Automated Congestion Prediction with Smart Phones

Accurate prediction of traffic congestion is essential for efficient highway operations and planning studies. Prevalent data collection and monitoring relies on human operators or fixed sensors, and hence, cannot systematically acquire dynamic information about vehicle behaviors such as acceleration, deceleration, and steering necessary for detailed modeling and analysis. The project proposes to investigate the use of smart phone technology to facilitate dynamic data collection. The smart phone application will be initially tested on the transportation network surrounding the University of Connecticut (UConn) in Storrs. To demonstrate the potential for technology transfer to highway monitoring, the portion of Interstate 84 running through Hartford will then be targeted for data collection. The smart phone application will securely transmit trip data over the Internet to servers hosted at UConn for statistical analysis and model development. The proposed models will be validated against real data feeds provided by our collaborators at ConnDOT. This research will enable real-time data fusion for efficient operation of transportation networks, a major focus of the t-HUB living laboratory at UConn. The smartphone application will be made available to t-HUB partners to promote a deeper understanding of regional demand, which will enhance regional transportation monitoring and planning efforts.


  • English


  • Status: Completed
  • Funding: $214725.00
  • Contract Numbers:



  • Sponsor Organizations:

    Research and Innovative Technology Administration

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

    New England University Transportation Center

    Massachusetts Institute of Technology
    77 Massachusetts Avenue, Room 40-279
    Cambridge, MA  United States  01239
  • Start Date: 20120101
  • Expected Completion Date: 0
  • Actual Completion Date: 20160131
  • Source Data: RiP Project 33390

Subject/Index Terms

Filing Info

  • Accession Number: 01489782
  • Record Type: Research project
  • Source Agency: New England University Transportation Center
  • Contract Numbers: DTRT12-G-UTC01, UCNR24-29
  • Files: UTC, RiP
  • Created Date: Aug 15 2013 1:01AM