FUZZY LOGIC BASED ONLINE COLLISION PREDICTION SYSTEM FOR SIGNALIZED INTERSECTIONS

This paper proposes a conceptual framework of online collision prediction and avoidance system for signalized intersections. A fuzzy logic inference system is developed to perform online collision prediction, which is the core for implementation of intersection collision alerting/avoidance technologies. The risk is quantified by 3 fuzzy inputs to the model, time to collision, severity of the crash, and the local perception of the drivers. Perception and Severity Indices are integrated to reflect driver-vehicle system safety characteristics. An example at a hypothetical intersection is given to demonstrate the proposed methodology for the red light running vehicle. Discussion of the results and some extensions of this work are also provided.

  • Availability:
  • Corporate Authors:

    University Roma Tre

    Department of Sciences of Civil Engineering
    via Vito Volterra, 62
    Rome,   Italy  00146
  • Authors:
    • Sun, D
    • Ukkusuri, S
    • Benekohal, R F
    • Waller, S T
    • Liu, B
  • Publication Date: 2004

Language

  • English

Media Info

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Filing Info

  • Accession Number: 00976543
  • Record Type: Publication
  • ISBN: 8879997300
  • Files: TRIS
  • Created Date: Jul 26 2004 12:00AM