Traffic State Prediction: A Traveler Equity and Multi-model Perspective

Traffic congestion has become one of the modern life problems in many urban areas. Urban traffic congestion has the potential to be relieved by developing tools that plan multi-mode trips to encourage more people to ride public transportation and provide better alternatives to less affluent citizens. Traffic state prediction is the key component to plan multi-mode trips in complex transportation network. This research attempts to address transportation system state prediction problems considering private vehicle, transit, and bike share services within the context of a multimodal transportation system. For public transit service, the proposed effort focuses on developing real-time passenger demand prediction models using multiple data sources to enhance prediction accuracy. For bike share service, the proposed effort focuses on developing prediction models for the number of bikes and travel times of bikes. Finally, for the automobile effort this research will develop a comprehensive traffic prediction tool by including different categories of prediction models. The proposed prediction algorithms and tools will be evaluated by the field data collected in multimodal transportation system by comparing with existing methods.


    • English


    • Status: Active
    • Funding: $300000
    • Contract Numbers:


    • Sponsor Organizations:

      Office of the Assistant Secretary for Research and Technology

      University Transportation Centers Program
      Department of Transportation
      Washington, DC  United States  20590

      U.S. Department of Transportation

      1200 New Jersey Avenue, SE
      Washington, DC  United States  20590
    • Managing Organizations:

      Urban Mobility and Equity Center

      Morgan State University
      Baltimore, MD  United States  21251
    • Project Managers:

      Tucker-Thomas, Dawn

    • Performing Organizations:

      Virginia Polytechnic Institute and State University, Blacksburg

      Virginia Tech Transportation Institute
      3500 Transportation Research Plaza
      Blacksburg, VA  United States  24061
    • Principal Investigators:

      Rakha, Hesham

    • Start Date: 20170601
    • Expected Completion Date: 20190531
    • Actual Completion Date: 0
    • USDOT Program: University Transportation Centers Program

    Subject/Index Terms

    Filing Info

    • Accession Number: 01635142
    • Record Type: Research project
    • Source Agency: Urban Mobility and Equity Center
    • Contract Numbers: 69A43551747123
    • Files: UTC, RiP
    • Created Date: May 24 2017 11:22AM