This study aims to model pedestrian temporal violation behavior at signalized crosswalks. Video data of pedestrian crossing behavior were collected from three locations in China and were used to investigate the effect of several factors on pedestrian temporal violation behavior. The temporal violation behavior was analyzed using the relationship between pedestrian waiting duration and their endurance probabilities. A fully parametric duration model with Weibull distribution was used to model the temporal violation behavior, and the cluster-specific heterogeneity among the three study sites was accounted for using random intercepts. Six variables were identified to significantly affect the violation behavior: pedestrian gender and phone distraction status, location type, pedestrian volume, day of the week, and time of the day. The results show that pedestrians are likely to disobey traffic regulations when there are longer waiting durations. Male pedestrians have a higher violation tendency than females. Pedestrians distracted by their phones have longer waiting durations than undistracted pedestrians. Signalized road segment crosswalks are associated with higher temporal violation propensity than signalized intersection crosswalks. Pedestrians are more likely to commit violations at higher pedestrian densities. Weekdays are associated with shorter waiting durations and higher violation tendency than weekends. Pedestrians are more likely to violate traffic regulations in the morning than at midday and in the evening. These findings give insights into the pedestrian crossing behavior to better accommodate pedestrians and improve safety.


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    Title :

    Modeling Pedestrian Temporal Violations at Signalized Crosswalks: A Random Intercept Parametric Survival Model


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:
    Liu, Yan (author) / Alsaleh, Rushdi (author) / Sayed, Tarek (author)


    Publication date :

    2022-03-03




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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