Highlights Enhanced dynamic Forward Collision Warning (FCW) model tailored for hazmat truck drivers with varying driving characteristics and risk levels. Multi-objective optimization method employed to determine the optimal warning time considering real-time driving risk, driver acceptance, and driving comfort. Differentiation in optimal warning times for driver categories under mid-level and low-level risks, while similar warning time for high-level risks. Development of user profiles based on historical driving records improves driver trust and enhances driving safety with ADAS systems.

    Abstract The risky driving behavior of hazmat truck drivers is a crucial factor in many severe traffic accidents. In-vehicle Advanced Driving Assistance Systems (ADAS), integrating vehicle active safety and driver assistance technology, has been installed into hazmat trucks aiming to reduce driving risks during emergencies. This paper presents an enhanced dynamic Forward Collision Warning (FCW) model tailored for hazmat truck drivers with different driving characteristics and risk levels. Our objective is to determine the optimal moment to alert drivers during risky situations. The novelty of our approach lies in analyzing the driver’s response mechanism to the warning by considering their characteristics and real-time driving risk levels. We employ a multi-objective optimization method that integrates real-time driving risk, driver acceptance, and driving comfort to calculate the optimal warning time. Our findings indicate that the appropriate warning time is similar for all drivers under high-level risks, while significant differentiation exists for different driver categories under mid-level and low-level risks. Additionally, aggressive drivers tend to follow leading vehicles closely and exhibit lower deceleration intentions when faced with dangers compared to normal and cautious drivers. Our research outcomes enable the development of user profiles for hazmat truck drivers based on extensive historical driving records, facilitating the analysis of driver response differences to FCWs. This enhances driving safety and improves driver trust in ADAS systems.


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    Titel :

    Adaptive forward collision warning system for hazmat truck drivers: Considering differential driving behavior and risk levels


    Beteiligte:
    Shao, Yichang (Autor:in) / Shi, Xiaomeng (Autor:in) / Zhang, Yi (Autor:in) / Zhang, Yuhan (Autor:in) / Xu, Yueru (Autor:in) / Chen, Weijie (Autor:in) / Ye, Zhirui (Autor:in)


    Erscheinungsdatum :

    2023-07-14




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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