This paper presents the dynamic neuro-fuzzy control system for controlling the intelligent transportation system. The controller proposed in this paper is comprised two dynamic neural networks and a system identifier. The system identifier is used to identify the output of the adaptive cruise control system, and one of the dynamic neural networks is employed to learn the weighting factor of the fuzzy logic neural network, the other is control the vehicle system. When the control strategy is not suit for vehicle, identifier will select the best model to be the controller.
Dynamic Neuro-Fuzzy Control Design for Adaptive Cruise Controller in Intelligent Transportation System
Second International Conference on Transportation Engineering ; 2009 ; Southwest Jiaotong University, Chengdu, China
2009-07-29
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Highways and roads , Information technology (IT) , Transportation management , Construction , Freight transportation , Traffic flow , Water transportation , Intelligent transportation systems , Fuzzy sets , Air transportation , Rail transportation , Traffic safety , Optimization , Public transportation , Traffic management
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