Highway vehicle weaving analysis aims to determine the percentage and number of vehicles changing lanes from origin to destination on a highway segment. Vehicle weaving often slows traffic, causes jams, and increases safety concerns. Quantitative lane-based highway weaving patterns analysis is crucial for traffic management and road improvement. However, there is currently no cost-effective tool to obtain lane-based vehicle weaving data. This paper describes a method combining machine learning with convenient user verification to achieve accurate weaving analysis using field camera videos. The effectiveness of this approach has been demonstrated in experimental results, and a software tool has been deployed to the Indiana Department of Transportation.


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    Titel :

    Highway Origin-Destination Vehicle Weaving Analysis Using Field Camera Videos


    Beteiligte:
    Lin, Wei (Autor:in) / Qiu, Mei (Autor:in) / Chien, Stanley (Autor:in) / Christopher, Lauren (Autor:in) / Chen, Yaobin (Autor:in)


    Erscheinungsdatum :

    24.09.2024


    Format / Umfang :

    1423344 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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