Traffic congestion detection is the basis of dynamic traffic control and real time guidance. This study proposes a fuzzy logic based traffic congestion identification method. The components of a fuzzy logic inference are firstly formulated. According to such information as the speed and occupancy of freeway traffic flow, and the weather conditions on the freeway, a congestion identification method based on fuzzy logic inference is then designed. Gauss curves are assumed for the membership functions of the input and output variables, and 45 fuzzy rules are also established. Finally, the congestion identification method is simulated. Simulation results verify the effectiveness of the above method. Fuzzy logic inference is suitable for estimating the traffic congestion index.


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    Titel :

    Freeway Traffic Congestion Identification Based on Fuzzy Logic Inference


    Beteiligte:
    Peng, Ming-Long (Autor:in) / Liang, Xin-Rong (Autor:in) / Dong, Chao-Jun (Autor:in) / Liu, Yan-Yan (Autor:in)


    Erscheinungsdatum :

    2013


    Format / Umfang :

    4 Seiten




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Freeway Traffic Congestion Identification Based on Fuzzy Logic Inference

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