Analysis of conflict between right-turning vehicles and pedestrians at urban intersections using random parameter Logit model.

Abstract

Objective: Pedestrians are prone to more dangerous conflicts with right-turning vehicles when crossing the street because of sharing phases with right-turning vehicles or their own violations. This paper aims to alleviate the frequent conflicts between right-turning vehicles and pedestrians and explores the significant influencing factors behind these conflicts.

Method: This study conducted field investigations at two representative signalized intersections in Guangzhou. During the research process, unmanned aerial vehicles (UAVs) were employed for oblique photography to collect data, which were then preprocessed using T-Analyst software. Based on this, intersection characteristics, characteristics of conflict participants, and unsafe crossing behaviors were extracted in detail, and this information was correlated with the behavioral trajectories of both parties involved in the traffic conflicts. In terms of conflict identification, the study utilized the time difference to collision (TDTC) method to identify 701 valid conflicts. In the data analysis phase, ordered Logit models, generalized ordered Logit models, and random parameter ordered Logit models were employed for modeling and analysis. Among them, the random coefficients ordered Logit model exhibited the best fit.

Result: The model results indicate that pedestrian pairing and the sequence in which conflict participants traverse the conflict point. Specifically, pedestrians crossing in pairs face a 13.9% higher risk of severe conflicts compared to those crossing alone, while the probability of minor conflicts decreases by 14.5%. Although vehicles passing first (VPF) through the conflict point reduce the occurrence of general and minor conflicts to some extent, they may trigger more severe conflicts. Furthermore, pedestrian and right-turning vehicle violations such as running red lights and failing to pay attention to oncoming traffic significantly increase the risk of severe conflicts.

Conclusion: To mitigate conflicts between right-turning vehicles and pedestrians, it is recommended to appropriately adjust the length and width of pedestrian crossings and implement dynamic signal phase control strategies at intersections where significant temporal variations in pedestrian and vehicular traffic are observed, ensuring orderly traffic movement across all time periods. Additionally, surveillance equipment should be installed at intersections to conduct real-time monitoring and management of pedestrian and vehicular violations, thereby curbing the occurrence of unsafe behaviors.