TRAFFIC SURVEILLANCE DATA PROCESSING IN URBAN FREEWAY CORRIDORS USING KALMAN FILTER TECHNIQUES

Real-time surveillance of traffic conditions on urban freeway corridors using spatially discrete presence detectors is addressed. Using a finite-dimensional (macroscopic) fluid-analog model for freeway vehicular traffic flow, an extended Kalman filter is proposed as a data-processing algorithm to obtain minimum variance estimates of spatial mean speed and density. It is shown that certain model parameters associated with available roadway capacity can be estimated on-line with a variation of the extended Kalman filter, and furthermore, that the time signatures associated with these estimates provide quantitative information concerning the presence of anomalous (i.e., incident) traffic events. Performance of the surveillance algorithm is evaluated using a detailed, multi-lane microscopic vehicle simulation which retains a stochastic mix of driver-vehicle types and passing. Complexity problems associated with the computer implementation of the extended Kalman filter are addressed, and techniques for decentralized realization are proposed.

  • Corporate Authors:

    Massachusetts Institute of Technology

    Electronics Systems Laboratory
    Cambridge, MA  United States 

    Transportation Systems Center

    55 Broadway, Kendall Square
    Cambridge, MA  United States  02142
  • Authors:
    • HOUPT, P K
    • Athans, M
    • Orlhac, D G
    • Mitchell, W J
  • Publication Date: 1978-11

Media Info

  • Pagination: 198 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00190513
  • Record Type: Publication
  • Source Agency: National Technical Information Service
  • Report/Paper Numbers: DOT-TSC-RSPA-78-18 Final Rpt.
  • Contract Numbers: DOT-TSC-849
  • Files: NTIS, TRIS
  • Created Date: Mar 14 1979 12:00AM