With the advances and development in technology, transportation becomes one of the centers of life, and urban area control is one of its important parts. However, the increase of vehicles inevitable creates the phenomenon of road congestion, especially at the intersection. Intersection signal time optimization can effectively reduce traffic delays, improve the intersection's traffic capacity and is an important measure to improve the traffic condition. This paper proposes a fuzzy neural network traffic signal control method based on line length of cars in waiting. First, the method initial coordinates the intersection signal time according to the traffic status information. Then, with fuzzy control and artificial neural network, the traffic signal is adjusted to achieve the optimization of the whole system. Simulation results show that, compared with the general time-set control, this method can get superior results.


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    Titel :

    Traffic Signal Control of Fuzzy Neural Network Based on Line Length of Cars in Waiting


    Beteiligte:
    Li, Xue (Autor:in) / Lu, Bai-Chuan (Autor:in) / Li, Yi (Autor:in)

    Kongress:

    Ninth Asia Pacific Transportation Development Conference ; 2012 ; Chongqing, China


    Erschienen in:

    Erscheinungsdatum :

    2012-06-28




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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