The number of urban road traffic accidents is increasing all the time, which is greatly threatening the safety of people’s lives and property. This paper uses Bayesian network theory to analyze the causes of road traffic accidents; it selects urban road systems as the subject to confirm the accident factors and reform the risk factors to improve the urban road safety. Finally, this paper uses a true case to infer, predict, and diagnose the model, and the model is validated to be feasible and effective. The research can provide the basis for the improvement of traffic conditions and propose appropriate measures for improvement, to reduce accidents, and to improve the urban road traffic safety.


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    Titel :

    The Analysis of Urban Traffic Accidents Based on Bayesian Network


    Beteiligte:
    Li, Wenyong (Autor:in) / Zheng, Shuqing (Autor:in) / Lu, Yuan (Autor:in)

    Kongress:

    17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China


    Erschienen in:

    CICTP 2017 ; 4879-4888


    Erscheinungsdatum :

    18.01.2018




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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