The assessment of pedestrian safety is often conducted in a reactive way by analyzing pedestrian crash data. However, in a developing country, the availability of reliable crash data is a major challenge. Therefore, without relying solely on reactive approach, it is essential to combine some methods that can proactively assess pedestrian safety. In this background, the present study proposed a methodology combining both reactive and proactive approaches to assess pedestrian safety at urban intersections in Kolkata, India. The method developed in the present study utilizes a combination of the historical crash data analysis, the analysis of pedestrian-vehicular conflict (i.e., pedestrian-vehicular post-encroachment time), along with pedestrians’ risk perception toward the built environment and traffic parameters, to identify the key factors influencing pedestrian safety and to recognize potential risk-prone intersections in Kolkata.

    Based on the combined reactive and proactive assessments, there is evidence that high vehicle volume, pedestrian-vehicular volume ratio, absence of traffic signal, inaccessibility of the pedestrian crosswalk, absence of police personnel, higher approaching speed, commercial area, inadequate sight distance, presence of slum population, and higher population density near the intersection significantly increase the risk of pedestrian crashes. Finally, using this combined proactive-reactive approach, the present study also identifies and ranks twenty-five high risk-prone intersections for pedestrians. This is a significant step toward scientific decision making and allowing the use of information beyond historical crash records.


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    Title :

    Pedestrian safety analysis of urban intersections in Kolkata, India using a combined proactive and reactive approach


    Contributors:

    Published in:

    Publication date :

    2022-05-04


    Size :

    42 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





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