The Effect of Competition of Transport Modes on Mobility

Emerging technologies in transportation will have profound impacts on travel both within and between cities in the Unites States. Some examples of these new technologies include Uber, Zipcar, driverless vehicles, high-speed rail and hyperloop. These new technologies will enhance competition of transport modes and therefore benefit travelers by improving their mobility. Policymakers need rigorous evidence on the effects of the enhanced transport mode competition caused by new technologies on travelers’ mobility in order to prioritize transportation policies. This project will build transport mode-choice models of travelers both within and between metropolitan areas in the United States and use the models to understand travelers’ willingness-to-pay for important transport attributes such as travel time, reliability and safety. Given these parameter estimates, the project will quantify the effect of the enhanced competition on travelers’ mobility which is measured by both trip allocation and trip generation. The project will include the following two components. (1) Transport mode choice models for within-city travel. Typical transport modes for within-city travel include private driving, public transit, taxi and bicycle. The project will study how UBER services affect travelers’ mode choices. (2) Transport mode choice models for inter-city travel. The project will analyze mode choice behavior among automobile, rail and air and simulate how high-speed railway affect inter-city travel. The mode choice models will have the following important features. First, they are nested-logit models in order to account for the non-travel option, which is important to quantify the trip generation effects of new technologies. Second, they are random-parameter models in order to account for the rich heterogeneity in travelers’ preferences. Third, they can be estimated by both disaggregate and aggregate mode share data so we do not need to compile survey data all the time. Data can be used to estimate the model choice models are the National Household Transport Survey Data, which are disaggregate data, and the DB1B data, which provide market share of air travel between any two cities in the United States.

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


  • English


  • Status: Completed
  • Funding: $37267
  • 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:

    Washington State University

    PO Box 646210
    Pullman, Washington  United States  99164-6210
  • Principal Investigators:

    Yan, Jia

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

Subject/Index Terms

Filing Info

  • Accession Number: 01625946
  • 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 12:21PM