Traffic Queue Prediction (TQP) & Warning System

To save lives, reduce secondary crashes, and in general protect the end of the queue and the motorists approaching the end of queue at a high speed, TDOT has successfully deployed HELP trucks to alert, advise, and, for some cases, actively control the approaching traffic. A challenge though is to have a better handle of the queue, once formed, in terms of where the end of the queue is and how fast it might grow and move. As such, this study proposes to develop a dynamic queue prediction model that utilizes real-time traffic data to estimate the behavior of the queue and the locus of the end of the queue. By studying different cases with comprehensive data and incident logs and video footages, the UT research team will develop a model capable of taking in real-time data to predict the end of queue location and movement dynamically. The proposed study will also assess quick information dissemination means for warning motorists approaching the vicinity of the end of the queue. Another focus of the study will look at the location and setup of the HELP truck upstream of the end of the queue.

Project

  • Status: Active
  • Funding: $40,409.00
  • Contract Numbers:

    RES2016-06

    IG1658992

  • Sponsor Organizations:

    Tennessee Department of Transportation

    James K. Polk Building
    Fifth and Deaderick Street
    Nashville, TN  United States  37243-0349

    Federal Highway Administration

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

    Tennessee Department of Transportation

    James K. Polk Building
    Fifth and Deaderick Street
    Nashville, TN  United States  37243-0349
  • Project Managers:

    Oldham, Jason

  • Performing Organizations:

    University of Tennessee, Knoxville

    Knoxville, TN  United States 
  • Principal Investigators:

    Han, Lee

  • Start Date: 20151001
  • Expected Completion Date: 20190630
  • Actual Completion Date: 0
  • USDOT Program: Transportation, Planning, Research, and Development

Subject/Index Terms

Filing Info

  • Accession Number: 01709925
  • Record Type: Research project
  • Source Agency: Tennessee Department of Transportation
  • Contract Numbers: RES2016-06, IG1658992
  • Files: RiP
  • Created Date: Jun 21 2019 5:23PM