TECHNIQUES FOR DETECTION OF INCIDENTS AND TRAFFIC DISTURBANCES

The increasing contribution of incidents to freeway congestion has generated strong interest in the development of incident detection algorithms in the last two decades. Existing techniques for the detection of freeway incidents do not provide the necessary reliability for freeway operations. The initial phase of this research focused on assessing the performance limitations of conventional automatic incident detection systems. That research was directed towards two objectives, the performance evaluation of major existing algorithms and the development of an improved algorithm. This research developed and tested algorithms that efficiently detect incidents at low levels of false alarms. The second stage of this project: described, classified and analyzed major types of traffic disturbance and their characteristics; developed strategies for detecting major traffic disturbances based on their distinctive features; and developed strategies for modeling the propagation of detected traffic disturbances and predicting the traffic conditions in the area of the disturbance.

• Corporate Authors:

  University of Minnesota, Minneapolis

  Center for Transportation Studies, 511 Washington Avenue, SE
  Minneapolis, MN  United States  55455-0375
• Authors:
  • STEPHANEDES, Y J
  • Chassiakos, A
  • Vassilakis, G
• Publication Date: 1994-4

Language

• English

Media Info

• Features: Appendices; Figures; References; Tables;
• Pagination: 110 p.

Subject/Index Terms

• TRT Terms: Algorithms; Forecasting; Incident detection; Traffic congestion; Traffic crashes; Traffic models
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 00724600
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 19 1996 12:00AM