Connected and automated vehicles are widely agreed to bring tremendous benefits to the traffic system. But the understanding of them is still challenging due to the complexity of the mixed traffic flow of human-driven (HDVs), automated vehicles (AVs), and connected and automated vehicles (CAVs), and due to our limited knowledge of the impacts of adverse weather conditions. Given this, this study was driven to test the safety performance of the above mixed traffic flow both in sunny and snowy conditions under various market penetration rates (MPRs) using SUMO. Minimum gap, the acceleration/deceleration ability of vehicles, and the drivers’ desired (minimum) time headway were specifically calibrated for car-following behaviors by a Kolmogorov-Smirnov test based on data collected at an intersection in China. Three surrogate safety measures, i.e., time to collision (TTC), Time-Exposed TTC (TET), and brake rate (BR), were utilized to evaluate the real-time crash risk variations. The results show that 1) the safety performance improved in sunny and snowy conditions when the traffic flow was mixed with AVs and CAVs; 2) the improvement of AVs and CAVs in avoiding serious conflicts was more significant in the snowy condition, and 3) the performance of the braking rate was different when MPRs increased in the sunny and snowy conditions. In addition, the difference in safety benefits between AVs and CAVs in sunny and snowy conditions was analyzed. The findings of this study provide valuable insights for managing connected and automated traffic under the snowy condition on urban roads.


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    Titel :

    Safety Benefits Evaluation of Mixed Traffic Flow with Connected and Automated Vehicles under Snowy Conditions


    Beteiligte:
    Lu, Zhaoyou (Autor:in) / Ding, Naikan (Autor:in) / Gao, Jin (Autor:in) / Fu, Chuanyun (Autor:in) / Zhang, Hui (Autor:in)


    Erscheinungsdatum :

    2023-08-04


    Format / Umfang :

    892267 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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