The present study investigates the effects of traffic volume on various surrogate safety measures (SSM) under varying roadway and traffic conditions both under work zone and without work-zone areas. The traffic data extractor is used to extract the collected traffic data. MATLAB coding tool was used to identify leader–follower pairs considering different vehicular movements. The potential SSM, such as post encroachment time (PET), time to collision (TTC), and de-acceleration rate to avoid collision (DRAC), are considered for the present study. Further, the Pearson correlation coefficient is computed to test the possible variations and dependence among SSMs. The analysis revealed a substantial variation between parameters for the selected pairs, PET and TTC, TTC, and DRAC, and PET and DRAC. Moreover, it is also inferred that the Pearson correlation coefficient result varies for different traffic volumes and roadway sections (work zone and without work zone) of roads.


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    Titel :

    Investigating Surrogate Safety Measures Under Varying Roadway and Traffic Conditions Using Vehicular Trajectory Data


    Weitere Titelangaben:

    Lecture Notes in Civil Engineering


    Beteiligte:
    Devi, Lelitha (Herausgeber:in) / Errampalli, Madhu (Herausgeber:in) / Maji, Avijit (Herausgeber:in) / Ramadurai, Gitakrishnan (Herausgeber:in) / Bidkar, Omkar (Autor:in) / Arkatkar, Shriniwas (Autor:in) / Joshi, Gaurang (Autor:in)

    Kongress:

    Conference of Transportation Research Group of India ; 2021 December 14, 2021 - December 17, 2021



    Erscheinungsdatum :

    29.09.2022


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch








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