To assess traffic risk at intersections during snowy weather, this study introduces a collision risk determination method based on the extreme values of Post-Encroachment Time (PET). Subsequently, the SUMO software is utilized to simulate traffic flow during peak hours under continuous snowfall conditions at the intersection, and the Markov Chain Monte Carlo (MCMC) method is employed to fit the parameters of the extreme value theory model. The results indicate that the MCMC method performs better in handling parameter estimation for the generalized extreme value (GEV) model, and the risk of traffic conflict events in snowy environments is significantly higher than in clear weather.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Traffic Conflicts-Based Crash Risk Assessment at Intersections Using Extreme Value Theory Approach


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Liu, Jun (Herausgeber:in) / Li, Wang (Herausgeber:in) / Geng, Xiongfei (Herausgeber:in) / Zhang, Ke (Herausgeber:in) / Ji, Honghai (Herausgeber:in) / Li, Kailong (Herausgeber:in) / Fu, Chuanyun (Autor:in) / Liu, Jiaming (Autor:in) / Wumaierjiang, Ayinigeer (Autor:in) / Liu, Huahua (Autor:in)

    Kongress:

    International Conference on Artificial Intelligence and Autonomous Transportation ; 2024 ; Beijing, China December 06, 2024 - December 08, 2024



    Erscheinungsdatum :

    02.04.2025


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Traffic Crash Analysis and Risk Modeling at Signalized Intersections

    Jinmei, W. / Zhao an, W. / Jianguo, Y. | British Library Online Contents | 2005





    Identifying High-Crash-Risk Intersections

    Lim, In-Kyu / Kweon, Young-Jun | Transportation Research Record | 2013