Adverse weather conditions can threaten driving safety. This study focuses on exploring rear-end collision risks of car-following vehicles under adverse weather conditions. From the observations of car following behaviors and weather conditions on rural highways, some indicators are designed to measure rear-end collision risk. After the trails of each candidate indicator based on collected data, the indictor, namely the following risk, is selected to evaluate rear-end collision risk. A generalized linear model is established to assess the impact of different weather conditions on the risk. Results show that in terms of the effect of a single factor, the light condition has the greatest influence on the risk, followed by weather or road conditions. Meanwhile, interactive influence of the two factors is determined by specific car-following states. The interaction between each factor and light condition always has the greatest impact on rear-end collision risk.


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    Titel :

    Rear-End Collision Risk Assessment in Adverse Weather Conditions


    Beteiligte:
    Chen, Jingchang (Autor:in) / Zhao, Zhengcheng (Autor:in) / Li, Jinqiang (Autor:in) / Li, Li (Autor:in)

    Kongress:

    22nd COTA International Conference of Transportation Professionals ; 2022 ; Changsha, Hunan Province, China


    Erschienen in:

    CICTP 2022 ; 1824-1838


    Erscheinungsdatum :

    08.09.2022




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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