TRAFFIC PREDICTION FOR REAL TIME TRAFFIC MANAGEMENT

A real-time traffic model is developed for operation as the kernel unit in a traffic management system, supplying the system with necessary short-term predictions. Online real-time tests are performed. Traffic is estimated and predicted for three different time worlds; one is used internally for fast feedback of predictions. High frequency response from sensors are filtered for different frequency domains, and then special methods are applied giving the best possible prediction of traffic flow and corresponding travel time. The new knowledge about real-time traffic processes is utilized in a queue model to handle direction and prediction of the queue growth process in real time. The automatic incident detection function is developed using advanced constant false alarm ratio. The real-time traffic theory is not only the basis for the traffic model, but also serves as the basis for design of traffic management systems and precalculation of system performance.

  • Supplemental Notes:
    • Five volumes of papers and one volume of abstracts comprise the published set of conference materials.
  • Corporate Authors:

    VERTIS

    TORANOMOM 34 MORI BUILDING 1-25-5
    TORANOMON, MINATOKU, TOKYO 105  Japan 
  • Authors:
    • Olsson, K
  • Conference:
  • Publication Date: 1995-11

Language

  • English

Media Info

  • Pagination: p. 375

Subject/Index Terms

Filing Info

  • Accession Number: 00721105
  • Record Type: Publication
  • Report/Paper Numbers: Volume 1
  • Files: TRIS
  • Created Date: May 22 1996 12:00AM