In the expressway network, a large number of abnormal vehicle overtime behaviors occur every day. Currently, there is no efficient detection method. To solve this problem, this paper presents a vehicle full probability prediction optimization model, which can calculate the abnormal probability of other vehicles affected by the event after one vehicle is identified as abnormal vehicle. Further on, this paper establishes multiple events linear estimation model for two probability vehicle types. Finally, this paper presents a probability algorithm of abnormal overtime driving behavior to calculate the abnormal probability of various probability vehicle types.


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    Titel :

    Research on prediction of abnormal overtime behavior of expressway vehicles


    Beteiligte:
    Huo, Lingyu (Autor:in) / Lei, Yuyang (Autor:in) / Ye, Jinsong (Autor:in) / Zhou, Lei (Autor:in)

    Kongress:

    Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022) ; 2022 ; Wuhan,China


    Erschienen in:

    Proc. SPIE ; 12610


    Erscheinungsdatum :

    28.04.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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