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2021 Regional Plan
Ziying Ouyang edited this page Oct 5, 2022
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The 2021 Regional Plan project contains SQL objects, a Python project, and a formatted Excel template. The main output product is a formatted and populated Excel workbook containing up to seven scenarios for performance measure and SB375 comparison.
To run the project
- Pull the ABM-Reporting repository from GitHub into your local environment
- Update the settings.py file located in the python\rp_2021 folder to point at the correct SQL Server instance and database containing the rp_2021 SQL objects created by the rp_2021.sql file in the sql\rp_2021 folder and the correct SQL Server instance and database containing the GIS Performance Measures table
- Update the settings.py file located in the python\rp_2021 folder with the desired full path of the formatted and populated Excel workbook (ex. templateWritePath = "C:/Users/MyUserName/Desktop/PerformanceMeasures.xlsx")
- Update the settings.py file located in the python\rp_2021 folder with the list of up to seven comparison scenarios IDs and their labels within the Regional Plan. See the settings.py file for examples and possible labels.
- Use the environment.yml file located in the python\rp_2021 folder to create the rp_2021 Python virtual environment and set as the project interpreter
- Run python\rp_2021\main.py from the top-level ABM-Reporting working directory
There is a similar Python project used to create Mobility Hub specific Access Performance Measures M1 and M5. It is run identically to the above process subbing in mainHubAccess.py for main.py using settingsMoHubAccess.py in place of settings.py. This is used to run Access Performance Measures M1 and M5 only considering origins within a specified Mobility Hub.
File | Description |
---|---|
environment.yml |
conda environment used to run rp_2021 python files |
main.py |
orchestrator file used to populate the rp_2021 Excel Workbook |
performanceMeasuresGIS.py |
class for all information and utilities relating to calculations of GIS Performance Measures SM-2, SM-3, SM-4 |
performanceMeasuresM1M5.py |
class for all information and utilities relating to calculations of Main Performance Measures M1-(a-c) and M5-(a-c) |
settings.py |
settings file used to run rp_2021 python files |
mainMoHubAccess.py |
orchestrator file used to populate Mobility Hub specific Access Measures Excel Workbook |
settingsMoHubAccess.py |
settings file used to run the Mobility Hub specific orchestrator |
File | Description |
---|---|
Performance Measures_template.xlsx |
formatted Excel template to hold output from rp_2021 scenario comparisons |
MoHubAccess_template.xlsx |
formatted Excel template to hold output from Mobility Hub specific Access Measures |
Name | Description |
---|---|
[rp_2021].[freight_distribution_hubs] |
Table of series 13 TAZs identified as freight distribution hubs |
[rp_2021].[mobility_hubs] |
Table of series 13 MGRAs identified as mobility hubs |
[rp_2021].[particulate_matter_grid] |
Table holding a representation of the San Diego region broken into a square polygon grid |
[rp_2021].[results] |
Table holding results from 2021 regional plan measures |
Name | Description |
---|---|
[rp_2021].[fn_eir_shp_qry_layer] |
query layer to create shape file for EIR |
[rp_2021].[fn_particulate_matter_ctemfac_2014] |
calculate link level particulate matter 2.5 and 10 emissions using CT-EMFAC 2014 |
[rp_2021].[fn_particulate_matter_ctemfac_2017] |
calculate link level particulate matter 2.5 and 10 emissions using CT-EMFAC 2017 |
[rp_2021].[fn_person_coc] |
ABM synthetic population with Community of Concern (CoC) designations |
[rp_2021].[fn_transit_node_tiers] |
transit stop ([near_node]/[trcov_id]) for Tier 1, Tier 2, and Tier 3 transit stops |
Name | Description |
---|---|
[rp_2021].[sp_m1_m5_destinations] |
destinations at the MGRA level used in calculations for the 2021 Regional Plan Main Performance Measures M1 and M5 |
[rp_2021].[sp_m1_m5_populations] |
population at the MGRA level used in calculations for the 2021 Regional Plan Main Performance Measures M1 and M5 |
[rp_2021].[sp_particulate_matter_ctemfac_2014] |
calculate person-level particulate matter 2.5 and 10 exposure using CT-EMFAC 2014 |
[rp_2021].[sp_particulate_matter_ctemfac_2017] |
calculate person-level particulate matter 2.5 and 10 exposure using CT-EMFAC 2017 |
[rp_2021].[sp_pm_m4] |
performance measure M-4, network VMT per capita and regionwide for a given ABM scenario |
[rp_2021].[sp_pm_sm1] |
performance measure SM-1 mode share, percent of person-trips by mode with option to filter to work purpose trips (defined as outbound work tour where the mode is determined by the SANDAG tour journey mode hierarchy) and/or to trips made in the peak period (ABM 5 TOD AM Peak and PM Peak periods) for a given ABM scenario |
[rp_2021].[sp_pm_sm10] |
performance measure SM-10, percent of household income consumed by transportation costs |
[rp_2021].[sp_pm_sm5] |
performance measure SM-5, daily transit boardings |
[rp_2021].[sp_pm_sm6_activity] |
performance measure SM-6, time engaged in transportation-related physical activity per capita (minutes) |
[rp_2021].[sp_pm_sm6_pct] |
performance measure SM-6, percent of population engaging in more than 20 minutes of daily transportation related physical activity |
[rp_2021].[sp_pm_sm7] |
performance measure SM-7, average trip travel time for commercial vehicles and trucks to/from freight distribution hubs |
[rp_2021].[sp_pm_sm9a] |
performance measure SM-9-a, truck travel time index (TTI) calculated as the summation of link-based travel time divided by free-flow time weighted by truck mode VMT |
[rp_2021].[sp_pm_sm9b] |
performance measure SM-9-b, truck delay by facility type |
[rp_2021].[sp_resident_vmt] |
San Diego resident vehicle miles traveled (VMT) at a user-determined geographic resolution. VMT is assigned to either the resident's home or work location. Optional filter to select workers only and their work purpose tour VMT. Available at any geographic resolution present in the ABM database. |
[rp_2021].[sp_sb375_auto_ownership] |
SB375 average household auto ownership |
[rp_2021].[sp_sb375_avg_headways_tier] |
SB375 average transit headways |
[rp_2021].[sp_sb375_housing_structures] |
SB375 housing structure and household metrics |
[rp_2021].[sp_sb375_jobs] |
SB375 total jobs in the San Diego region |
[rp_2021].[sp_sb375_median_income] |
SB375 median household income for a given ABM scenario |
[rp_2021].[sp_sb375_mode_measures] |
calculates a person trip based measure for ABM resident sub-models by ABM mode |
[rp_2021].[sp_sb375_population] |
SB375 total population (including institutionalized group quarters and modeled population (not including institutionalized group quarters) |
[rp_2021].[sp_sb375_seat_utilization] |
SB375 transit seat utilization for a given ABM scenario |
[rp_2021].[sp_sb375_travel_time_purpose] |
SB375 travel time by trip purpose for a given ABM scenario |