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.
Fuzzy Inference-Based Driver Decision Processes and Traffic Flow Simulation
1996
32 pages
Report
Keine Angabe
Englisch
Transportation Safety , Road Transportation , Traffic flow simulations , Decision making , Driver behavior , Traffic simulation , Traffic flow , Acceleration , Deceleration , Cruising , Car following , Distance headways , Following distance , Traffic congestion , Intelligent Transportation Systems(ITS)
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