Setup

Input Files

You can download the Soundcast inputs here. This zip file in combination with the code in this repository has all the files needed to run the model. Extract the zip file to a desired workplace with at least 150 GB of free disk space. Check that the folder has full security control on your computer after unzipping, and update it to full control if not.

Inputs are made available in hierarchy by year for land use and network inputs. This allows the user to specify various alternatives for each year, and allows a combination of different land use and network combinations. In the provided 2018 input data the directory structure is as follows:

• v3.0.0
  • base_year
    • 2018
      • all base year inputs for 2018.
  • db
    • this single database file contains data for multiple years. Data is filtered based on the specified model year
  • landuse
    • 2018
      • v3.0_RTP
        • all land use data corresponding to year 2018 and the base v3.0 policies
  • networks
    • 2018
      • rtp_2018_final
        • all network data corresponding to year 2018 and the RTP assumptions

Note that in the zipped input folder an additional folder called "install" is included, which contains the latest Anaconda environment install files.

Input Configuration

The primary control configuration for typical runs is the input_configuration.py file in the root directory of the Soundcast repository. This file should be updated to identify the location of model inputs and other settings prior to running. The version checked in with releases should be otherwise configured for a base-year run, with all settings relevant to that context.

Input Paths

Near the top of input_configuration.py, ensure that following parameters are accurate and point to the proper input set. If you extracted the input file above to a folder in your C drive called "soundcast_inputs", the name of the main inputs folder should be 'C:/soundcast_inputs'. Presuming that the inputs correspond to the supplied 2018 base year data, the following settings should be applied:

model_year = '2018'
base_year = '2018'
landuse_inputs = 'v3.0_RTP'
network_inputs = 'rtp_2018_final'
soundcast_inputs_dir = 'C:/soundcast_inputs'

Model Component Control

The default setting for Soundcast is to run all model components, including

• freeflow assignment and skimming
• Daysim choice models for all simulated person-days
• global iterations between assignment and choice modeling until convergence
• truck, bike, and external trip assignment
• summaries

These components may be run or skipped individually, as defined by parameters in input_configuration.py. The default settings should not be changed to run a standard full model run. If a run is interrupted or only assignment or summary scripts need to be run, True/False statements can be used to control whether model components are executed. The following table describes the configurable parameters in input_configuration.py.

Variable	Default Setting	Description
model_year	'2018	Model year used to look up year-specific inputs
base_year	'2018'	Should be always be 2018 regardless of scenario, unless using another base year
landuse_inputs	'vers2_july2020'	Input folder name for land use scenario, nested within model_year directory of input folder
network_inputs	'current_2018'	Input folder name for network scenario, nested within model_year directory of input folder
soundcast_inputs_dir	{set to location of input data}	top-level location of input directory
run_accessibility_calcs	True	Calculate land-use and network accessibility measures from all-streets network; only needs to be performed once during model run
run_setup_emme_project_folders	True	Create empty (or overwrite existing) Emme projects at initial run setup
run_setup_emme_bank_folders	True	Create empty emmebanks at initial setup
run_copy_scenario_inputs	True	Copy input files to local soundcast directory
run_import_networks	True	Load networks to each time-of-day Emme project
run_skims_and_paths_free_flow	True	Default for Soundcast is free-flow assignment
run_skims_and_paths	True	Majority of trip assignment and skim building occurs when True
run_truck_model	True	Generate truck trips and add to network
run_supplemental_trips	True	Separately consider external and special purpose trips not considered by Daysim
run_daysim	True	Run the main activity-generation portion of the model
run_summaries	True	Run a set of network and activity summaries to produce CSV and HTML outputs
include_av	False	Model inclusion of automated vehicles
include_tnc	True	Model including of TNC/ridehailing vehicles
tnc_av	False	Allow TNCs to operate as AVs
include_tnc_to_transt	False	AV drop offs to transit
include_knr_to_Transit	False	Allow Kiss and Ride drop-offs at transit stations
include_delivery	False	Allow for additional delivery trips to neighborhoods
add_distance_pricing	False (in base year; True in future years generally)	Apply per-mile pricing
distance_rate_dict	{'am' : 13.5, 'md' : 8.5, 'pm' : 13.5, 'ev' : 8.5, 'ni' : 8.5}	Prices per mile applied when
run_integrated	False	For integration with urbansim
should_build_shadow_price	False	Drive-to-transit shadow pricing control
delete_banks	False	Method to minimize run size by removing large Emmebank data files

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