Because of the poor results we've got from research on intersection traffic light based on fuzzy control, fuzzy neural network is then considered to be applied. By integrating the unique characteristics into fuzzy control, which are self-learning and self-adapting, a proper intersection traffic light control model that complies better with the present road condition is established. By constructing multiple intersections linkage control, the model applying a fuzzy network control rule where vehicle speed and distance are input variables of the model, the obtained phase difference is the output variable. With the use of MATLAB to verify the fitness of the model, it is proved that this model has a significant effect on improving traffic situations.


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    Titel :

    Gang Control Model for Intersection Traffic Light Control Based on Fuzzy Neural Network


    Beteiligte:
    Zha, Weixiong (Autor:in) / Peng, Chuan (Autor:in)

    Kongress:

    Fourth International Conference on Transportation Engineering ; 2013 ; Chengdu, China


    Erschienen in:

    ICTE 2013 ; 2643-2649


    Erscheinungsdatum :

    09.10.2013




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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