Road safety management focuses on mitigating the occurrence of crashes by building safer roads, and crash prediction is one effective technique for achieving this goal. The crash prediction methodology developed by AASHTO and explained in the Highway Safety Manual (HSM) is the most common model among road management authorities and researchers. The manual provides calibration techniques to make the model flexible and applicable for roads that differ from the base conditions. However, the transferability of the HSM crash prediction model needs to be assessed before using it for real-life crash estimations. The objective of this study is to assess the transferability of the HSM crash model in the case of a mountainous two-lane rural highway in Nepal. Through this study, two major issues were identified in the HSM model: (1) the homogenous segmentation approach would lead to the formation of numerous short road segments with zero crashes and thus would be unpragmatic to consider, and (2) the function for crash modification factor for horizontal curves contributes to overpredicting road crashes because of curves with a smaller radius and shorter lengths. This shows that special considerations are required for applying the HSM to mountainous roads.


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    Titel :

    Assessing the Transferability of the Highway Safety Manual Crash Prediction Model in the Context of the Mountainous Rural Two-Lane Highway of Nepal


    Weitere Titelangaben:

    Lect.Notes Mechanical Engineering


    Beteiligte:
    Abdul-Nour, Georges (Herausgeber:in) / Ngoc Dinh, Minh (Herausgeber:in) / Seecharan, Turuna (Herausgeber:in) / Crespo Márquez, Adolfo (Herausgeber:in) / Komljenovic, Dragan (Herausgeber:in) / Amadi-Echendu, Joe (Herausgeber:in) / Mathew, Joseph (Herausgeber:in) / Acharya, Nitesh (Autor:in) / Henry, Michael (Autor:in)

    Kongress:

    World Congress on Engineering Asset Management ; 2023 ; Ho Chi Ming City, Vietnam October 17, 2023 - October 23, 2023



    Erscheinungsdatum :

    01.10.2024


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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