To evaluate the robustness of emerging mixed traffic flow under snowy conditions from the perspective of crash risk, this study proposes a TTC (Time-to-Collision) dynamic threshold determination method based on extreme value theory to quantify the crash risk. This study simulates traffic flow during peak hours under continuous snowfall conditions in the SUMO software, and use eta-squared to evaluate the robustness of traffic flow under the various Market Penetration Rates (MPR). The results indicate that at different extreme quantiles, as MPR increases, eta-squared shows a downward trend. Especially under high MPR (80%), eta-squared can decrease by more than 45%. This result indicates that emerging mixed traffic flow under high MPRs can effectively improve the robustness under snowy conditions and reduce crash risk compared to traditional traffic flow.


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    Titel :

    Robustness Evaluation of Emerging Mixed Traffic Flow in Snowy Weather Using Extreme Value Theory


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Gao, Kun (Herausgeber:in) / Bie, Yiming (Herausgeber:in) / Howlett, R. J. (Herausgeber:in) / Jain, Lakhmi C. (Herausgeber:in) / Fu, Chuanyun (Autor:in) / Liu, Huahua (Autor:in) / Lu, Zhaoyou (Autor:in)

    Kongress:

    Proceedings of KES-STS International Symposium ; 2024 ; Madeira, Portugal June 19, 2024 - June 21, 2024



    Erscheinungsdatum :

    22.09.2024


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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