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Bike Demand Model

Work flow

Base scenario steps:

• ArcGIS export multimodal network to CSV files with headers
  • nodes, links, link shapes, transit stops
• ArcGIS export microzone system to CSV files with headers
  • zones, zone shapes, land use
• Python script reads CSV files into pandas DataFrames and store in one HDF5 data store binary file for efficient I/O
• Cube export WFRC travel model zonal data to CSV files with headers
  • zones, zone shapes, land use data
• Cube export WFRC mode choice matrices and network LOS skims to OMX files
  • trips by mode by time period
  • auto travel time matrix by time period
• Python script adds z coordinate to every x,y coordinate in the HDF5 data store
• Python script disaggregates WFRC model zone-to-zone data to microzone-to-microzone
  • using microzone land use
  • including accessibility measures from multimodal network
• Python script generates microzone-to-microzone walk and bike route costs using multimodal network

The result is microzone-to-microzone trips and route costs by mode for the base scenario.

Build scenario steps:

• User edits the multimodal network and/or microzone attribution in ArcGIS
• Runs similar data processing steps as in the base scenario:
  • ArcGIS export multimodal network to CSV files with headers
    • nodes, links, link shapes, transit stops
  • ArcGIS export microzone system to CSV files with headers
    • zones, zone shapes, land use
  • Python script reads CSV files into pandas DataFrames and store in one HDF5 data store
  • Python script adds z coordinate to every x,y coordinate in the HDF5 data store
  • Python script updates the disaggregation of WFRC model zone-to-zone data to microzone-to-microzone
    • using microzone land use
    • including accessibility measures from multimodal network
• Python script defines the area of influence for the build scenario in order to only run the route costs for a subarea to save time
• Python script generates microzone-to-microzone walk and bike route costs using multimodal network
• Python script runs incremental logit model using the trips by mode and change in bike route utility
• Python script summarizes results and returns report to ArcGIS user

The result is microzone-to-microzone trips and route costs by mode for the build scenario.