Expressway conflict risk mechanism considering the interactions between vehicle-group and road-segment

There have been numerous studies on conflict risk for expressways, with the majority of previous studies focusing on road-segments' conflict risk while neglecting the impact of moving vehicles. In recent years, some studies have begun to work on vehicle-group without the consideration of the traffic on the road-segment. However, as the vehicle-group travels along the road-segment, the conflict risk of road-segment and vehicle-group will interact with each other. The aim of this study is to analyze the interactive mechanism of conflict risk between vehicle-groups and road-segments on expressways.

This study utilized high-resolution vehicle trajectory data to separately build conflict risk prediction models for vehicle-groups and road-segments. The best performing models were selected and explainability algorithms were applied. The analysis then focused on two aspects: (1) the influence of downstream high-risk vehicle-groups on upstream road-segment conflict risk and (2) the impact of geometric and traffic parameters of downstream road-segments on the conflict risk of vehicle-groups.

The results show that vehicle-group characteristics significantly affect road-segment conflict risk. When high-risk vehicle-groups appear downstream, the conflict risk of the road-segment increases by about 6%, and the impact is stronger when the propagation distance is shorter. In turn, when the conflict risk of a downstream road-segment increases, this risk propagates upstream through the traffic flow, affecting the behavior of vehicle-groups and raising their conflict risk. A difference of 29% in vehicle-group conflict risk was observed depending on the median downstream road-segment conflict risk.

This study demonstrates that vehicle-groups and road-segments interact in the propagation of expressway conflict risk. Integrating these two dimensions enables more accurate conflict risk prediction and analysis. This research provides a novel perspective by integrating vehicle-group and road-segment interactions for more accurate conflict risk prediction and analysis.