Assessing conflict likelihood and its severity at interconnected intersections: Insights from drone trajectory data

Abstract

Unsignalized intersections are complex and hazardous due to their numerous conflicts. However, most studies analyzing crash factors at unsignalized intersections focus solely on the isolated intersection itself. This study investigates how proximity to signalized intersections affects traffic conflicts at unsignalized intersections (divided into three segments). Traditional segment-level traffic flow data often fail to capture the nuanced short-term traffic conditions that contribute to conflicts; thus, we utilized microscopic high-resolution trajectory data extracted from the CitySim drone dataset. To represent real dangerous events, conflict probability and severity were introduced and assessed using two surrogate safety measures: time-to-collision (TTC) and the predicted change in velocity post-collision (Delta-V). A Structural Equation Model (SEM) is applied to explore the interactive relationship within the interconnected intersections. Then, a hierarchical Joint Generalized Linear Mixed Model (JGLMM) was employed to identify factors contributing to conflict risks and severity across the three segments. SEM findings reveal that upstream traffic volume can significantly mitigate conflict risks downstream at interconnected intersections. Estimation results show that angled conflicts are prominent in weaving sections, with increased conflict probability and severity as the angle increases. Meanwhile, conflict potential decreases as vehicle queue length increases in right-turn lanes, but it increases with longer queues in left-turn lanes. Suggested countermeasures include clearly marking the left-turn lane at the intersection and installing clear left-turn signs in advance of the intersection. This study highlights the value of high-resolution trajectory data for in-depth variable analysis, facilitating hierarchical safety assessments and pinpointing influential interactions at interconnected intersections.