Forecasting Ridership for Commuter Rail in Austin

Austin Texas is one of the most rapidly growing cities in the United States. Current estimates indicate over 150 people per day are moving to Austin. To deal with the growing transportation needs, Capital Metro is proposing the addition of commuter rail services in several corridors where publicly owned rail right of way is available. Forecasting ridership for such services is problematic due to a lack of experience with access modal choices and the potential operational state of the transport system due to rapid growth. The research team has developed dynamic traffic assignment algorithm for such problems, however, it currently estimates time and cost of access in very rudimentary ways. This work will develop robust predictive tools for assessing modes used for accessing the proposed commuter rail systems. The purpose of this project is to develop the proposed models using a combination of stated preference survey data and analogies with other cities.

  • Supplemental Notes:
    • Contract to a Performing Organization has not yet been awarded.


  • English


  • Status: Completed
  • Funding: $140000
  • Contract Numbers:


  • Sponsor Organizations:

    Center for Advanced Multimodal Mobility Solutions and Education

    University of North Carolina, Charlotte
    Charlotte, NC  United States  28223
  • Managing Organizations:

    University of North Carolina, Charlotte

    Department of Civil and Environmental Engineering
    9201 University City Boulevard
    Charlotte, NC  United States  28223-0001
  • Project Managers:

    Fan, Wei

  • Performing Organizations:

    University of Texas at Austin

    Austin, TX  United States  78712
  • Principal Investigators:

    Machemehl, R

  • Start Date: 20170115
  • Expected Completion Date: 20180930
  • Actual Completion Date: 20180930

Subject/Index Terms

Filing Info

  • Accession Number: 01625943
  • Record Type: Research project
  • Source Agency: Center for Advanced Multimodal Mobility Solutions and Education
  • Contract Numbers: 69A3551747133
  • Files: UTC, RIP
  • Created Date: Feb 14 2017 12:02PM