The operational influence of signalized intersections extends beyond the physical intersection area to the upstream and downstream segments, where vehicles decelerate, stop, and accelerate in response to traffic signals. Determining this influence area is important for accurately evaluating the operational performance of intersections at the arterial or corridor level. However, the spatial extent of the operational influence of signalized intersections is not well-addressed in existing literature or practice. Therefore, this study aims to determine and model the influence area of urban signalized intersections using a large sample of crowdsourced trajectory data collected across 20 approaches in Tucson, Arizona, U.S. We developed analytical models for the upstream and downstream influence areas by examining the speed profiles of vehicles approaching an intersection. Results showed a high variation in drivers’ decelerating and accelerating behaviors while approaching signalized intersections. The acceleration rates for departing downstream were lower than the deceleration rates for stopping upstream. The downstream influence area was 20% to 90% longer than upstream. The impacts of operating speed and temporal factors on both influence areas are further analyzed and modeled using quantile regression. Additionally, we discuss the practical implications of the influence area in traffic operations, safety, intersection design, and emissions estimation.


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    Titel :

    Modeling Influence Area for Urban Signalized Intersections Using Crowdsourced Trajectory Data


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:


    Erscheinungsdatum :

    06.06.2025




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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