This study leverages commercial connected vehicle (CCV) data to address road safety issues at high-speed signalized intersections in Iowa. The study focuses on assessing road safety using minimal CCV data. The temporal stability analysis of the data concluded that the 8-week data was relatively stable. By testing the correlation between the number of hard braking at different intersections and crash data in 8 weeks of randomly selected CCV data, it was concluded that hard braking and crashes have a high correlation (greater than 0.5). Additionally, the study explores the predictive power of CCV data on crash risk and time distribution throughout the day. The results reflect the importance of real-time insights from CCV data for targeted interventions, highlighting the need for a data-driven approach to enhance overall road safety.


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    Titel :

    Leveraging Commercial Connected Vehicle Data for High-Speed Signalized Intersection Safety: A Quantitative Analysis of Hard-Braking and Crashes


    Beteiligte:
    Wei, Xi (Autor:in) / Knickerbocker, Skylar (Autor:in) / Hawkins, Neal (Autor:in) / Hans, Zachary (Autor:in) / Sharma, Anuj (Autor:in)


    Erscheinungsdatum :

    14.05.2024


    Format / Umfang :

    963992 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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