Impacts of Ridesourcing on VMT, Parking Demand, Transportation Equity, and Travel Behavior

The transportation sector is currently experiencing a monumental disruption with the introduction and evolution of transportation services such as bikesharing, carsharing, ridesharing, and on-demand ridesourcing (e.g. Lyft, Uber). Many factors – including social networks, real-time information, and mobile technology – allow passengers and drivers to connect through mobile smartphone applications (i.e. apps). In turn, this led to the creation and popularization of ridesourcing companies offering an app-based on-demand platform. As these new layers of technology-based transportation options begin to flourish, it is important to understand how they compete and interact with more traditional modes. Beyond travel behavior, these evolving transportation services can also significantly impact transportation systems, society, and the environment. Yet, these outcomes have yet to be adequately studied in the academic literature. Accordingly, this research will investigate the travel modes replaced by these evolving services and why people shifted from a previous mode. More specifically, the project team will investigate new trips that may not have occurred before (i.e. induced travel) as well as multimodality (i.e. availability of several modes) and intermodality (i.e. combination of various modes for a single trip or mixed-modes) in order to analyze the impact of these services on the overall transportation system in terms of vehicle miles traveled (VMT), parking demand, transportation equity, and travel behavior. In theory, providing a more diverse array of travel options may reduce car dependence and lower parking demand; in practice, however, there are still unresolved questions about what cities actually gain (or lose) with ridesourcing in terms of sustainability-related outcomes such as mode choice, VMT, carbon emissions, as well as transportation equity issues. For instance when replacing 2 single occupancy vehicle (SOV) trips, there is a potential for negative effects. If a person shifts from driving to ridesourcing, the ride-source driver may travel additional mileage – to pick them up or after dropping them off – than what would have been driven with the initial trip. There is also a theoretical saturation point where higher ridesourcing supply than demand leaves many drivers circulating without riders, which can cause unnecessary VMT, congestion, environmental issues, and other problems that are not yet documented with respect to these new technology-based modal options. While there is robust information online regarding companies such as Uber and Lyft, the academic literature on ridesourcing is extremely limited due to the lack of open data on these services. This research will employ a combination of revealed-behavior data and stated-response data structures collected via travel data records, travel diaries, and individual surveys using an innovative approach that combines information gathered from the Lyft/Uber driver and passenger interviews. The project team will assess the travel modes replaced by ridesourcing including new trips, multimodal trips, and intermodal trips in order to gather insights from individuals on the process of why a specific mode was selected over the alternatives. For example, what is the role of travel time, travel cost, and parking ease in the decision making process? Other measurements will include VMT impacts and equity issues with the introduction of ridesourcing in transportation systems. The project team will then be able to provide insights into the different impact levels of ridesourcing based on the characteristics of a region or a city. The project team hypothesizes that the effects on VMT, parking demand, and equity issues vary among different geographical areas (e.g. urban vs. suburban vs. rural, city size, density) and mode share distribution (e.g. the higher the driving mode share for a city the more positive effects the city will experience with ridesourcing). As a result, this research will be relevant for the region and beyond. Also, current transportation travel models focus on traditional modes of transportation (i.e. car, transit, walk, and bike), but few models appropriating take into account the impacts of ridesourcing (e.g. Lyft, Uber) (DuPuis et al., 2015). Thus, this research will also fill a gap in the literature by studying the effects of evolving services on travel behavior, which will help cities and regional transportation organizations better account for the impact of technology and evolving transportation services in their transportation planning processes.


  • English


  • Status: Completed
  • Funding: $154422
  • Contract Numbers:


  • Sponsor Organizations:

    Research and Innovative Technology Administration

    Department of Transportation
    1200 New Jersey Avneue, SE
    Washington, DC  United States  20590
  • Managing Organizations:

    Mountain-Plains Consortium

    North Dakota State University
    P.O. Box 6050, Department 2880
    Fargo, ND  United States  58108-6050
  • Project Managers:

    Kline, Robin

  • Performing Organizations:

    Dept. of Civil Engineering

    University of Colorado Denver
    Denver, CO  United States 
  • Principal Investigators:

    Marshall, Wesley

    Janson, Bruce

  • Start Date: 20160721
  • Expected Completion Date: 20190731
  • Actual Completion Date: 20190508
  • USDOT Program: University Transportation Centers Program
  • Source Data: MPC-514

Subject/Index Terms

Filing Info

  • Accession Number: 01607377
  • Record Type: Research project
  • Source Agency: Mountain-Plains Consortium
  • Contract Numbers: DTRT13-G-UTC38
  • Files: UTC, RiP
  • Created Date: Aug 2 2016 3:24PM