Studying the connection between road features and road safety is vital for enhancing traffic safety management and reducing accidents. However, relying solely on accident data may not accurately assess road safety, as some roads can be hazardous without a history of accidents. To address this, our study developed a multivariate ordered probit model to examine the relationship between road characteristics and instances of risky driving behavior, considering acceleration and deceleration interactions. We analyzed a data set of 7,866 risky driving behaviors linked to road characteristics, including road width, length, congestion index, speed limit, and road type. The result showed that the length and width of the road, the average speed of the road, and the type of road are all significantly related to risky acceleration. The length and width of the road, average road speed, speed limits, and road type are all significantly associated with risky deceleration.


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    Titel :

    The Association between Road Characteristics and Risky Driving Behaviors Based on Naturalistic Driving Data


    Beteiligte:
    Yue, Quansheng (Autor:in) / Cui, Pengfei (Autor:in) / Chai, Hua (Autor:in) / Hu, Runbo (Autor:in) / Luo, Yuanwei (Autor:in) / Guo, Yanyong (Autor:in)

    Kongress:

    24th COTA International Conference of Transportation Professionals ; 2024 ; Shenzhen, China


    Erschienen in:

    CICTP 2024 ; 2582-2591


    Erscheinungsdatum :

    11.12.2024




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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