Vehicle-pedestrian interactions at unsignalized intersections are crucial for pedestrian safety. This study examines interactions at three unsignalized intersections in Germany: one zebra crossing and two unmarked crossings. Vehicle-pedestrian interactions were documented within a 30-meter predefined zone, and linear regression models evaluated the relationship between vehicle obstructed travel time and predictors like pedestrian time-to-start-crossing, vehicle speed, deceleration, pedestrian speed, direction of travel, crossing location, and group behavior. Clustering analysis revealed critical behavioral patterns impacting safety. At zebra crossings, two clusters emerged: one with high driver-yielding compliance, facilitating safe crossings, and another with low compliance, possibly due to aggressive driving or unfamiliarity with traffic rules. At unmarked crossings, results showed more variability, with some drivers yielding despite having the right of way. These behaviors might be influenced by factors like pedestrian assertiveness and visibility conditions. The combination of clustering and regression analysis provided insights into key variables influencing driver behavior and pedestrian safety. Identifying clusters where risky interactions occur highlights opportunities for targeted interventions. Traffic safety professionals can use these findings to implement strategies such as improved signage, driver education, and enforcement against aggressive driving. Additionally, clustering helps prioritize intersections for proactive safety measures, addressing underlying risk factors to prevent future incidents.


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    Title :

    Modeling vehicle-pedestrian interactions at unsignalized intersections


    Additional title:

    H. Nassereddine
    Journal of Transportation Safety & Security


    Contributors:

    Published in:

    Publication date :

    2025-06-03


    Size :

    19 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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