Traffic conflicts are most used surrogate safety measure (SSM), primarily defined using temporal or spatial proximity indicators assuming homogeneous traffic scenario where vehicle sizes do not vary much. In order to segregate conflicts from normal interactions, a proper threshold value of a conflict indicator must be used. Selecting an appropriate threshold value is challenging since it de-pends on static and dynamic characteristics such as size, speed, acceleration, and breaking capability of the vehicles. Inappropriately selecting the threshold would likely lead to false estimation of conflict and hence safety. The objective of pre-sent study is to define conflict considering vehicle sizes for more accurate rear-end crash risk estimation in heterogeneous traffic conditions. Time-to-collision (TTC), a conflict indicator was estimated from Traffic video data recorded at 4 unsignalized T-intersections for 3.5 hours at each location, identified as black spot on divided high-speed roads in Uttar Pradesh, India. In this study, a semi-automated method was used to extract vehicle trajectories from videos. In this paper, we propose extreme value-based Peak over threshold modelling to relate rear-end crash risk with vehicle size. Results show that threshold for TTC is dependent upon leader-follower pair. Therefore, conflict analysis based on global threshold would be biased since such normal interactions may be identified as critical even if they are safe. The proposed framework can be used for a more accurate risk assessment and calibration of vehicle warning system in heterogeneous traffic conditions.


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    Title :

    The Impact of Vehicular Heterogeneity on the Rear-end Crash Risk in Mixed Traffic: An Extreme Value Approach


    Additional title:

    Lecture Notes in Civil Engineering



    Conference:

    International Conference on Traffic and Granular Flow ; 2022 ; Delhi, India October 08, 2022 - October 10, 2022



    Publication date :

    2024-05-26


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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