With the rapid advancement of intelligent connected vehicle technology, ensuring safe and efficient travel in highway weaving areas has become a significant research topic. Traditional trajectory prediction methods inadequately consider real-time traffic situation changes and lack generalizability. Consequently, this study introduces a trajectory prediction method for mixed vehicles in highway weaving areas based on Cyber-Physical Systems (CPS). Moreover, an enhanced Transformer model is employed to model the dynamic spatial interactions between vehicles. The well-trained model is deployed in the cyber layer, and by training with data from the physical layer, it facilitates real-time prediction of manually driven vehicle trajectories. Experimental results demonstrate that compared to prevalent approaches, our method offers more accurate and efficient trajectory prediction in complex weaving area scenarios.


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    Title :

    CPS-Based Vehicle Trajectory Prediction in Highway Interchanges under Mixed Traffic Conditions


    Contributors:
    Gu, Zhenyu (author) / Jiang, Wei (author) / Li, Dongyang (author) / Liu, Rentao (author)

    Conference:

    24th COTA International Conference of Transportation Professionals ; 2024 ; Shenzhen, China


    Published in:

    CICTP 2024 ; 131-140


    Publication date :

    2024-12-11




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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