DYNAMIC MODEL-BASED TECHNIQUES FOR THE DETECTION OF INCIDENTS ON FREEWAYS

A discussion is presented of an approach to the detection of incidents on freeways. The techniques are based on the use of a macroscopic dynamic model describing the evolution of spatial-average traffic variables (velocities, flows, and densities) over sections of the freeway. With such a model as a starting point, the authors develop two incident detection algorithms based on the multiple model and generalized likelihood ratio techniques. A description is given of a new and very simple system for processing raw data from presence-type vehicle detectors to produce estimates of the aggregate variables, which are then in turn used as the input variables to the incident detection algorithms. Simulation results are examined.

• Corporate Authors:

  Institute of Electrical and Electronics Engineers (IEEE)

  3 Park Avenue, 17th Floor
  New York, NY  United States  10016-5997
• Authors:
  • Willsky, A S
  • Chow, E Y
  • Gershwin, S B
  • Greene, C S
  • Kurkjian, A L
  • HOUPT, P K
• Publication Date: 1980-6

Media Info

• Features: References;
• Pagination: p. 347-360
• Serial:
  • IEEE Transactions on Automatic Control
  • Volume: AC-2
  • Issue Number: 3
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Subject/Index Terms

• TRT Terms: Algorithms; Control systems; Freeways; Information processing; Traffic crashes; Traffic simulation; Vehicle detectors
• Subject Areas: Highways; Operations and Traffic Management; I71: Traffic Theory;

Filing Info

• Accession Number: 00325055
• Record Type: Publication
• Source Agency: Engineering Index
• Files: TRIS
• Created Date: May 21 1981 12:00AM