The trend of intelligent transportation has been leading the world for years, and human acceptance of applying Advanced Driver Assistance Systems (ADAS) in driving is increasing. Among all types of human driving, large vehicle driving is the one that requires the assistance of ADAS the most. It is imperative to use automatic driving technology to assist large vehicle driving and further integrate those successful cases into ADAS to increase safety and driving experience. According to [1] and [2], improper lane changes are one of the top 10 driver-related factors involved in large truck crashes. Due to their size and weight, large vehicles require more space and time to change lanes. To fundamentally improve the safety of their lane changes, this paper proposes a Lane Change Assisting Framework (LCAF) for large vehicles. It helps to reduce the potential risks of large vehicles in the lane-changing process by predicting the driving intention of surrounding vehicles and evaluating the safety of potential routes. By assisting the lane change decision-making of large vehicles, while not affecting their passing rate, the passive influence of their lane changes on the whole traffic flow is minimized, and the speed and capacity of the traffic system are improved.


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    Titel :

    A Lane Change Assisting Framework for Large Vehicles


    Beteiligte:
    Zhao, Nanbin (Autor:in) / Wang, Xinran (Autor:in) / Wang, Bohui (Autor:in) / Zhang, Jialu (Autor:in) / Lu, Yun (Autor:in) / Su, Rong (Autor:in)


    Erscheinungsdatum :

    2023-09-24


    Format / Umfang :

    1497831 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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