Pedestrian safety has become a critical issue due to the increase in pedestrian crashes every year, while proactive traffic safety management based on surrogate safety measures (SSMs) has been considered one of the key approaches to improving pedestrian safety. However, existing SSMs are developed based on the assumption that road users will maintain constant speed and direction. Risk estimations based on this assumption are less stable and more likely to be exaggerated. Considering the limitations of existing SSMs, this study has proposed a probabilistic framework for estimating the risk of pedestrian-vehicle conflicts at intersections. The proposed framework works by predicting the trajectories of vehicles and pedestrians using Gaussian process regression models and incorporating these results with the probability of vehicles making different maneuvers. The proposed framework has been evaluated using both simulated and real-world data collected at an intersection. The simulation results validated an increased estimated risk given time-critical pedestrian-vehicle conflicts, as well as a higher probability of the vehicle maneuver that led to such conflicts. This observation remained even when multiple conflicts arose from different directions. Moreover, experimental results using real-world data suggested that the proposed framework outperformed traditional time-to-collision (TTC) in terms of conflict prediction, quantification, and localization. For example, the proposed framework had a sensitivity of 0.92 in terms of conflict prediction, while TTC had a sensitivity of 0.62. Furthermore, the proposed framework required much less computation time compared to deep learning methods, which made it an optimal choice for proactive pedestrian safety solutions at intersections.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Probabilistic Framework for Estimating the Risk of Pedestrian-Vehicle Conflicts at Intersections


    Contributors:
    Li, Pei (author) / Guo, Huizhong (author) / Bao, Shan (author) / Kusari, Arpan (author)

    Published in:

    Publication date :

    2023-12-01


    Size :

    1951380 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    A Probabilistic Framework for Estimating the Risk of Pedestrian-Vehicle Conflicts at Intersections

    Li, Pei / Guo, Huizhong / Bao, Shan et al. | ArXiv | 2022

    Free access

    Mitigation of Pedestrian–Vehicle Conflicts at Stop-Controlled T-Intersections

    Gómez, Radhameris A. / Samuel, Siby / Romoser, Matthew R. E. et al. | Transportation Research Record | 2014


    Analysis of Spontaneous Order of Pedestrian–Vehicle Conflicts at Signalized Intersections

    Kumar, Abhinav / Ghosh, Indrajit | Transportation Research Record | 2020


    Pedestrian conflicts and left-turning traffic at signalized intersections

    Lord, D. | British Library Conference Proceedings | 1995


    Estimating the Safety of Unsignalized Intersections Using Traffic Conflicts

    Sayed, T. | British Library Conference Proceedings | 1997