Adaptive cruise control (ACC) systems can effectively reduce drivers’ workload, improve vehicles’ active safety, and make driving more comfortable. Real-time leading vehicle detection is one of the most important research tasks in the ACCs. The traditional leading vehicle detection methods based on radar or vision have many problems on curved roads, such as limited detection range, low real-time performance, poor adaptability to the environment, and so on. This paper proposes a method of real-time leading vehicle detection on curved roads based on the vehicle-to-vehicle (V2V) communication technique. We collect vehicle state information by equipment on-board and use V2V communication equipment to send, receive, and store this information. Moreover, one vehicle detection algorithm based on contact ratio of vehicle trajectory has been designed. The experimental results indicate that the method can meet the requirements of excellent accuracy, high real-time performance, and good adaptability to the environment.


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    Titel :

    A Method of Real-Time Leading Vehicle Detection of Adaptive Cruise Control System on Curved Road Based on V2V


    Beteiligte:
    Wu, Mengxiao (Autor:in) / Lu, Guangquan (Autor:in) / Chen, Peng (Autor:in) / Ding, Chuan (Autor:in)

    Kongress:

    17th COTA International Conference of Transportation Professionals ; 2017 ; Shanghai, China


    Erschienen in:

    CICTP 2017 ; 411-419


    Erscheinungsdatum :

    2018-01-18




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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