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.


    Access

    Download


    Export, share and cite



    Title :

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


    Additional title:

    Int. J. ITS Res.


    Contributors:


    Publication date :

    2024-04-01




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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

    Kawasaki, Yosuke / Hirata, Kensuke / Ootake, Hiroshi | Springer Verlag | 2024

    Free access

    A Traffic Anomaly Detection Method Using Traffic Flow Vectors During Heavy Rainfall

    Hirata, Kensuke / Kawasaki, Yosuke / Yoshida, Takahiro | Springer Verlag | 2025

    Free access

    A Traffic Anomaly Detection Method Using Traffic Flow Vectors During Heavy Rainfall

    Hirata, Kensuke / Kawasaki, Yosuke / Yoshida, Takahiro | Springer Verlag | 2025

    Free access


    Expressway traffic anomaly detection method

    LYU CHEN / SUN LIN / DING BO et al. | European Patent Office | 2024

    Free access