0.2771584910567812
+10872205,33146,12593,work,1,False,1,3259,3131,1359025,home,,16,SHARED2FREE,-0.3682899649069351
+10872529,33147,12593,work,1,True,1,3342,3259,1359066,work,,8,SHARED2FREE,0.4187992443742946
+10872533,33147,12593,work,1,False,4,3383,3342,1359066,escort,14.576775128994838,12,SHARED2FREE,0.8686143194682551
+10872534,33147,12593,work,2,False,4,3274,3383,1359066,social,13.66341661662671,13,SHARED2FREE,0.5107943560451084
+10872535,33147,12593,work,3,False,4,3340,3274,1359066,escort,14.112546915053883,13,SHARED2FREE,0.4230067105850933
+10872536,33147,12593,work,4,False,4,3259,3340,1359066,home,,13,DRIVEALONEFREE,0.2491163354013192
 11957177,36454,13797,shopping,1,True,1,3342,3134,1494647,shopping,,14,DRIVEALONEFREE,0.2941685907193185
-11957181,36454,13797,shopping,1,False,2,3574,3342,1494647,shopping,12.641799100811618,14,TAXI,-0.10899026335766256
+11957181,36454,13797,shopping,1,False,2,3574,3342,1494647,shopping,12.641799100811618,14,TAXI,-0.1089902633576625
 11957182,36454,13797,shopping,2,False,2,3134,3574,1494647,home,,14,TNC_SINGLE,-0.1841764445667141
-11957185,36454,13797,shopping,1,True,2,3402,3134,1494648,escort,17.45390698273753,16,DRIVEALONEFREE,1.2790849131748439
+11957185,36454,13797,shopping,1,True,2,3402,3134,1494648,escort,17.45390698273753,16,DRIVEALONEFREE,1.279084913174844
 11957186,36454,13797,shopping,2,True,2,3497,3402,1494648,shopping,,16,SHARED2FREE,1.520377820514991
 11957189,36454,13797,shopping,1,False,1,3134,3497,1494648,home,,16,SHARED2FREE,1.253344921201897
 11957553,36455,13797,work,1,True,1,3317,3134,1494694,work,,7,WALK,0.5467805012552107
@@ -22,111 +22,119 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 13679573,41706,15777,atwork,1,False,1,3398,3131,1709946,work,,17,SHARED2FREE,1.565177581330629
 13679881,41706,15777,work,1,True,1,3398,3342,1709985,work,,8,DRIVEALONEFREE,0.229309200564582
 13679885,41706,15777,work,1,False,2,3317,3398,1709985,escort,12.99906661478402,18,DRIVEALONEFREE,0.3635288368935579
-13679886,41706,15777,work,2,False,2,3342,3317,1709985,home,,19,WALK,0.19920388273033734
-16411529,50035,18261,eatout,1,True,1,3397,3493,2051441,eatout,,14,WALK,0.12625935411606823
-16411533,50035,18261,eatout,1,False,1,3493,3397,2051441,home,,14,WALK,0.15242482702152813
-16411649,50035,18261,social,1,True,1,3497,3493,2051456,social,,15,SHARED3FREE,0.5161004433004338
-16411653,50035,18261,social,1,False,4,3398,3497,2051456,social,12.435752373363133,17,SHARED3FREE,0.6235491283373512
-16411654,50035,18261,social,2,False,4,3259,3398,2051456,social,13.109363614679568,17,SHARED3FREE,0.10863108474424804
-16411655,50035,18261,social,3,False,4,3315,3259,2051456,othmaint,12.178850689443042,18,TAXI,0.6223635901533645
-16411656,50035,18261,social,4,False,4,3493,3315,2051456,home,,18,WALK,0.2709747664598304
-16411729,50035,18261,school,1,True,1,3340,3493,2051466,school,,7,WALK_LRF,1.4696656344321337
-16411733,50035,18261,school,1,False,1,3493,3340,2051466,home,,13,WALK_LRF,1.4689853433575488
-16412449,50037,18261,work,1,True,1,3314,3493,2051556,work,,7,DRIVEALONEFREE,-0.0810500687411067
-16412453,50037,18261,work,1,False,1,3493,3314,2051556,home,,13,DRIVEALONEFREE,-0.07951757122976569
+13679886,41706,15777,work,2,False,2,3342,3317,1709985,home,,19,WALK,0.1992038827303373
+16411649,50035,18261,social,1,True,1,3497,3493,2051456,social,,15,SHARED2FREE,0.8144179602536189
+16411653,50035,18261,social,1,False,3,3398,3497,2051456,social,13.607997193750748,16,SHARED2FREE,0.9055182726514672
+16411654,50035,18261,social,2,False,3,3259,3398,2051456,social,14.227902019942242,16,SHARED2FREE,0.4816403510255787
+16411655,50035,18261,social,3,False,3,3493,3259,2051456,home,,16,TAXI,0.4624895573096613
+16411729,50035,18261,school,1,True,1,3340,3493,2051466,school,,7,SHARED3FREE,-0.3581378319265033
+16411733,50035,18261,school,1,False,1,3493,3340,2051466,home,,12,DRIVEALONEFREE,-0.7018451340834048
+16411745,50035,18261,shopping,1,True,1,3396,3493,2051468,shopping,,18,DRIVEALONEFREE,0.2675492794224116
+16411749,50035,18261,shopping,1,False,1,3493,3396,2051468,home,,21,DRIVEALONEFREE,0.2641141398041625
+16412073,50036,18261,shopping,1,True,1,3497,3493,2051509,shopping,,11,WALK,0.3815001484705561
+16412077,50036,18261,shopping,1,False,2,3378,3497,2051509,escort,12.868283363745013,11,DRIVEALONEFREE,-0.1609182250241023
+16412078,50036,18261,shopping,2,False,2,3493,3378,2051509,home,,11,DRIVEALONEFREE,-0.2842450511223511
+16412449,50037,18261,work,1,True,1,3396,3493,2051556,work,,7,DRIVEALONEFREE,0.2543385882925606
+16412453,50037,18261,work,1,False,1,3493,3396,2051556,home,,14,DRIVEALONEFREE,0.2544109368585356
 18151113,55338,19758,school,1,True,1,3592,3592,2268889,school,,7,WALK,-0.5037709043643227
 18151117,55338,19758,school,1,False,1,3592,3592,2268889,home,,10,WALK,-0.5037709043643227
-18151505,55339,19758,work,1,True,1,3497,3592,2268938,work,,5,WALK,-0.03916734678520527
-18151509,55339,19758,work,1,False,1,3592,3497,2268938,home,,16,WALK,-0.039161801335005776
+18151505,55339,19758,work,1,True,1,3497,3592,2268938,work,,5,WALK,-0.0391673467852052
+18151509,55339,19758,work,1,False,1,3592,3497,2268938,home,,16,WALK,-0.0391618013350057
 18990529,57897,20552,work,1,True,1,3176,3746,2373816,work,,7,DRIVEALONEFREE,-0.8320971690146864
-18990533,57897,20552,work,1,False,1,3746,3176,2373816,home,,20,DRIVEALONEFREE,-1.0379874213845641
-18990729,57898,20552,atwork,1,True,1,3176,3278,2373841,atwork,,10,WALK,0.6526827067858828
-18990733,57898,20552,atwork,1,False,2,3176,3176,2373841,eatout,17.593313947504814,13,WALK,2.65285618245215
-18990734,57898,20552,atwork,2,False,2,3278,3176,2373841,work,,13,DRIVEALONEFREE,0.8671513659982285
-18990857,57898,20552,work,1,True,1,3278,3746,2373857,work,,10,DRIVEALONEFREE,-0.3107965939702929
-18990861,57898,20552,work,1,False,3,3849,3278,2373857,escort,11.89535523798524,20,DRIVEALONEFREE,-0.2760277005262499
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 649043761,1978791,762159,work,1,True,1,3176,3598,81130470,work,,7,DRIVEALONEFREE,-0.0843772599901702
 649043765,1978791,762159,work,1,False,1,3598,3176,81130470,home,,17,SHARED2FREE,-0.3190406065799127
-819359665,2498047,922602,school,1,True,1,3340,3383,102419958,school,,9,WALK_LRF,1.6706161179735755
-819359669,2498047,922602,school,1,False,1,3383,3340,102419958,home,,16,WALK_LRF,1.6700244897917944
-819360057,2498048,922602,work,1,True,1,3378,3383,102420007,work,,7,WALK,-0.13456278597486782
-819360061,2498048,922602,work,1,False,1,3383,3378,102420007,home,,16,WALK,-0.13456831014826334
-819360385,2498049,922602,work,1,True,1,3115,3383,102420048,work,,6,WALK_LRF,-0.08360445355178359
-819360389,2498049,922602,work,1,False,1,3383,3115,102420048,home,,16,WALK_LRF,-0.05921629297972695
-860079225,2622192,952720,school,1,True,1,3375,3505,107509903,school,,7,WALK,0.0964808201354442
-860079229,2622192,952720,school,1,False,1,3505,3375,107509903,home,,14,WALK,0.09647983156011154
+819359665,2498047,922602,school,1,True,1,3340,3383,102419958,school,,9,WALK,0.0009173412871742
+819359669,2498047,922602,school,1,False,1,3383,3340,102419958,home,,15,WALK_LRF,0.0131918923923682
+819360057,2498048,922602,work,1,True,1,3383,3383,102420007,work,,7,WALK,0.6883532259078515
+819360061,2498048,922602,work,1,False,1,3383,3383,102420007,home,,16,WALK,0.688353222623592
+819360385,2498049,922602,work,1,True,1,3115,3383,102420048,work,,6,BIKE,-1.6833752824565824
+819360389,2498049,922602,work,1,False,1,3383,3115,102420048,home,,16,BIKE,-1.406426614368767
+860079225,2622192,952720,school,1,True,1,3378,3505,107509903,school,,7,WALK,-0.3024781465081771
+860079229,2622192,952720,school,1,False,1,3505,3378,107509903,home,,14,WALK,-0.3024751617974213
 860079377,2622193,952720,escort,1,True,1,3376,3505,107509922,escort,,6,DRIVEALONEFREE,0.5385189014110604
 860079381,2622193,952720,escort,1,False,1,3505,3376,107509922,home,,6,SHARED2FREE,0.5341382626062584
-860079529,2622193,952720,othmaint,1,True,1,3176,3505,107509941,othmaint,,8,SHARED2FREE,0.6260270503650781
-860079533,2622193,952720,othmaint,1,False,1,3505,3176,107509941,home,,13,SHARED2FREE,0.6471780282809932
-860079897,2622194,952720,shopping,1,True,1,3131,3505,107509987,shopping,,9,TNC_SINGLE,0.5884396750912873
-860079901,2622194,952720,shopping,1,False,1,3505,3131,107509987,home,,14,TNC_SINGLE,0.5045716371064428
-860080273,2622195,952720,work,1,True,1,3343,3505,107510034,work,,8,DRIVEALONEFREE,0.07283220516452811
-860080277,2622195,952720,work,1,False,1,3505,3343,107510034,home,,17,DRIVEALONEFREE,-0.026653167825918853
-933123249,2844887,1028031,work,1,True,1,3464,3597,116640406,work,,11,WALK,-0.5119594850444773
-933123253,2844887,1028031,work,1,False,1,3597,3464,116640406,home,,20,WALK,-0.5804495137233229
-962301409,2933845,1048898,school,1,True,1,3536,3134,120287676,school,,12,SHARED3FREE,-1.8253639025348933
-962301413,2933845,1048898,school,1,False,1,3134,3536,120287676,home,,22,SHARED3FREE,-1.8000359821275593
+860079529,2622193,952720,othmaint,1,True,1,3176,3505,107509941,othmaint,,8,DRIVEALONEFREE,0.4138401650211165
+860079533,2622193,952720,othmaint,1,False,1,3505,3176,107509941,home,,13,TAXI,0.4250830718473121
+860079897,2622194,952720,shopping,1,True,1,3131,3505,107509987,shopping,,9,TNC_SINGLE,0.0622325149119334
+860079901,2622194,952720,shopping,1,False,1,3505,3131,107509987,home,,14,TNC_SINGLE,-0.0694219397215716
+860080273,2622195,952720,work,1,True,1,3363,3505,107510034,work,,8,DRIVEALONEFREE,0.1605413267290312
+860080277,2622195,952720,work,1,False,1,3505,3363,107510034,home,,17,DRIVEALONEFREE,0.0796511780693144
+933123249,2844887,1028031,work,1,True,1,3497,3597,116640406,work,,11,DRIVEALONEFREE,-0.0640441703152012
+933123253,2844887,1028031,work,1,False,2,3410,3497,116640406,eatout,11.389365156532708,18,DRIVEALONEFREE,-0.2404374327805191
+933123254,2844887,1028031,work,2,False,2,3597,3410,116640406,home,,19,DRIVEALONEFREE,-0.1519509037830223
+962301409,2933845,1048898,school,1,True,1,3536,3134,120287676,school,,12,SHARED3FREE,-1.8253639025348931
+962301413,2933845,1048898,school,1,False,1,3134,3536,120287676,home,,22,SHARED3FREE,-1.800035982127559
 962301737,2933846,1048898,school,1,True,1,3536,3134,120287717,school,,8,WALK,-2.1374786293216195
 962301741,2933846,1048898,school,1,False,1,3134,3536,120287717,home,,16,SHARED2FREE,-2.1233856637960864
-962302017,2933847,1048898,othdiscr,1,True,1,3272,3134,120287752,othdiscr,,7,WALK,0.9723049345876643
+962302017,2933847,1048898,othdiscr,1,True,1,3272,3134,120287752,othdiscr,,7,WALK,0.9723049345876644
 962302021,2933847,1048898,othdiscr,1,False,2,3399,3272,120287752,eatout,14.6590717484754,12,WALK,1.2236873568553286
 962302022,2933847,1048898,othdiscr,2,False,2,3134,3399,120287752,home,,12,DRIVEALONEFREE,0.8157972936115587
 962302457,2933848,1048898,work,1,True,1,3536,3134,120287807,work,,6,DRIVEALONEFREE,-0.1804673034758373
-962302461,2933848,1048898,work,1,False,2,3460,3536,120287807,escort,12.158136904433114,17,DRIVEALONEFREE,-0.23821604547144257
+962302461,2933848,1048898,work,1,False,2,3460,3536,120287807,escort,12.158136904433114,17,DRIVEALONEFREE,-0.2382160454714425
 962302462,2933848,1048898,work,2,False,2,3134,3460,120287807,home,,18,DRIVEALONEFREE,-0.3950033708360319
 1055052265,3216622,1148260,univ,1,True,1,3112,3098,131881533,univ,,14,WALK,-1.7221539064441829
-1055052269,3216622,1148260,univ,1,False,3,3112,3112,131881533,univ,9.085902358698817,16,WALK,-0.5510518904620926
-1055052270,3216622,1148260,univ,2,False,3,3176,3112,131881533,escort,14.025105605160245,17,WALK,-0.6958229859822935
+1055052269,3216622,1148260,univ,1,False,3,3112,3112,131881533,univ,9.085902358698815,16,WALK,-0.5510518904620926
+1055052270,3216622,1148260,univ,2,False,3,3176,3112,131881533,escort,14.025105605160244,17,WALK,-0.6958229859822935
 1055052271,3216622,1148260,univ,3,False,3,3098,3176,131881533,home,,17,WALK,2.3965343775069243
diff --git a/activitysim/examples/example_sandag/test/regress/final_2_zone_tours.csv b/activitysim/examples/example_sandag/test/regress/final_2_zone_tours.csv
index 9a7f326bb..c58aab933 100644
--- a/activitysim/examples/example_sandag/test/regress/final_2_zone_tours.csv
+++ b/activitysim/examples/example_sandag/test/regress/final_2_zone_tours.csv
@@ -1,78 +1,79 @@
 tour_id,person_id,tour_type,tour_type_count,tour_type_num,tour_num,tour_count,tour_category,number_of_participants,destination,origin,household_id,tdd,start,end,duration,composition,destination_logsum,tour_mode,mode_choice_logsum,atwork_subtour_frequency,parent_tour_id,stop_frequency,primary_purpose
-1359025,33146,work,1,1,1,1,mandatory,1,1100.0,560.0,12593,24.0,6.0,11.0,5.0,,,WALK_LOC,4.992740820190236,no_subtours,,0out_1in,work
-1359066,33147,work,1,1,1,1,mandatory,1,1070.0,560.0,12593,61.0,8.0,15.0,7.0,,,WALK_LOC,5.47640669570735,no_subtours,,0out_1in,work
-1494647,36454,shopping,2,1,1,2,non_mandatory,1,723.0,580.0,13797,135.0,14.0,14.0,0.0,,11.546493666990555,DRIVEALONEFREE,0.15319089892900378,,,0out_1in,shopping
-1494648,36454,shopping,2,2,2,2,non_mandatory,1,729.0,580.0,13797,151.0,15.0,21.0,6.0,,11.568482640106433,WALK,-0.1456338005031894,,,0out_2in,shopping
-1494680,36455,othdiscr,1,1,1,1,non_mandatory,1,587.0,580.0,13797,159.0,16.0,21.0,5.0,,12.811351052170956,SHARED2FREE,0.9330192771890069,,,0out_2in,othdiscr
+1359025,33146,work,1,1,1,1,mandatory,1,1100.0,560.0,12593,13.0,5.0,18.0,13.0,,,SHARED2FREE,0.3653801991721616,no_subtours,,2out_0in,work
+1359066,33147,work,1,1,1,1,mandatory,1,1070.0,560.0,12593,59.0,8.0,13.0,5.0,,,SHARED3FREE,0.0994117679786244,no_subtours,,0out_3in,work
+1494647,36454,shopping,2,1,1,2,non_mandatory,1,723.0,580.0,13797,135.0,14.0,14.0,0.0,,11.54675919468374,DRIVEALONEFREE,0.1529407042214395,,,0out_1in,shopping
+1494648,36454,shopping,2,2,2,2,non_mandatory,1,729.0,580.0,13797,151.0,15.0,21.0,6.0,,11.568558678347042,WALK,-0.1460596676048219,,,0out_2in,shopping
+1494680,36455,othdiscr,1,1,1,1,non_mandatory,1,587.0,580.0,13797,159.0,16.0,21.0,5.0,,12.81165575629481,SHARED2FREE,0.9330192771890068,,,0out_2in,othdiscr
 1494694,36455,work,1,1,1,1,mandatory,1,555.0,580.0,13797,58.0,8.0,12.0,4.0,,,WALK,0.438267562530625,no_subtours,,0out_0in,work
-1709911,41705,eatout,1,1,1,1,non_mandatory,1,1070.0,645.0,15777,76.0,9.0,15.0,6.0,,12.00167567675964,SHARED2FREE,-0.46063888593474556,,,0out_0in,eatout
-1709946,41706,business,1,1,1,1,atwork,1,1070.0,712.0,15777,116.0,12.0,16.0,4.0,,18.5810914509117,SHARED3FREE,-1.0620273595158904,,1709985.0,0out_0in,atwork
-1709985,41706,work,1,1,1,1,mandatory,1,712.0,645.0,15777,65.0,8.0,19.0,11.0,,,DRIVEALONEFREE,0.650607886600058,business1,,0out_1in,work
-2051441,50035,eatout,1,1,1,1,non_mandatory,1,746.0,757.0,18261,127.0,13.0,16.0,3.0,,11.57244574656017,WALK,1.1730869449073673,,,0out_0in,eatout
-2051448,50035,eatout,1,1,1,1,joint,3,999.0,757.0,18261,156.0,16.0,18.0,2.0,mixed,11.621816598406262,BIKE,-4.147719279635277,,,0out_2in,eatout
-2051466,50035,school,1,1,1,1,mandatory,1,919.0,757.0,18261,43.0,7.0,13.0,6.0,,,WALK_EXP,0.021538313983639704,,,0out_0in,school
-2051556,50037,work,1,1,1,1,mandatory,1,1070.0,757.0,18261,46.0,7.0,16.0,9.0,,,WALK_LRF,0.1212167759990911,no_subtours,,0out_0in,work
+1709911,41705,eatout,1,1,1,1,non_mandatory,1,1070.0,645.0,15777,76.0,9.0,15.0,6.0,,11.958812988658847,SHARED2FREE,-0.7287326640119223,,,0out_0in,eatout
+1709946,41706,business,1,1,1,1,atwork,1,1070.0,712.0,15777,116.0,12.0,16.0,4.0,,18.56981131689576,SHARED2FREE,-1.1732310040119578,,1709985.0,0out_0in,atwork
+1709985,41706,work,1,1,1,1,mandatory,1,712.0,645.0,15777,65.0,8.0,19.0,11.0,,,DRIVEALONEFREE,0.4605169952714734,business1,,0out_1in,work
+2051448,50035,eatout,1,1,1,1,joint,3,986.0,757.0,18261,156.0,16.0,18.0,2.0,mixed,11.523078896520504,BIKE,-4.315590233974143,,,0out_1in,eatout
+2051466,50035,school,1,1,1,1,mandatory,1,919.0,757.0,18261,43.0,7.0,13.0,6.0,,,SHARED3FREE,-1.4990945285645794,,,0out_0in,school
+2051468,50035,shopping,1,1,1,1,non_mandatory,1,991.0,757.0,18261,175.0,19.0,19.0,0.0,,11.42312659118132,DRIVEALONEFREE,-0.497433560680673,,,0out_0in,shopping
+2051504,50036,othmaint,1,1,1,1,non_mandatory,1,874.0,757.0,18261,44.0,7.0,14.0,7.0,,12.121531465064445,DRIVEALONEFREE,-0.2081441870570267,,,0out_0in,othmaint
+2051556,50037,work,1,1,1,1,mandatory,1,1070.0,757.0,18261,46.0,7.0,16.0,9.0,,,DRIVEALONEFREE,-1.2594160646317012,no_subtours,,0out_0in,work
 2268889,55338,school,1,1,1,1,mandatory,1,699.0,794.0,19758,40.0,7.0,10.0,3.0,,,BIKE,-0.8648143979597476,,,0out_0in,school
-2268938,55339,work,1,1,1,1,mandatory,1,699.0,794.0,19758,11.0,5.0,16.0,11.0,,,WALK,0.17157961837412644,no_subtours,,0out_0in,work
-2373816,57897,work,1,1,1,1,mandatory,1,1070.0,829.0,20552,50.0,7.0,20.0,13.0,,,DRIVEALONEFREE,0.9434613816902598,no_subtours,,0out_0in,work
-2373841,57898,maint,1,1,1,1,atwork,1,923.0,913.0,20552,88.0,10.0,13.0,3.0,,11.202405666783465,DRIVEALONEFREE,0.2638451507110187,,2373857.0,0out_1in,atwork
-2373857,57898,work,1,1,1,1,mandatory,1,913.0,829.0,20552,97.0,10.0,22.0,12.0,,,DRIVEALONEFREE,1.2027855646943666,maint,,0out_2in,work
-2373898,57899,work,1,1,1,1,mandatory,1,687.0,829.0,20552,47.0,7.0,17.0,10.0,,,WALK_LRF,1.6818772601019591,no_subtours,,0out_0in,work
-2373980,57901,work,2,1,1,2,mandatory,1,706.0,829.0,20552,24.0,6.0,11.0,5.0,,,BIKE,0.930628434327518,no_subtours,,0out_0in,work
-2373981,57901,work,2,2,2,2,mandatory,1,706.0,829.0,20552,148.0,15.0,18.0,3.0,,,SHARED2FREE,0.9269977868666633,no_subtours,,1out_0in,work
+2268938,55339,work,1,1,1,1,mandatory,1,699.0,794.0,19758,11.0,5.0,16.0,11.0,,,WALK,0.1715796183741264,no_subtours,,0out_0in,work
+2373816,57897,work,1,1,1,1,mandatory,1,1070.0,829.0,20552,50.0,7.0,20.0,13.0,,,DRIVEALONEFREE,-0.3033814075242954,no_subtours,,0out_0in,work
+2373857,57898,work,1,1,1,1,mandatory,1,913.0,829.0,20552,102.0,11.0,14.0,3.0,,,DRIVEALONEFREE,0.5102304832959351,no_subtours,,0out_0in,work
+2373898,57899,work,1,1,1,1,mandatory,1,687.0,829.0,20552,47.0,7.0,17.0,10.0,,,WALK,1.2941088699931569,no_subtours,,0out_0in,work
+2373980,57901,work,2,1,1,2,mandatory,1,706.0,829.0,20552,24.0,6.0,11.0,5.0,,,SHARED2FREE,0.5267612467815088,no_subtours,,0out_0in,work
+2373981,57901,work,2,2,2,2,mandatory,1,706.0,829.0,20552,148.0,15.0,18.0,3.0,,,DRIVEALONEFREE,0.5171713294052263,no_subtours,,1out_0in,work
 2563802,62531,school,1,1,1,1,mandatory,1,938.0,900.0,21869,180.0,20.0,20.0,0.0,,,SHARED3FREE,-0.5831759151226724,,,0out_0in,school
-2563821,62532,escort,1,1,1,1,non_mandatory,1,647.0,900.0,21869,20.0,6.0,7.0,1.0,,12.514106025827692,SHARED2FREE,-1.286443043101258,,,0out_0in,escort
-2563862,62533,escort,3,1,1,4,non_mandatory,1,695.0,900.0,21869,1.0,5.0,6.0,1.0,,12.556774848881231,SHARED3FREE,-1.2677737648720784,,,0out_3in,escort
-2563863,62533,escort,3,2,2,4,non_mandatory,1,518.0,900.0,21869,99.0,11.0,11.0,0.0,,12.489882430779174,SHARED2FREE,-1.6806379499549269,,,0out_0in,escort
-2563864,62533,escort,3,3,3,4,non_mandatory,1,844.0,900.0,21869,135.0,14.0,14.0,0.0,,12.522428851988876,SHARED3FREE,-1.4301638123863791,,,0out_0in,escort
-2563878,62533,othdiscr,1,1,4,4,non_mandatory,1,1070.0,900.0,21869,100.0,11.0,12.0,1.0,,12.911626592939612,DRIVEALONEFREE,-0.12067644461343223,,,0out_0in,othdiscr
-2563925,62534,school,1,1,1,1,mandatory,1,916.0,900.0,21869,55.0,8.0,9.0,1.0,,,SHARED2FREE,-0.03968765816614382,,,0out_1in,school
-2787968,67999,escort,1,1,1,2,non_mandatory,1,767.0,973.0,23619,124.0,13.0,13.0,0.0,,12.987400853718018,TNC_SINGLE,-0.7501532775900004,,,0out_2in,escort
-2787995,67999,social,1,1,2,2,non_mandatory,1,909.0,973.0,23619,165.0,17.0,20.0,3.0,,12.08384066215117,WALK,0.806107090149921,,,0out_0in,social
-2788039,68000,work,1,1,1,1,mandatory,1,1044.0,973.0,23619,49.0,7.0,19.0,12.0,,,SHARED2FREE,-0.007467847267855256,no_subtours,,1out_1in,work
+2563821,62532,escort,1,1,1,1,non_mandatory,1,647.0,900.0,21869,20.0,6.0,7.0,1.0,,12.514093908053251,SHARED2FREE,-1.2864424308629347,,,0out_0in,escort
+2563862,62533,escort,3,1,1,4,non_mandatory,1,695.0,900.0,21869,1.0,5.0,6.0,1.0,,12.556775320374928,SHARED3FREE,-1.2677737648720784,,,0out_3in,escort
+2563863,62533,escort,3,2,2,4,non_mandatory,1,518.0,900.0,21869,99.0,11.0,11.0,0.0,,12.489879701235449,SHARED2FREE,-1.680637950443967,,,0out_0in,escort
+2563864,62533,escort,3,3,3,4,non_mandatory,1,844.0,900.0,21869,135.0,14.0,14.0,0.0,,12.522412736170066,SHARED3FREE,-1.4300972456209138,,,0out_0in,escort
+2563878,62533,othdiscr,1,1,4,4,non_mandatory,1,1070.0,900.0,21869,100.0,11.0,12.0,1.0,,12.911650593748837,DRIVEALONEFREE,-0.1200993715843141,,,0out_0in,othdiscr
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 52668557,1284598,work,1,1,1,1,mandatory,1,551.0,562.0,436008,80.0,9.0,19.0,10.0,,,DRIVEALONEFREE,0.5965069673099715,no_subtours,,0out_0in,work
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-81048476,1976792,eat,1,1,1,1,atwork,1,540.0,517.0,761445,70.0,9.0,9.0,0.0,,18.065032209797042,DRIVEALONEFREE,0.33497110493504234,,81048511.0,0out_0in,atwork
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 102420007,2498048,work,1,1,1,1,mandatory,1,722.0,730.0,922602,46.0,7.0,16.0,9.0,,,WALK,2.055671714033067,no_subtours,,0out_0in,work
-102420048,2498049,work,1,1,1,1,mandatory,1,763.0,730.0,922602,29.0,6.0,16.0,10.0,,,BIKE,2.2091489400460276,no_subtours,,0out_0in,work
-107509903,2622192,school,1,1,1,1,mandatory,1,992.0,1025.0,952720,44.0,7.0,14.0,7.0,,,WALK,0.45587295883932566,,,0out_0in,school
-107509922,2622193,escort,1,1,1,2,non_mandatory,1,773.0,1025.0,952720,19.0,6.0,6.0,0.0,,12.866904432169989,SHARED2FREE,-0.7001189540955738,,,0out_0in,escort
-107509941,2622193,othmaint,1,1,2,2,non_mandatory,1,550.0,1025.0,952720,61.0,8.0,15.0,7.0,,12.56502298286147,DRIVEALONEFREE,-0.07186683243895249,,,0out_0in,othmaint
-107509987,2622194,shopping,1,1,1,1,non_mandatory,1,989.0,1025.0,952720,72.0,9.0,11.0,2.0,,11.929269758100192,WALK_LRF,0.611855928520119,,,0out_0in,shopping
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+107509922,2622193,escort,1,1,1,2,non_mandatory,1,773.0,1025.0,952720,19.0,6.0,6.0,0.0,,12.864427008033694,SHARED2FREE,-0.7023079893536955,,,0out_0in,escort
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 107510034,2622195,work,1,1,1,1,mandatory,1,1021.0,1025.0,952720,63.0,8.0,17.0,9.0,,,DRIVEALONEFREE,0.5725252120237364,no_subtours,,0out_0in,work
-116640406,2844887,work,1,1,1,1,mandatory,1,821.0,846.0,1028031,109.0,11.0,21.0,10.0,,,WALK,6.09342476610226,no_subtours,,0out_0in,work
-120287676,2933845,school,1,1,1,1,mandatory,1,563.0,574.0,1048898,121.0,12.0,21.0,9.0,,,WALK,0.06746422642459422,,,0out_0in,school
-120287717,2933846,school,1,1,1,1,mandatory,1,515.0,574.0,1048898,62.0,8.0,16.0,8.0,,,SHARED2FREE,-1.1032044609164289,,,0out_0in,school
-120287752,2933847,othdiscr,1,1,1,1,non_mandatory,1,623.0,574.0,1048898,42.0,7.0,12.0,5.0,,12.842403586034807,DRIVEALONEFREE,0.13341511843310172,,,0out_1in,othdiscr
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+120287717,2933846,school,1,1,1,1,mandatory,1,515.0,574.0,1048898,62.0,8.0,16.0,8.0,,,SHARED2FREE,-1.10324431187674,,,0out_0in,school
+120287752,2933847,othdiscr,1,1,1,1,non_mandatory,1,623.0,574.0,1048898,42.0,7.0,12.0,5.0,,12.842166431288351,DRIVEALONEFREE,0.1313944840147255,,,0out_1in,othdiscr
 120287807,2933848,work,1,1,1,1,mandatory,1,502.0,574.0,1048898,31.0,6.0,18.0,12.0,,,DRIVEALONEFREE,0.2481327510805355,no_subtours,,0out_1in,work
 131881533,3216622,school,1,1,1,1,mandatory,1,1074.0,1076.0,1148260,136.0,14.0,15.0,1.0,,,WALK,-0.5000951875907141,,,0out_2in,univ
diff --git a/activitysim/examples/example_sandag/test/regress/final_2_zone_trips.csv b/activitysim/examples/example_sandag/test/regress/final_2_zone_trips.csv
index 4266ecd8a..f22f1c787 100644
--- a/activitysim/examples/example_sandag/test/regress/final_2_zone_trips.csv
+++ b/activitysim/examples/example_sandag/test/regress/final_2_zone_trips.csv
@@ -1,71 +1,70 @@
 trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,destination,origin,tour_id,purpose,destination_logsum,depart,trip_mode,mode_choice_logsum
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-10872205,33146,12593,work,1,False,2,638,1100,1359025,escort,13.653215787298686,11,WALK_LOC,0.2527797595546389
-10872206,33146,12593,work,2,False,2,560,638,1359025,home,,11,WALK,0.30249535512264275
-10872529,33147,12593,work,1,True,1,1070,560,1359066,work,,8,WALK_LOC,1.3454912424198129
-10872533,33147,12593,work,1,False,2,1070,1070,1359066,escort,16.695446596004093,15,WALK,2.047593682625909
-10872534,33147,12593,work,2,False,2,560,1070,1359066,home,,15,WALK_LOC,1.346486830904328
-11957177,36454,13797,shopping,1,True,1,723,580,1494647,shopping,,14,DRIVEALONEFREE,0.17959628639436204
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-11957182,36454,13797,shopping,2,False,2,580,803,1494647,home,,14,TNC_SINGLE,0.09288382465179322
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+10872203,33146,12593,work,3,True,3,1100,997,1359025,work,,7,WALK,0.82889632223554
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 11957185,36454,13797,shopping,1,True,1,729,580,1494648,shopping,,15,WALK,-1.7031016034742517
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 11957191,36454,13797,shopping,3,False,3,580,627,1494648,home,,21,WALK,0.2535949467857011
 11957441,36455,13797,othdiscr,1,True,1,587,580,1494680,othdiscr,,16,SHARED2FREE,1.0398658929316622
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 11957446,36455,13797,othdiscr,2,False,3,648,756,1494680,social,15.113132471205256,21,SHARED2FREE,0.9397952540243504
-11957447,36455,13797,othdiscr,3,False,3,580,648,1494680,home,,21,SHARED2FREE,0.9782981839701123
+11957447,36455,13797,othdiscr,3,False,3,580,648,1494680,home,,21,SHARED2FREE,0.9782981839701124
 11957553,36455,13797,work,1,True,1,555,580,1494694,work,,8,WALK,0.3634416376281795
 11957557,36455,13797,work,1,False,1,580,555,1494694,home,,12,WALK,0.3634848237755095
-13679289,41705,15777,eatout,1,True,1,1070,645,1709911,eatout,,9,DRIVEALONEFREE,0.33225829451467775
+13679289,41705,15777,eatout,1,True,1,1070,645,1709911,eatout,,9,DRIVEALONEFREE,0.3322582945146777
 13679293,41705,15777,eatout,1,False,1,645,1070,1709911,home,,15,SHARED2FREE,0.2798579035187319
-13679569,41706,15777,atwork,1,True,1,1070,712,1709946,atwork,,12,SHARED3FREE,1.9211287099796566
-13679573,41706,15777,atwork,1,False,1,712,1070,1709946,work,,16,SHARED3FREE,1.8611573942310626
-13679881,41706,15777,work,1,True,1,712,645,1709985,work,,8,DRIVEALONEFREE,0.17465241000776272
-13679885,41706,15777,work,1,False,2,1058,712,1709985,escort,12.880657454713987,18,DRIVEALONEFREE,-0.266796751882562
+13679569,41706,15777,atwork,1,True,1,1070,712,1709946,atwork,,12,WALK,1.7140165672695504
+13679573,41706,15777,atwork,1,False,1,712,1070,1709946,work,,16,SHARED2FREE,1.656392941325861
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 13679886,41706,15777,work,2,False,2,645,1058,1709985,home,,19,DRIVEALONEFREE,-0.2819678461804502
-16411529,50035,18261,eatout,1,True,1,746,757,2051441,eatout,,13,WALK,-0.5847657002288363
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-16411729,50035,18261,school,1,True,1,919,757,2051466,school,,7,WALK_EXP,-0.38046580997674223
-16411733,50035,18261,school,1,False,1,757,919,2051466,home,,13,WALK_LOC,-0.3793432577365121
-16412449,50037,18261,work,1,True,1,1070,757,2051556,work,,7,WALK_LRF,1.7844480141935442
-16412453,50037,18261,work,1,False,1,757,1070,2051556,home,,16,WALK_LOC,1.7928643356794272
+16411585,50035,18261,eatout,1,True,1,986,757,2051448,eatout,,16,BIKE,-0.7708542602773313
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+16411733,50035,18261,school,1,False,1,757,919,2051466,home,,13,DRIVEALONEFREE,-0.609643926614725
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+16412033,50036,18261,othmaint,1,True,1,874,757,2051504,othmaint,,7,TAXI,0.188953061283284
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+16412449,50037,18261,work,1,True,1,1070,757,2051556,work,,7,DRIVEALONEFREE,-1.0310939939934904
+16412453,50037,18261,work,1,False,1,757,1070,2051556,home,,16,DRIVEALONEFREE,-1.44707562881012
 18151113,55338,19758,school,1,True,1,699,794,2268889,school,,7,BIKE,-0.4634581318660159
 18151117,55338,19758,school,1,False,1,794,699,2268889,home,,10,BIKE,-0.4634578978044055
-18151505,55339,19758,work,1,True,1,699,794,2268938,work,,5,WALK,-0.9284068498238057
-18151509,55339,19758,work,1,False,1,794,699,2268938,home,,16,WALK,-0.9284024967078643
+18151505,55339,19758,work,1,True,1,699,794,2268938,work,,5,WALK,-0.9284068498238056
+18151509,55339,19758,work,1,False,1,794,699,2268938,home,,16,WALK,-0.9284024967078645
 18990529,57897,20552,work,1,True,1,1070,829,2373816,work,,7,DRIVEALONEFREE,-0.8344257716032069
 18990533,57897,20552,work,1,False,1,829,1070,2373816,home,,20,DRIVEALONEFREE,-1.0366342786903855
-18990729,57898,20552,atwork,1,True,1,923,913,2373841,atwork,,10,DRIVEALONEFREE,-0.09070911521937304
-18990733,57898,20552,atwork,1,False,2,949,923,2373841,eatout,10.744925275565434,13,DRIVEALONEFREE,-0.31105434289520095
-18990734,57898,20552,atwork,2,False,2,913,949,2373841,work,,13,DRIVEALONEFREE,-0.3939653633830485
-18990857,57898,20552,work,1,True,1,913,829,2373857,work,,10,DRIVEALONEFREE,-0.30438642250793185
-18990861,57898,20552,work,1,False,3,716,913,2373857,escort,11.901137007662392,21,DRIVEALONEFREE,-0.06068046888397125
-18990862,57898,20552,work,2,False,3,641,716,2373857,work,12.273718845532713,22,WALK,0.18683478975390844
-18990863,57898,20552,work,3,False,3,829,641,2373857,home,,22,DRIVEALONEFREE,-0.14926372409090063
-18991185,57899,20552,work,1,True,1,687,829,2373898,work,,7,WALK_LRF,3.0095328365005356
-18991189,57899,20552,work,1,False,1,829,687,2373898,home,,17,WALK_LRF,2.959114196967946
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+18991853,57901,20552,work,1,False,1,829,706,2373981,home,,18,DRIVEALONEFREE,-0.2358241315666989
 20510417,62531,21869,school,1,True,1,938,900,2563802,school,,20,SHARED3FREE,-1.4613285433094236
 20510421,62531,21869,school,1,False,1,900,938,2563802,home,,20,WALK,-1.459500628974267
-20510569,62532,21869,escort,1,True,1,647,900,2563821,escort,,6,SHARED2FREE,0.33462552915364907
+20510569,62532,21869,escort,1,True,1,647,900,2563821,escort,,6,SHARED2FREE,0.334625529153649
 20510573,62532,21869,escort,1,False,1,900,647,2563821,home,,7,DRIVEALONEFREE,0.3206435595305147
 20510897,62533,21869,escort,1,True,1,695,900,2563862,escort,,5,SHARED3FREE,0.7144255977546087
 20510901,62533,21869,escort,1,False,4,996,695,2563862,shopping,13.914276145872222,6,SHARED3FREE,0.8532067175585919
 20510902,62533,21869,escort,2,False,4,565,996,2563862,eatout,14.470208679441688,6,SHARED3FREE,0.5414028775934869
-20510903,62533,21869,escort,3,False,4,1099,565,2563862,escort,14.893415760278991,6,SHARED2FREE,0.5359149885298558
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 20510904,62533,21869,escort,4,False,4,900,1099,2563862,home,,6,SHARED3FREE,0.8790959798947626
-20510905,62533,21869,escort,1,True,1,518,900,2563863,escort,,11,SHARED2FREE,0.02289399206874116
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 20510913,62533,21869,escort,1,True,1,844,900,2563864,escort,,14,SHARED2FREE,0.5953832095412978
 20510917,62533,21869,escort,1,False,1,900,844,2563864,home,,14,DRIVEALONEFREE,0.5982622294593943
 20511025,62533,21869,othdiscr,1,True,1,1070,900,2563878,othdiscr,,11,DRIVEALONEFREE,-0.1485066877504566
@@ -74,58 +73,63 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 20511405,62534,21869,school,1,False,2,1082,916,2563925,shopping,7.788875642915948,9,SHARED2FREE,-1.5272294838127598
 20511406,62534,21869,school,2,False,2,900,1082,2563925,home,,9,WALK,1.1927964486618703
 22303745,67999,23619,escort,1,True,1,767,973,2787968,escort,,13,TNC_SHARED,0.1443338083297466
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 22303961,67999,23619,social,1,True,1,909,973,2787995,social,,17,WALK,-0.6421177387226744
 22303965,67999,23619,social,1,False,1,973,909,2787995,home,,20,WALK,-0.6421162135547684
 22304313,68000,23619,work,1,True,2,713,973,2788039,social,13.33042668148613,7,SHARED2FREE,1.1998888948411992
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 421108889,1283868,435278,atwork,1,True,1,713,923,52638611,atwork,,16,DRIVEALONEFREE,-0.3206205769695649
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 611033369,1862906,721960,othdiscr,1,True,1,980,960,76379171,othdiscr,,11,SHARED2FREE,0.8131565075329917
@@ -133,57 +137,58 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
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 1055052265,3216622,1148260,univ,1,True,1,1074,1076,131881533,univ,,14,WALK,-1.3446315964343616
 1055052269,3216622,1148260,univ,1,False,3,1074,1074,131881533,univ,9.853996342181825,15,WALK,-0.5067482781368078
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diff --git a/activitysim/examples/example_sandag/test/regress/final_3_zone_tours.csv b/activitysim/examples/example_sandag/test/regress/final_3_zone_tours.csv
index 0a7d0d9c4..23434cccc 100644
--- a/activitysim/examples/example_sandag/test/regress/final_3_zone_tours.csv
+++ b/activitysim/examples/example_sandag/test/regress/final_3_zone_tours.csv
@@ -1,30 +1,38 @@
 tour_id,person_id,tour_type,tour_type_count,tour_type_num,tour_num,tour_count,tour_category,number_of_participants,destination,origin,household_id,tdd,start,end,duration,composition,destination_logsum,tour_mode,mode_choice_logsum,od_atap,od_btap,od_path_set,do_atap,do_btap,do_path_set,atwork_subtour_frequency,parent_tour_id,stop_frequency,primary_purpose
-1359025,33146,work,1,1,1,1,mandatory,1,1100.0,560.0,12593,12.0,5.0,17.0,12.0,,,WALK_TRANSIT,5.253186676179789,1584.0,1558.0,shortest,1558.0,1584.0,shortest,no_subtours,,1out_3in,work
-1359066,33147,work,1,1,1,1,mandatory,1,1070.0,560.0,12593,61.0,8.0,15.0,7.0,,,WALK_TRANSIT,7.357512193544526,1500.0,1558.0,fastest,1558.0,1500.0,fastest,no_subtours,,0out_1in,work
-1494647,36454,shopping,2,1,1,2,non_mandatory,1,725.0,580.0,13797,128.0,13.0,17.0,4.0,,13.601392254792993,WALK_TRANSIT,3.4613169534985735,1605.0,1238.0,shortest,1238.0,1605.0,cheapest,,,0out_0in,shopping
-1494648,36454,shopping,2,2,2,2,non_mandatory,1,739.0,580.0,13797,169.0,18.0,18.0,0.0,,13.56660835747549,WALK_TRANSIT,3.002680087780355,1662.0,1238.0,shortest,1238.0,1662.0,shortest,,,1out_0in,shopping
-1494694,36455,work,1,1,1,1,mandatory,1,562.0,580.0,13797,58.0,8.0,12.0,4.0,,,WALK_TRANSIT,6.349290419779566,1558.0,1238.0,shortest,1238.0,1558.0,shortest,no_subtours,,0out_0in,work
-1709911,41705,eatout,1,1,1,1,non_mandatory,1,1070.0,645.0,15777,76.0,9.0,15.0,6.0,,12.070246786563015,WALK_TRANSIT,0.4629895150090414,1500.0,1611.0,fastest,1611.0,1500.0,shortest,,,0out_0in,eatout
+1359025,33146,work,1,1,1,1,mandatory,1,1100.0,560.0,12593,12.0,5.0,17.0,12.0,,,DRIVEALONEFREE,1.0261372219238083,,,,,,,no_subtours,,2out_0in,work
+1359066,33147,work,1,1,1,1,mandatory,1,1070.0,560.0,12593,61.0,8.0,15.0,7.0,,,WALK_TRANSIT,2.96683804953191,1500.0,1558.0,fastest,1558.0,1500.0,fastest,no_subtours,,0out_1in,work
+1494647,36454,shopping,2,1,1,2,non_mandatory,1,725.0,580.0,13797,128.0,13.0,17.0,4.0,,11.688295162318989,DRIVEALONEFREE,0.185754815801926,,,,,,,,,0out_1in,shopping
+1494648,36454,shopping,2,2,2,2,non_mandatory,1,729.0,580.0,13797,169.0,18.0,18.0,0.0,,11.689029568940938,DRIVEALONEFREE,0.443644139698639,,,,,,,,,1out_0in,shopping
+1494680,36455,othdiscr,1,1,1,1,non_mandatory,1,623.0,580.0,13797,159.0,16.0,21.0,5.0,,13.239720693390336,SHARED2FREE,0.738377038878971,,,,,,,,,0out_2in,othdiscr
+1494694,36455,work,1,1,1,1,mandatory,1,562.0,580.0,13797,58.0,8.0,12.0,4.0,,,SHARED3FREE,0.8851264867711228,,,,,,,no_subtours,,0out_0in,work
+1709911,41705,eatout,1,1,1,1,non_mandatory,1,1070.0,645.0,15777,76.0,9.0,15.0,6.0,,12.070246786563017,WALK_TRANSIT,0.4629895150090414,1500.0,1611.0,fastest,1611.0,1500.0,shortest,,,0out_0in,eatout
 1709950,41706,eat,1,1,1,1,atwork,1,989.0,854.0,15777,112.0,12.0,12.0,0.0,,18.50954665100095,WALK_TRANSIT,-0.6180823333381719,1666.0,1662.0,shortest,1748.0,1618.0,fastest,,1709985.0,0out_0in,atwork
 1709985,41706,work,1,1,1,1,mandatory,1,854.0,645.0,15777,65.0,8.0,19.0,11.0,,,SHARED2FREE,0.613674174636675,,,,,,,eat,,0out_1in,work
-2051441,50035,eatout,1,1,1,1,non_mandatory,1,756.0,757.0,18261,127.0,13.0,16.0,3.0,,11.799526229988642,WALK,1.6563404449848542,,,,,,,,,0out_0in,eatout
 2051448,50035,eatout,1,1,1,1,joint,3,1070.0,757.0,18261,156.0,16.0,18.0,2.0,mixed,11.85828127629614,SHARED3FREE,-5.832306485220664,,,,,,,,,1out_0in,eatout
-2051466,50035,school,1,1,1,1,mandatory,1,919.0,757.0,18261,43.0,7.0,13.0,6.0,,,WALK_TRANSIT,1.2158966517539807,1618.0,1748.0,shortest,1748.0,1618.0,fastest,,,0out_0in,school
+2051466,50035,school,1,1,1,1,mandatory,1,919.0,757.0,18261,43.0,7.0,13.0,6.0,,,WALK_TRANSIT,1.2158966517539809,1618.0,1748.0,shortest,1748.0,1618.0,fastest,,,0out_0in,school
+2051468,50035,shopping,1,1,1,1,non_mandatory,1,996.0,757.0,18261,175.0,19.0,19.0,0.0,,11.577466521097683,DRIVEALONEFREE,-0.1846581633337935,,,,,,,,,0out_0in,shopping
+2051504,50036,othmaint,1,1,1,1,non_mandatory,1,877.0,757.0,18261,44.0,7.0,14.0,7.0,,12.412335687839308,SHARED2FREE,0.0818069109613803,,,,,,,,,0out_0in,othmaint
 2051556,50037,work,1,1,1,1,mandatory,1,1070.0,757.0,18261,46.0,7.0,16.0,9.0,,,WALK_TRANSIT,1.2858135302346076,1500.0,1651.0,shortest,1651.0,1500.0,shortest,no_subtours,,0out_0in,work
-2268889,55338,school,1,1,1,1,mandatory,1,699.0,794.0,19758,40.0,7.0,10.0,3.0,,,WALK_TRANSIT,1.4261796341422381,1608.0,1652.0,cheapest,1652.0,1608.0,fastest,,,0out_0in,school
+2268889,55338,school,1,1,1,1,mandatory,1,699.0,794.0,19758,40.0,7.0,10.0,3.0,,,WALK_TRANSIT,1.426179634142238,1608.0,1652.0,cheapest,1652.0,1608.0,fastest,,,0out_0in,school
 2268938,55339,work,1,1,1,1,mandatory,1,762.0,794.0,19758,11.0,5.0,16.0,11.0,,,DRIVEALONEFREE,0.6319219718888117,,,,,,,no_subtours,,0out_0in,work
-2373816,57897,work,1,1,1,1,mandatory,1,1070.0,829.0,20552,50.0,7.0,20.0,13.0,,,WALK_TRANSIT,1.8152536207268481,1500.0,1754.0,fastest,1754.0,1500.0,shortest,no_subtours,,0out_0in,work
+2373816,57897,work,1,1,1,1,mandatory,1,1070.0,829.0,20552,50.0,7.0,20.0,13.0,,,WALK_TRANSIT,1.815253620726848,1500.0,1754.0,fastest,1754.0,1500.0,shortest,no_subtours,,0out_0in,work
 2373818,57898,business,1,1,1,1,atwork,1,948.0,948.0,20552,101.0,11.0,13.0,2.0,,10.856328670591866,WALK,1.0849001811607144,,,,,,,,2373857.0,1out_0in,atwork
-2373857,57898,work,1,1,1,1,mandatory,1,948.0,829.0,20552,105.0,11.0,17.0,6.0,,,DRIVEALONEFREE,0.22661990599461826,,,,,,,business1,,0out_1in,work
+2373857,57898,work,1,1,1,1,mandatory,1,948.0,829.0,20552,105.0,11.0,17.0,6.0,,,DRIVEALONEFREE,0.2266199059946182,,,,,,,business1,,0out_1in,work
 2373898,57899,work,1,1,1,1,mandatory,1,687.0,829.0,20552,47.0,7.0,17.0,10.0,,,WALK,1.4925958516365831,,,,,,,no_subtours,,0out_0in,work
 2373980,57901,work,2,1,1,2,mandatory,1,708.0,829.0,20552,29.0,6.0,16.0,10.0,,,DRIVEALONEFREE,0.5654424599486602,,,,,,,no_subtours,,0out_0in,work
 2373981,57901,work,2,2,2,2,mandatory,1,708.0,829.0,20552,172.0,18.0,21.0,3.0,,,SHARED2FREE,0.7217981727639898,,,,,,,no_subtours,,1out_0in,work
-2563777,62531,eatout,1,1,1,1,non_mandatory,1,705.0,900.0,21869,149.0,15.0,19.0,4.0,,14.322466484667979,WALK,3.703010473851466,,,,,,,,,0out_0in,eatout
-2787968,67999,escort,1,1,1,2,non_mandatory,1,767.0,973.0,23619,124.0,13.0,13.0,0.0,,12.970512717862757,SHARED3FREE,-0.7145790466379958,,,,,,,,,0out_2in,escort
+2563802,62531,school,1,1,1,1,mandatory,1,938.0,900.0,21869,180.0,20.0,20.0,0.0,,,WALK_TRANSIT,1.0406873179045706,1673.0,1633.0,shortest,1633.0,1673.0,fastest,,,0out_0in,school
+2563821,62532,escort,1,1,1,1,non_mandatory,1,647.0,900.0,21869,20.0,6.0,7.0,1.0,,12.49976194812137,SHARED2FREE,-1.2299200748899617,,,,,,,,,0out_0in,escort
+2563862,62533,escort,3,1,1,4,non_mandatory,1,695.0,900.0,21869,1.0,5.0,6.0,1.0,,12.55798878217292,SHARED3FREE,-1.221458591960288,,,,,,,,,0out_3in,escort
+2563863,62533,escort,3,2,2,4,non_mandatory,1,518.0,900.0,21869,99.0,11.0,11.0,0.0,,12.502003827155296,SHARED3FREE,-1.66067049305692,,,,,,,,,0out_0in,escort
+2563864,62533,escort,3,3,3,4,non_mandatory,1,844.0,900.0,21869,135.0,14.0,14.0,0.0,,12.530459798779978,SHARED2FREE,-1.4032965315757244,,,,,,,,,0out_0in,escort
+2563878,62533,othdiscr,1,1,4,4,non_mandatory,1,1070.0,900.0,21869,100.0,11.0,12.0,1.0,,13.216136797297771,WALK_TRANSIT,1.0118533227067692,1500.0,73.0,fastest,73.0,1500.0,shortest,,,0out_0in,othdiscr
+2563925,62534,school,1,1,1,1,mandatory,1,793.0,900.0,21869,55.0,8.0,9.0,1.0,,,WALK_TRANSIT,-0.605105363231441,1748.0,73.0,shortest,73.0,1748.0,shortest,,,0out_0in,school
+2787968,67999,escort,1,1,1,2,non_mandatory,1,767.0,973.0,23619,124.0,13.0,13.0,0.0,,12.970512717862755,SHARED3FREE,-0.7145790466379958,,,,,,,,,0out_2in,escort
 2787995,67999,social,1,1,2,2,non_mandatory,1,988.0,973.0,23619,165.0,17.0,20.0,3.0,,12.777797143559908,WALK,1.394261833722182,,,,,,,,,0out_0in,social
 2788039,68000,work,1,1,1,1,mandatory,1,1070.0,973.0,23619,51.0,7.0,21.0,14.0,,,WALK_TRANSIT,1.4899770411640134,1500.0,1588.0,shortest,1588.0,1500.0,fastest,no_subtours,,1out_0in,work
 3238088,78977,school,1,1,1,1,mandatory,1,984.0,1081.0,26897,44.0,7.0,14.0,7.0,,,WALK,1.0391837359866254,,,,,,,,,0out_0in,school
-3238143,78979,eat,1,1,1,1,atwork,1,1070.0,897.0,26897,72.0,9.0,11.0,2.0,,18.50007970900582,DRIVEALONEFREE,-0.28647706051384236,,,,,,,,3238178.0,0out_0in,atwork
+3238143,78979,eat,1,1,1,1,atwork,1,1070.0,897.0,26897,72.0,9.0,11.0,2.0,,18.50007970900582,DRIVEALONEFREE,-0.2864770605138423,,,,,,,,3238178.0,0out_0in,atwork
 3238178,78979,work,1,1,1,1,mandatory,1,897.0,1081.0,26897,48.0,7.0,18.0,11.0,,,DRIVEALONEFREE,0.5747485518145101,,,,,,,eat,,0out_0in,work
 52627721,1283602,work,1,1,1,1,mandatory,1,1078.0,521.0,435012,64.0,8.0,18.0,10.0,,,WALK_TRANSIT,5.710266024459359,1584.0,1238.0,shortest,1238.0,1584.0,cheapest,no_subtours,,0out_0in,work
 52638588,1283868,business,1,1,1,1,atwork,1,1070.0,1070.0,435278,112.0,12.0,12.0,0.0,,19.38117027561944,WALK,0.6487888616012731,,,,,,,,52638627.0,0out_0in,atwork
@@ -34,37 +42,38 @@ tour_id,person_id,tour_type,tour_type_count,tour_type_num,tour_num,tour_count,to
 52668557,1284598,work,1,1,1,1,mandatory,1,553.0,562.0,436008,80.0,9.0,19.0,10.0,,,DRIVEALONEFREE,0.7312528815647517,,,,,,,no_subtours,,0out_0in,work
 52734819,1286215,eat,1,1,1,1,atwork,1,1077.0,606.0,437625,88.0,10.0,13.0,3.0,,18.149830935609163,WALK_TRANSIT,-0.8798916104770301,1500.0,1562.0,shortest,1562.0,1500.0,shortest,,52734854.0,0out_0in,atwork
 52734854,1286215,work,1,1,1,1,mandatory,1,606.0,656.0,437625,65.0,8.0,19.0,11.0,,,DRIVEALONEFREE,0.8985332322364314,,,,,,,eat,,0out_2in,work
-52897548,1290184,eat,1,1,1,1,atwork,1,1100.0,977.0,441594,88.0,10.0,13.0,3.0,,18.564890217266726,DRIVEALONEFREE,0.2802460620432638,,,,,,,,52897583.0,1out_0in,atwork
-52897572,1290184,othmaint,3,1,1,3,non_mandatory,1,540.0,1096.0,441594,0.0,5.0,5.0,0.0,,12.744589144842791,DRIVEALONEFREE,-0.268246760515124,,,,,,,,,0out_0in,othmaint
-52897573,1290184,othmaint,3,2,2,3,non_mandatory,1,1070.0,1096.0,441594,55.0,8.0,9.0,1.0,,12.758662199493308,SHARED3FREE,0.303683655557905,,,,,,,,,0out_0in,othmaint
-52897574,1290184,othmaint,3,3,3,3,non_mandatory,1,1070.0,1096.0,441594,70.0,9.0,9.0,0.0,,12.758874480929563,BIKE,0.3595692972928397,,,,,,,,,0out_0in,othmaint
-52897583,1290184,work,1,1,1,1,mandatory,1,977.0,1096.0,441594,82.0,9.0,21.0,12.0,,,DRIVEALONEFREE,-0.04238204929920889,,,,,,,eat,,0out_1in,work
+52897544,1290184,business,1,1,1,1,atwork,1,732.0,977.0,441594,99.0,11.0,11.0,0.0,,18.610370946991612,SHARED2FREE,0.4316303329603235,,,,,,,,52897583.0,0out_0in,atwork
+52897550,1290184,eatout,1,1,4,4,non_mandatory,1,949.0,1096.0,441594,184.0,21.0,21.0,0.0,,11.904706692046382,SHARED2FREE,-0.1665710953231831,,,,,,,,,0out_1in,eatout
+52897569,1290184,othdiscr,3,1,1,4,non_mandatory,1,684.0,1096.0,441594,2.0,5.0,7.0,2.0,,12.918529902113356,DRIVEALONEFREE,0.2317787046274241,,,,,,,,,0out_0in,othdiscr
+52897570,1290184,othdiscr,3,2,2,4,non_mandatory,1,762.0,1096.0,441594,185.0,21.0,22.0,1.0,,12.959861282775266,WALK_TRANSIT,0.2522845990878585,1748.0,1516.0,fastest,1516.0,1748.0,fastest,,,0out_0in,othdiscr
+52897571,1290184,othdiscr,3,3,3,4,non_mandatory,1,725.0,1096.0,441594,189.0,23.0,23.0,0.0,,13.001363665570665,WALK,0.3854413463230495,,,,,,,,,0out_0in,othdiscr
+52897583,1290184,work,1,1,1,1,mandatory,1,977.0,1096.0,441594,82.0,9.0,21.0,12.0,,,DRIVEALONEFREE,-0.0423820492992088,,,,,,,business1,,0out_1in,work
 52915705,1290626,work,1,1,1,1,mandatory,1,1070.0,1100.0,442036,64.0,8.0,18.0,10.0,,,WALK_TRANSIT,1.4095982213888998,1500.0,1584.0,cheapest,1584.0,1500.0,fastest,no_subtours,,1out_0in,work
-76379130,1862905,othdiscr,1,1,1,1,non_mandatory,1,986.0,960.0,721960,151.0,15.0,21.0,6.0,,12.957346522442645,WALK_TRANSIT,0.32125226609019847,1618.0,1762.0,fastest,1762.0,1618.0,fastest,,,0out_0in,othdiscr
+76379130,1862905,othdiscr,1,1,1,1,non_mandatory,1,986.0,960.0,721960,151.0,15.0,21.0,6.0,,12.957346522442643,WALK_TRANSIT,0.3212522660901984,1618.0,1762.0,fastest,1762.0,1618.0,fastest,,,0out_0in,othdiscr
 76379171,1862906,othdiscr,1,1,1,1,non_mandatory,1,992.0,960.0,721960,104.0,11.0,16.0,5.0,,12.9976638956563,SHARED3FREE,0.3134675853717786,,,,,,,,,0out_1in,othdiscr
 80946571,1974306,othdiscr,1,1,1,1,non_mandatory,1,564.0,509.0,760593,62.0,8.0,16.0,8.0,,13.57415728090829,WALK,1.2942555315594169,,,,,,,,,0out_0in,othdiscr
-80946591,1974307,eat,1,1,1,1,atwork,1,913.0,739.0,760593,113.0,12.0,13.0,1.0,,18.622653002301586,SHARED3FREE,-0.7672328773497228,,,,,,,,80946626.0,0out_0in,atwork
+80946591,1974307,eat,1,1,1,1,atwork,1,913.0,739.0,760593,113.0,12.0,13.0,1.0,,18.622653002301583,SHARED3FREE,-0.7672328773497228,,,,,,,,80946626.0,0out_0in,atwork
 80946626,1974307,work,1,1,1,1,mandatory,1,739.0,509.0,760593,79.0,9.0,18.0,9.0,,,WALK_TRANSIT,0.6201259698287482,1748.0,1603.0,fastest,1665.0,1662.0,cheapest,eat,,1out_1in,work
-80946637,1974308,escort,1,1,1,1,non_mandatory,1,716.0,509.0,760593,0.0,5.0,5.0,0.0,,12.671799977139083,SHARED3FREE,-0.8180421450990675,,,,,,,,,0out_0in,escort
-81048440,1976791,escort,1,1,1,1,non_mandatory,1,908.0,613.0,761445,124.0,13.0,13.0,0.0,,12.820991913739821,SHARED2FREE,-0.9528167859302505,,,,,,,,,0out_0in,escort
+80946637,1974308,escort,1,1,1,1,non_mandatory,1,716.0,509.0,760593,0.0,5.0,5.0,0.0,,12.671799977139084,SHARED3FREE,-0.8180421450990675,,,,,,,,,0out_0in,escort
+81048440,1976791,escort,1,1,1,1,non_mandatory,1,908.0,613.0,761445,124.0,13.0,13.0,0.0,,12.82099191373982,SHARED2FREE,-0.9528167859302504,,,,,,,,,0out_0in,escort
 81048476,1976792,eat,1,1,1,1,atwork,1,517.0,517.0,761445,70.0,9.0,9.0,0.0,,17.910037480926228,SHARED2FREE,0.7181216397530412,,,,,,,,81048511.0,0out_0in,atwork
 81048478,1976792,eatout,1,1,1,1,non_mandatory,1,648.0,613.0,761445,130.0,13.0,19.0,6.0,,11.955235691700665,DRIVEALONEFREE,1.3804088714164349,,,,,,,,,0out_0in,eatout
 81048511,1976792,work,1,1,1,1,mandatory,1,517.0,613.0,761445,7.0,5.0,12.0,7.0,,,WALK_TRANSIT,0.5051019359212883,1681.0,1238.0,fastest,1238.0,1681.0,fastest,eat,,0out_0in,work
 81130344,1978788,social,1,1,1,1,non_mandatory,1,763.0,961.0,762159,66.0,8.0,20.0,12.0,,12.393316604403664,SHARED2FREE,1.1233925360416968,,,,,,,,,0out_0in,social
 81130399,1978790,escort,1,1,1,1,non_mandatory,1,992.0,961.0,762159,54.0,8.0,8.0,0.0,,12.58022321361327,SHARED2FREE,-0.9361958649826466,,,,,,,,,0out_0in,escort
 81130429,1978790,work,1,1,1,1,mandatory,1,672.0,961.0,762159,63.0,8.0,17.0,9.0,,,DRIVEALONEFREE,0.7319548477569705,,,,,,,no_subtours,,0out_0in,work
-81130470,1978791,work,1,1,1,1,mandatory,1,1070.0,961.0,762159,47.0,7.0,17.0,10.0,,,WALK_TRANSIT,1.2232315365174313,1500.0,1762.0,shortest,1762.0,1500.0,shortest,no_subtours,,0out_0in,work
+81130470,1978791,work,1,1,1,1,mandatory,1,1070.0,961.0,762159,47.0,7.0,17.0,10.0,,,WALK_TRANSIT,1.223231536517431,1500.0,1762.0,shortest,1762.0,1500.0,shortest,no_subtours,,0out_0in,work
 102419958,2498047,school,1,1,1,1,mandatory,1,865.0,730.0,922602,77.0,9.0,16.0,7.0,,,WALK_TRANSIT,4.515115660099912,1698.0,1608.0,shortest,1608.0,1698.0,shortest,,,0out_0in,school
 102420007,2498048,work,1,1,1,1,mandatory,1,735.0,730.0,922602,46.0,7.0,16.0,9.0,,,WALK_TRANSIT,2.37613290143943,1592.0,1612.0,shortest,1612.0,1592.0,shortest,no_subtours,,0out_0in,work
 102420048,2498049,work,1,1,1,1,mandatory,1,763.0,730.0,922602,29.0,6.0,16.0,10.0,,,WALK,2.522839906360249,,,,,,,no_subtours,,0out_0in,work
 107509903,2622192,school,1,1,1,1,mandatory,1,995.0,1025.0,952720,44.0,7.0,14.0,7.0,,,WALK_TRANSIT,0.7240925397746193,1664.0,1666.0,fastest,1666.0,1664.0,fastest,,,0out_0in,school
-107509922,2622193,escort,1,1,1,2,non_mandatory,1,773.0,1025.0,952720,19.0,6.0,6.0,0.0,,12.840047018957563,SHARED3FREE,-0.7318852867656347,,,,,,,,,0out_0in,escort
-107509941,2622193,othmaint,1,1,2,2,non_mandatory,1,550.0,1025.0,952720,61.0,8.0,15.0,7.0,,12.867502750182359,WALK_TRANSIT,0.3002279969733954,1238.0,1666.0,fastest,1666.0,1238.0,cheapest,,,0out_0in,othmaint
+107509922,2622193,escort,1,1,1,2,non_mandatory,1,773.0,1025.0,952720,19.0,6.0,6.0,0.0,,12.840047018957565,SHARED3FREE,-0.7318852867656347,,,,,,,,,0out_0in,escort
+107509941,2622193,othmaint,1,1,2,2,non_mandatory,1,550.0,1025.0,952720,61.0,8.0,15.0,7.0,,12.86750275018236,WALK_TRANSIT,0.3002279969733954,1238.0,1666.0,fastest,1666.0,1238.0,cheapest,,,0out_0in,othmaint
 107509987,2622194,shopping,1,1,1,1,non_mandatory,1,989.0,1025.0,952720,72.0,9.0,11.0,2.0,,11.974087902319576,SHARED3FREE,0.5678792550825605,,,,,,,,,0out_0in,shopping
 107510034,2622195,work,1,1,1,1,mandatory,1,1021.0,1025.0,952720,63.0,8.0,17.0,9.0,,,DRIVEALONEFREE,0.8640931880479102,,,,,,,no_subtours,,0out_0in,work
-116640406,2844887,work,1,1,1,1,mandatory,1,845.0,846.0,1028031,111.0,11.0,23.0,12.0,,,TNC_SINGLE,6.579157199539979,,,,,,,no_subtours,,0out_1in,work
-120287676,2933845,school,1,1,1,1,mandatory,1,666.0,574.0,1048898,121.0,12.0,21.0,9.0,,,WALK,-0.007445252449514138,,,,,,,,,0out_0in,school
+116640406,2844887,work,1,1,1,1,mandatory,1,845.0,846.0,1028031,111.0,11.0,23.0,12.0,,,WALK_TRANSIT,0.9802398468480144,1730.0,1695.0,shortest,1695.0,1730.0,cheapest,no_subtours,,0out_0in,work
+120287676,2933845,school,1,1,1,1,mandatory,1,666.0,574.0,1048898,121.0,12.0,21.0,9.0,,,WALK,-0.0074452524495141,,,,,,,,,0out_0in,school
 120287717,2933846,school,1,1,1,1,mandatory,1,515.0,574.0,1048898,62.0,8.0,16.0,8.0,,,SHARED2FREE,-1.016021399976598,,,,,,,,,0out_0in,school
-120287752,2933847,othdiscr,1,1,1,1,non_mandatory,1,657.0,574.0,1048898,42.0,7.0,12.0,5.0,,13.002449945790438,WALK_TRANSIT,0.8636594074657713,1238.0,1559.0,shortest,1559.0,1238.0,shortest,,,0out_1in,othdiscr
-120287807,2933848,work,1,1,1,1,mandatory,1,502.0,574.0,1048898,31.0,6.0,18.0,12.0,,,WALK_TRANSIT,0.38857733727947175,1333.0,1559.0,fastest,1559.0,1333.0,fastest,no_subtours,,0out_0in,work
-131881533,3216622,school,1,1,1,1,mandatory,1,1074.0,1076.0,1148260,136.0,14.0,15.0,1.0,,,WALK_TRANSIT,10.725339744357893,1500.0,1516.0,fastest,1516.0,1500.0,fastest,,,0out_1in,univ
+120287752,2933847,othdiscr,1,1,1,1,non_mandatory,1,657.0,574.0,1048898,42.0,7.0,12.0,5.0,,13.002449945790438,WALK_TRANSIT,0.8636594074657715,1238.0,1559.0,shortest,1559.0,1238.0,shortest,,,0out_1in,othdiscr
+120287807,2933848,work,1,1,1,1,mandatory,1,502.0,574.0,1048898,31.0,6.0,18.0,12.0,,,WALK_TRANSIT,0.3885773372794717,1333.0,1559.0,fastest,1559.0,1333.0,fastest,no_subtours,,0out_0in,work
+131881533,3216622,school,1,1,1,1,mandatory,1,1074.0,1076.0,1148260,136.0,14.0,15.0,1.0,,,WALK_TRANSIT,10.725339744357893,1500.0,1516.0,fastest,1516.0,1500.0,fastest,,,0out_0in,univ
diff --git a/activitysim/examples/example_sandag/test/regress/final_3_zone_trips.csv b/activitysim/examples/example_sandag/test/regress/final_3_zone_trips.csv
index 6d04bc125..03a015e70 100644
--- a/activitysim/examples/example_sandag/test/regress/final_3_zone_trips.csv
+++ b/activitysim/examples/example_sandag/test/regress/final_3_zone_trips.csv
@@ -1,20 +1,23 @@
 trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,destination,origin,tour_id,purpose,destination_logsum,depart,trip_mode,mode_choice_logsum,atap,btap,path_set
-10872201,33146,12593,work,1,True,2,791,560,1359025,escort,17.78862021819126,5,WALK_TRANSIT,1.076240180821363,1748.0,1558.0,shortest
-10872202,33146,12593,work,2,True,2,1100,791,1359025,work,,7,SHARED2FREE,1.323546666937803,,,
-10872205,33146,12593,work,1,False,4,515,1100,1359025,escort,18.443152309342498,16,TAXI,0.9940444731258395,,,
-10872206,33146,12593,work,2,False,4,536,515,1359025,eatout,18.04646259905213,17,BIKE,1.5072057797522642,,,
-10872207,33146,12593,work,3,False,4,672,536,1359025,escort,18.8509937537178,17,SHARED2FREE,1.45242139445582,,,
-10872208,33146,12593,work,4,False,4,560,672,1359025,home,,17,WALK_TRANSIT,1.9107495509585688,1558.0,1333.0,shortest
-10872529,33147,12593,work,1,True,1,1070,560,1359066,work,,8,WALK_TRANSIT,2.7379934634249263,1500.0,1558.0,shortest
-10872533,33147,12593,work,1,False,2,995,1070,1359066,escort,19.304294035594243,15,SHARED2FREE,1.7167528830202354,,,
-10872534,33147,12593,work,2,False,2,560,995,1359066,home,,15,SHARED2FREE,1.2449334998555297,,,
-11957177,36454,13797,shopping,1,True,1,725,580,1494647,shopping,,13,WALK_TRANSIT,1.4450301070637832,1605.0,1238.0,fastest
-11957181,36454,13797,shopping,1,False,1,580,725,1494647,home,,17,WALK_TRANSIT,1.965213626430132,1238.0,1605.0,shortest
-11957185,36454,13797,shopping,1,True,2,687,580,1494648,escort,21.455782988843794,18,WALK_TRANSIT,4.827028844466682,1748.0,1562.0,fastest
-11957186,36454,13797,shopping,2,True,2,739,687,1494648,shopping,,18,BIKE,2.6679630470987634,,,
-11957189,36454,13797,shopping,1,False,1,580,739,1494648,home,,18,WALK_TRANSIT,2.0871839076409286,1238.0,1662.0,shortest
-11957553,36455,13797,work,1,True,1,562,580,1494694,work,,8,WALK_TRANSIT,2.135658438923573,1558.0,1562.0,cheapest
-11957557,36455,13797,work,1,False,1,580,562,1494694,home,,12,BIKE,1.9570590317256964,,,
+10872201,33146,12593,work,1,True,3,879,560,1359025,escort,11.70885284520791,5,DRIVEALONEFREE,-0.3548746577733072,,,
+10872202,33146,12593,work,2,True,3,989,879,1359025,escort,12.022433281644073,7,DRIVEALONEFREE,-0.361684345054043,,,
+10872203,33146,12593,work,3,True,3,1100,989,1359025,work,,7,DRIVEALONEFREE,0.1801428827020189,,,
+10872205,33146,12593,work,1,False,1,560,1100,1359025,home,,17,DRIVEALONEFREE,-0.368339088809198,,,
+10872529,33147,12593,work,1,True,1,1070,560,1359066,work,,8,WALK_TRANSIT,2.7567263588191,1500.0,1558.0,shortest
+10872533,33147,12593,work,1,False,2,942,1070,1359066,escort,19.449635104296835,15,DRIVEALONEFREE,1.4771881293112104,,,
+10872534,33147,12593,work,2,False,2,560,942,1359066,home,,15,SHARED2FREE,1.0374930881113709,,,
+11957177,36454,13797,shopping,1,True,1,725,580,1494647,shopping,,13,DRIVEALONEFREE,0.1717448995480592,,,
+11957181,36454,13797,shopping,1,False,2,803,725,1494647,shopping,12.016029658018422,17,TAXI,0.0352267728440656,,,
+11957182,36454,13797,shopping,2,False,2,580,803,1494647,home,,17,DRIVEALONEFREE,0.07359791064631,,,
+11957185,36454,13797,shopping,1,True,2,687,580,1494648,escort,13.593599471819292,18,WALK,0.7788942047635835,,,
+11957186,36454,13797,shopping,2,True,2,729,687,1494648,shopping,,18,DRIVEALONEFREE,0.489210171281661,,,
+11957189,36454,13797,shopping,1,False,1,580,729,1494648,home,,18,TAXI,0.2313076964301194,,,
+11957441,36455,13797,othdiscr,1,True,1,623,580,1494680,othdiscr,,16,DRIVEALONEFREE,0.7744647479734814,,,
+11957445,36455,13797,othdiscr,1,False,3,784,623,1494680,othmaint,15.224351954248831,21,SHARED2FREE,0.6723499661375587,,,
+11957446,36455,13797,othdiscr,2,False,3,687,784,1494680,social,14.665238994089853,21,SHARED2FREE,0.8916379345159234,,,
+11957447,36455,13797,othdiscr,3,False,3,580,687,1494680,home,,21,WALK,1.6583917720273251,,,
+11957553,36455,13797,work,1,True,1,562,580,1494694,work,,8,WALK,1.0769131864309256,,,
+11957557,36455,13797,work,1,False,1,580,562,1494694,home,,12,SHARED3FREE,1.1126409173456748,,,
 13679289,41705,15777,eatout,1,True,1,1070,645,1709911,eatout,,9,WALK_TRANSIT,3.1199845193778537,1500.0,1611.0,fastest
 13679293,41705,15777,eatout,1,False,1,645,1070,1709911,home,,15,WALK_TRANSIT,1.5023958487827092,1611.0,1500.0,shortest
 13679601,41706,15777,atwork,1,True,1,989,854,1709950,atwork,,12,WALK_TRANSIT,1.744638602675838,1618.0,1748.0,fastest
@@ -22,52 +25,69 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 13679881,41706,15777,work,1,True,1,854,645,1709985,work,,8,SHARED2FREE,0.484767983512682,,,
 13679885,41706,15777,work,1,False,2,1080,854,1709985,escort,14.795756318103102,18,SHARED2FREE,0.4510582957043532,,,
 13679886,41706,15777,work,2,False,2,645,1080,1709985,home,,19,SHARED2FREE,0.4925057974553318,,,
-16411529,50035,18261,eatout,1,True,1,756,757,2051441,eatout,,13,WALK,1.1939806545962508,,,
-16411533,50035,18261,eatout,1,False,1,757,756,2051441,home,,16,WALK,1.0513254189986925,,,
-16411585,50035,18261,eatout,1,True,2,897,757,2051448,shopping,9.847225415280661,16,SHARED3FREE,-0.8214696655451806,,,
-16411586,50035,18261,eatout,2,True,2,1070,897,2051448,eatout,,17,WALK,0.17299190819754515,,,
+16411585,50035,18261,eatout,1,True,2,897,757,2051448,shopping,9.84722541528066,16,SHARED3FREE,-0.8214696655451806,,,
+16411586,50035,18261,eatout,2,True,2,1070,897,2051448,eatout,,17,WALK,0.1729919081975451,,,
 16411589,50035,18261,eatout,1,False,1,757,1070,2051448,home,,18,SHARED3FREE,-1.5064572485047776,,,
-16411729,50035,18261,school,1,True,1,919,757,2051466,school,,7,SHARED2FREE,0.9176970231226665,,,
-16411733,50035,18261,school,1,False,1,757,919,2051466,home,,13,WALK_TRANSIT,1.0330239915909303,1748.0,1618.0,fastest
+16411729,50035,18261,school,1,True,1,919,757,2051466,school,,7,SHARED2FREE,0.9176970231226664,,,
+16411733,50035,18261,school,1,False,1,757,919,2051466,home,,13,WALK_TRANSIT,1.0330239915909305,1748.0,1618.0,fastest
+16411745,50035,18261,shopping,1,True,1,996,757,2051468,shopping,,19,DRIVEALONEFREE,-0.4672462178894699,,,
+16411749,50035,18261,shopping,1,False,1,757,996,2051468,home,,19,DRIVEALONEFREE,-0.4597066008562396,,,
+16412033,50036,18261,othmaint,1,True,1,877,757,2051504,othmaint,,7,SHARED2FREE,0.8103017184288349,,,
+16412037,50036,18261,othmaint,1,False,1,757,877,2051504,home,,14,SHARED2FREE,0.7939513107930013,,,
 16412449,50037,18261,work,1,True,1,1070,757,2051556,work,,7,DRIVEALONEFREE,2.631618309801618,,,
 16412453,50037,18261,work,1,False,1,757,1070,2051556,home,,16,WALK_TRANSIT,1.2835436251782917,1651.0,1500.0,fastest
 18151113,55338,19758,school,1,True,1,699,794,2268889,school,,7,WALK_TRANSIT,1.353066071452224,1608.0,1652.0,cheapest
 18151117,55338,19758,school,1,False,1,794,699,2268889,home,,10,SHARED2FREE,1.118204426327703,,,
-18151505,55339,19758,work,1,True,1,762,794,2268938,work,,5,DRIVEALONEFREE,-0.09751857931395859,,,
-18151509,55339,19758,work,1,False,1,794,762,2268938,home,,16,DRIVEALONEFREE,-0.00758777225194223,,,
+18151505,55339,19758,work,1,True,1,762,794,2268938,work,,5,DRIVEALONEFREE,-0.0975185793139585,,,
+18151509,55339,19758,work,1,False,1,794,762,2268938,home,,16,DRIVEALONEFREE,-0.0075877722519422,,,
 18990529,57897,20552,work,1,True,1,1070,829,2373816,work,,7,WALK_TRANSIT,2.259124587532973,1500.0,1754.0,fastest
 18990533,57897,20552,work,1,False,1,829,1070,2373816,home,,20,DRIVEALONEFREE,1.0944715206029072,,,
-18990545,57898,20552,atwork,1,True,2,948,948,2373818,othmaint,7.505984009752515,11,WALK,-0.43394566102590587,,,
-18990546,57898,20552,atwork,2,True,2,948,948,2373818,atwork,,11,WALK,-0.43394566102590587,,,
-18990549,57898,20552,atwork,1,False,1,948,948,2373818,work,,13,WALK,-0.43394566102590587,,,
+18990545,57898,20552,atwork,1,True,2,948,948,2373818,othmaint,7.505984009752515,11,WALK,-0.4339456610259058,,,
+18990546,57898,20552,atwork,2,True,2,948,948,2373818,atwork,,11,WALK,-0.4339456610259058,,,
+18990549,57898,20552,atwork,1,False,1,948,948,2373818,work,,13,WALK,-0.4339456610259058,,,
 18990857,57898,20552,work,1,True,1,948,829,2373857,work,,11,DRIVEALONEFREE,-0.4249793219573366,,,
-18990861,57898,20552,work,1,False,2,739,948,2373857,escort,11.536722530937924,17,DRIVEALONEFREE,-0.43515529700511774,,,
+18990861,57898,20552,work,1,False,2,739,948,2373857,escort,11.536722530937924,17,DRIVEALONEFREE,-0.4351552970051177,,,
 18990862,57898,20552,work,2,False,2,829,739,2373857,home,,17,DRIVEALONEFREE,-0.0991454272062134,,,
 18991185,57899,20552,work,1,True,1,687,829,2373898,work,,7,WALK,0.5220452718494769,,,
 18991189,57899,20552,work,1,False,1,829,687,2373898,home,,17,WALK,0.6195549538462863,,,
 18991841,57901,20552,work,1,True,1,708,829,2373980,work,,6,DRIVEALONEFREE,-0.2156500818117738,,,
 18991845,57901,20552,work,1,False,1,829,708,2373980,home,,16,DRIVEALONEFREE,-0.82405708338336,,,
-18991849,57901,20552,work,1,True,2,687,829,2373981,othmaint,13.312507041737813,18,WALK,1.203803918419165,,,
+18991849,57901,20552,work,1,True,2,687,829,2373981,othmaint,13.312507041737812,18,WALK,1.203803918419165,,,
 18991850,57901,20552,work,2,True,2,708,687,2373981,work,,21,SHARED2FREE,0.5645998198729414,,,
-18991853,57901,20552,work,1,False,1,829,708,2373981,home,,21,DRIVEALONEFREE,0.15388362826215857,,,
-20510217,62531,21869,eatout,1,True,1,705,900,2563777,eatout,,15,WALK,-2.961958736713177,,,
-20510221,62531,21869,eatout,1,False,1,900,705,2563777,home,,19,WALK,-2.1935851596369167,,,
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+20510417,62531,21869,school,1,True,1,938,900,2563802,school,,20,TAXI,1.0846519720828849,,,
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+20510569,62532,21869,escort,1,True,1,647,900,2563821,escort,,6,SHARED2FREE,0.335383128230131,,,
+20510573,62532,21869,escort,1,False,1,900,647,2563821,home,,7,DRIVEALONEFREE,0.3214092822815929,,,
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 22304317,68000,23619,work,1,False,1,973,1070,2788039,home,,21,WALK_TRANSIT,1.875153102901004,1588.0,1500.0,fastest
 25904705,78977,26897,school,1,True,1,984,1081,3238088,school,,7,WALK,-0.4961040893656598,,,
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 421021773,1283602,435012,work,1,False,1,521,1078,52627721,home,,18,WALK_TRANSIT,0.9194329115009408,1238.0,1584.0,shortest
 421108705,1283868,435278,atwork,1,True,1,1070,1070,52638588,atwork,,12,WALK,2.4750620100011926,,,
 421108709,1283868,435278,atwork,1,False,1,1070,1070,52638588,work,,12,WALK,2.4750620100011926,,,
@@ -78,88 +98,88 @@ trip_id,person_id,household_id,primary_purpose,trip_num,outbound,trip_count,dest
 421109021,1283868,435278,work,1,False,1,537,1070,52638627,home,,18,SHARED2FREE,1.283382912854287,,,
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 421134605,1283946,435356,work,1,False,1,523,1070,52641825,home,,19,TNC_SINGLE,1.3977246630790026,,,
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 421878553,1286215,437625,atwork,1,True,1,1077,606,52734819,atwork,,10,WALK_TRANSIT,1.186699589189828,1500.0,1562.0,cheapest
 421878557,1286215,437625,atwork,1,False,1,606,1077,52734819,work,,13,WALK_TRANSIT,1.681572479856284,1562.0,1500.0,fastest
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-423325641,1290626,442036,work,1,True,2,1070,1100,52915705,work,23.18866767080017,8,WALK_TRANSIT,2.8246315365649473,1500.0,1584.0,cheapest
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 611033045,1862905,721960,othdiscr,1,False,1,960,986,76379130,home,,21,TAXI,1.3532506038209091,,,
 611033369,1862906,721960,othdiscr,1,True,1,992,960,76379171,othdiscr,,11,SHARED3FREE,0.8858713264739554,,,
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 611033374,1862906,721960,othdiscr,2,False,2,960,551,76379171,home,,16,SHARED2FREE,0.5117735347645973,,,
-647572569,1974306,760593,othdiscr,1,True,1,564,509,80946571,othdiscr,,8,WALK,0.12477528626857051,,,
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 647572729,1974307,760593,atwork,1,True,1,913,739,80946591,atwork,,12,SHARED3FREE,2.326963701825421,,,
 647572733,1974307,760593,atwork,1,False,1,739,913,80946591,work,,13,SHARED3FREE,2.32846863119764,,,
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+647573013,1974307,760593,work,1,False,2,518,739,80946626,work,19.081960514674996,17,WALK_TRANSIT,2.9100248711462138,1681.0,1662.0,cheapest
 647573014,1974307,760593,work,2,False,2,509,518,80946626,home,,18,WALK,2.5433977364719564,,,
 647573097,1974308,760593,escort,1,True,1,716,509,80946637,escort,,5,SHARED3FREE,0.8908384736539703,,,
 647573101,1974308,760593,escort,1,False,1,509,716,80946637,home,,5,SHARED3FREE,0.8921116412562625,,,
-648387521,1976791,761445,escort,1,True,1,908,613,81048440,escort,,13,SHARED2FREE,0.43187460597514504,,,
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 648387809,1976792,761445,atwork,1,True,1,517,517,81048476,atwork,,9,WALK,3.011532825794776,,,
 648387813,1976792,761445,atwork,1,False,1,517,517,81048476,work,,9,WALK,3.011532825794776,,,
 648387825,1976792,761445,eatout,1,True,1,648,613,81048478,eatout,,13,DRIVEALONEFREE,0.4724646811902892,,,
 648387829,1976792,761445,eatout,1,False,1,613,648,81048478,home,,19,TAXI,0.5571365851477499,,,
 648388089,1976792,761445,work,1,True,1,517,613,81048511,work,,5,WALK_TRANSIT,1.796194897875614,1681.0,1238.0,cheapest
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 649042753,1978788,762159,social,1,True,1,763,961,81130344,social,,8,SHARED2FREE,0.3356357191681573,,,
 649042757,1978788,762159,social,1,False,1,961,763,81130344,home,,20,SHARED2FREE,0.3505516593935055,,,
 649043193,1978790,762159,escort,1,True,1,992,961,81130399,escort,,8,SHARED2FREE,0.5305214939922914,,,
 649043197,1978790,762159,escort,1,False,1,961,992,81130399,home,,8,SHARED2FREE,0.5188517472186277,,,
 649043433,1978790,762159,work,1,True,1,672,961,81130429,work,,8,DRIVEALONEFREE,-0.3341036694423639,,,
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 649043761,1978791,762159,work,1,True,1,1070,961,81130470,work,,7,WALK_TRANSIT,2.6922733054492127,1500.0,1762.0,fastest
 649043765,1978791,762159,work,1,False,1,961,1070,81130470,home,,17,TAXI,1.4645945681666606,,,
-819359665,2498047,922602,school,1,True,1,865,730,102419958,school,,9,TAXI,1.2028968838653513,,,
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 819360385,2498049,922602,work,1,True,1,763,730,102420048,work,,6,WALK,-0.7841986127882443,,,
 819360389,2498049,922602,work,1,False,1,730,763,102420048,home,,16,WALK,-0.8403247829423018,,,
 860079225,2622192,952720,school,1,True,1,995,1025,107509903,school,,7,TNC_SINGLE,1.737007403541493,,,
 860079229,2622192,952720,school,1,False,1,1025,995,107509903,home,,14,SHARED3FREE,1.6399355775465674,,,
-860079377,2622193,952720,escort,1,True,1,773,1025,107509922,escort,,6,SHARED3FREE,0.9453815876415103,,,
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 860079381,2622193,952720,escort,1,False,1,1025,773,107509922,home,,6,SHARED2FREE,0.9690872179986344,,,
 860079529,2622193,952720,othmaint,1,True,1,550,1025,107509941,othmaint,,8,TAXI,1.6791134568237254,,,
-860079533,2622193,952720,othmaint,1,False,1,1025,550,107509941,home,,15,WALK_TRANSIT,1.6848126498987461,1666.0,1238.0,shortest
-860079897,2622194,952720,shopping,1,True,1,989,1025,107509987,shopping,,9,WALK,1.6280881165461683,,,
+860079533,2622193,952720,othmaint,1,False,1,1025,550,107509941,home,,15,WALK_TRANSIT,1.6848126498987464,1666.0,1238.0,shortest
+860079897,2622194,952720,shopping,1,True,1,989,1025,107509987,shopping,,9,WALK,1.6280881165461685,,,
 860079901,2622194,952720,shopping,1,False,1,1025,989,107509987,home,,11,SHARED3FREE,1.5894514263370938,,,
-860080273,2622195,952720,work,1,True,1,1021,1025,107510034,work,,8,DRIVEALONEFREE,0.13076087259157862,,,
+860080273,2622195,952720,work,1,True,1,1021,1025,107510034,work,,8,DRIVEALONEFREE,0.1307608725915786,,,
 860080277,2622195,952720,work,1,False,1,1025,1021,107510034,home,,17,DRIVEALONEFREE,0.1511979688414838,,,
-933123249,2844887,1028031,work,1,True,1,845,846,116640406,work,,11,WALK,1.3386215748714405,,,
-933123253,2844887,1028031,work,1,False,2,769,845,116640406,eatout,16.31439014198426,23,WALK,1.3218750596260462,,,
-933123254,2844887,1028031,work,2,False,2,846,769,116640406,home,,23,TNC_SINGLE,1.2022721883024985,,,
-962301409,2933845,1048898,school,1,True,1,666,574,120287676,school,,12,WALK,-1.1062441750768535,,,
+933123249,2844887,1028031,work,1,True,1,845,846,116640406,work,,11,SHARED3FREE,1.662725895784853,,,
+933123253,2844887,1028031,work,1,False,1,846,845,116640406,home,,23,DRIVEALONEFREE,1.6190252500331577,,,
+962301409,2933845,1048898,school,1,True,1,666,574,120287676,school,,12,WALK,-1.1062441750768537,,,
 962301413,2933845,1048898,school,1,False,1,574,666,120287676,home,,21,WALK,-1.227339677708164,,,
 962301737,2933846,1048898,school,1,True,1,515,574,120287717,school,,8,SHARED2FREE,-2.095040038174043,,,
 962301741,2933846,1048898,school,1,False,1,574,515,120287717,home,,16,SHARED2FREE,-2.102822435414125,,,
 962302017,2933847,1048898,othdiscr,1,True,1,657,574,120287752,othdiscr,,7,WALK_TRANSIT,1.5362116862704658,1238.0,1559.0,cheapest
-962302021,2933847,1048898,othdiscr,1,False,2,1070,657,120287752,eatout,17.04052424640584,12,WALK_TRANSIT,3.4941014068165894,3.0,1238.0,shortest
+962302021,2933847,1048898,othdiscr,1,False,2,1070,657,120287752,eatout,17.04052424640584,12,WALK_TRANSIT,3.494101406816589,3.0,1238.0,shortest
 962302022,2933847,1048898,othdiscr,2,False,2,574,1070,120287752,home,,12,WALK_TRANSIT,1.3230638799617858,1559.0,1500.0,fastest
 962302457,2933848,1048898,work,1,True,1,502,574,120287807,work,,6,BIKE,1.3439545881637307,,,
 962302461,2933848,1048898,work,1,False,1,574,502,120287807,home,,18,WALK_TRANSIT,1.3169033457581467,1559.0,1333.0,shortest
 1055052265,3216622,1148260,univ,1,True,1,1074,1076,131881533,univ,,14,TAXI,0.933892780827025,,,
-1055052269,3216622,1148260,univ,1,False,2,1074,1074,131881533,univ,16.695408348525785,15,WALK,1.106944205307494,,,
-1055052270,3216622,1148260,univ,2,False,2,1076,1074,131881533,home,,15,SHARED2FREE,0.8615934658413547,,,
+1055052269,3216622,1148260,univ,1,False,1,1076,1074,131881533,home,,15,BIKE,0.8615934658413547,,,
diff --git a/activitysim/examples/example_sandag/test/test_sandag.py b/activitysim/examples/example_sandag/test/test_sandag.py
index 71313bec8..eb87c2ce2 100644
--- a/activitysim/examples/example_sandag/test/test_sandag.py
+++ b/activitysim/examples/example_sandag/test/test_sandag.py
@@ -4,6 +4,7 @@
 import subprocess
 import pkg_resources
 
+import pytest
 import pandas as pd
 import pandas.testing as pdt
 
@@ -29,8 +30,14 @@ def psrc_example_path(dirname):
     resource = os.path.join('examples', 'example_psrc', dirname)
     return pkg_resources.resource_filename('activitysim', resource)
 
+def build_data():
+    pass
 
-def test_sandag():
+@pytest.fixture(scope='module')
+def data():
+    build_data()
+
+def run_test(zone, multiprocess=False):
 
     def test_path(dirname):
         return os.path.join(os.path.dirname(__file__), dirname)
@@ -40,41 +47,65 @@ def regress(zone):
         # ## regress tours
         regress_tours_df = pd.read_csv(test_path(f'regress/final_{zone}_zone_tours.csv'))
         tours_df = pd.read_csv(test_path(f'output/final_{zone}_zone_tours.csv'))
+        tours_df.to_csv(test_path(f'regress/final_{zone}_zone_tours_last_run.csv'), index=False)
         print(f"regress tours")
-        pdt.assert_frame_equal(tours_df, regress_tours_df), "regress tours"
+        pdt.assert_frame_equal(tours_df, regress_tours_df, rtol=1e-03)
 
         # ## regress trips
         regress_trips_df = pd.read_csv(test_path(f'regress/final_{zone}_zone_trips.csv'))
         trips_df = pd.read_csv(test_path(f'output/final_{zone}_zone_trips.csv'))
+        trips_df.to_csv(test_path(f'regress/final_{zone}_zone_trips_last_run.csv'), index=False)
         print(f"regress trips")
-        pdt.assert_frame_equal(trips_df, regress_trips_df), "regress trips"
+        pdt.assert_frame_equal(trips_df, regress_trips_df, rtol=1e-03)
+
+    # run test
+    file_path = os.path.join(os.path.dirname(__file__), 'simulation.py')
+
+    if zone == '2':
+        base_configs = psrc_example_path(f'configs')
+    else:
+        base_configs = mtc_example_path(f'configs')
+
+    run_args = ['-c', test_path(f'configs_{zone}_zone'),
+                '-c', example_path(f'configs_{zone}_zone'),
+                '-c', base_configs,
+                '-d', example_path(f'data_{zone}'),
+                '-o', test_path('output')]
 
-    # run tests with and without multi processing
-    zones = ['1', '2', '3']
-    test_combos = [(z, mp) for z in zones for mp in [False, True]]
-    for test_combo in test_combos:
-        zone, multiprocess = test_combo
+    if multiprocess:
+        run_args = run_args + ['-s', 'settings_mp.yaml']
 
-        file_path = os.path.join(os.path.dirname(__file__), 'simulation.py')
+    subprocess.run(['coverage', 'run', '-a', file_path] + run_args, check=True)
 
-        if zone == '2':
-            base_configs = psrc_example_path(f'configs')
-        else:
-            base_configs = mtc_example_path(f'configs')
+    regress(zone)
 
-        run_args = ['-c', test_path(f'configs_{zone}_zone'),
-                    '-c', example_path(f'configs_{zone}_zone'),
-                    '-c', base_configs,
-                    '-d', example_path(f'data_{zone}'),
-                    '-o', test_path('output')]
+def test_1_zone(data):
+    run_test(zone='1', multiprocess=False)
 
-        if multiprocess:
-            run_args = run_args + ['-s', 'settings_mp.yaml']
+def test_1_zone_mp(data):
+    run_test(zone='1', multiprocess=True)
 
-        subprocess.run(['coverage', 'run', '-a', file_path] + run_args, check=True)
+def test_2_zone(data):
+    run_test(zone='2', multiprocess=False)
 
-        regress(zone)
+def test_2_zone_mp(data):
+    run_test(zone='2', multiprocess=True)
 
+def test_3_zone(data):
+    run_test(zone='3', multiprocess=False)
+
+def test_3_zone_mp(data):
+    run_test(zone='3', multiprocess=True)
 
 if __name__ == '__main__':
-    test_sandag()
+
+    # call each test explicitly so we get a pass/fail for each
+    build_data()
+    run_test(zone='1', multiprocess=False)
+    run_test(zone='1', multiprocess=True)
+
+    run_test(zone='2', multiprocess=False)
+    run_test(zone='2', multiprocess=True)
+
+    run_test(zone='3', multiprocess=False)
+    run_test(zone='3', multiprocess=True)
\ No newline at end of file
diff --git a/activitysim/examples/example_semcog/configs/trip_destination.yaml b/activitysim/examples/example_semcog/configs/trip_destination.yaml
index 7ea232427..1bd5b0fc6 100755
--- a/activitysim/examples/example_semcog/configs/trip_destination.yaml
+++ b/activitysim/examples/example_semcog/configs/trip_destination.yaml
@@ -15,7 +15,7 @@ DEST_CHOICE_SAMPLE_TABLE_NAME: trip_destination_sample
 # model-specific logsum-related settings
 TRIP_ORIGIN: origin
 ALT_DEST_COL_NAME: dest_taz
-PRIMARY_DEST: destination
+PRIMARY_DEST: tour_leg_dest # must be created in preprocessor
 
 REDUNDANT_TOURS_MERGED_CHOOSER_COLUMNS:
   - tour_mode
diff --git a/activitysim/examples/example_semcog/configs/trip_destination_annotate_trips_preprocessor.csv b/activitysim/examples/example_semcog/configs/trip_destination_annotate_trips_preprocessor.csv
index 0e5e80100..e4317d8e8 100755
--- a/activitysim/examples/example_semcog/configs/trip_destination_annotate_trips_preprocessor.csv
+++ b/activitysim/examples/example_semcog/configs/trip_destination_annotate_trips_preprocessor.csv
@@ -7,3 +7,4 @@ Description,Target,Expression
 #,,not needed as school is not chosen as an intermediate trip destination
 #,_grade_school,"(df.primary_purpose == 'school') & reindex(persons.is_gradeschool, df.person_id)"
 #,size_segment,"df.primary_purpose.where(df.primary_purpose != 'school', np.where(_grade_school,'gradeschool', 'highschool'))"
+,tour_leg_dest,"np.where(df.outbound,reindex(tours.destination, df.tour_id), reindex(tours.origin, df.tour_id))"
\ No newline at end of file