The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems.


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    Titel :

    A Red-Light Running Prevention System Based on Artificial Neural Network and Vehicle Trajectory Data


    Beteiligte:
    Li, Pengfei (Autor:in) / Li, Yan (Autor:in) / Guo, Xiucheng (Autor:in) / Jiang, Xiaobei (Autor:in)


    Erscheinungsdatum :

    2014


    Format / Umfang :

    11 Seiten, 25 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch




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