AbstractDuring heavy rains, traffic monitoring is limited, as the affected areas are monitored by reporting and patrolling. In this study, a method for detecting traffic anomalies during heavy rainfall events was established, and a model that uses probe vehicle data to detect traffic anomalies during a disaster (an event in which vehicles make U-turns in front of a damaged area) was proposed. In addition, a parameter calibration method was developed for the model using past disaster-related data. The generalizability of the calibrated model was evaluated by applying it to other disasters. According to the results, the proposed model exhibited good generalizability.


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    Titel :

    Evaluation of the Versatility of a Traffic Anomaly Detection Method during Heavy Rainfall


    Weitere Titelangaben:

    Int. J. ITS Res.


    Beteiligte:
    Kawasaki, Yosuke (Autor:in) / Hirata, Kensuke (Autor:in) / Ootake, Hiroshi (Autor:in)


    Erscheinungsdatum :

    01.04.2024




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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