Traffic simulations have traditionally used strictly deterministic, differential-equation-based, models of driving processes. Human decision making is, however, a linguistically structured rule-based process where desired outcomes are only approximately defined. The nature of human reasoning is thus better captured by fuzzy-inference logic, which this project uses to model driving behavior. individualized fuzzy inference models of different types of drivers that have been developed and incorporated into the TRAF-NETSIM microscopic traffic flow simulation environment. Users can now choose this fuzzy inference based driver decision model as an option when running TRAF-NETSIM to simulate more realistic vehicle motion accuracy.


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    Title :

    Fuzzy Inference-Based Driver Decision Processes and Traffic Flow Simulation


    Contributors:
    S. Kikuchi (author)

    Publication date :

    1996


    Size :

    32 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




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