Causal Inference-Based Analysis of Critical Design Features for Right-turn Crashes at Signalized Intersections

发布者: TJsafety发布时间:2026-08-11浏览次数:10

Ziyuan Huang, Xuesong Wang*, Xiao Qin, Mengjiao Wu, Qiming Guo, Guangzhu Luo, Bangyu Wang, Yu Jiang

Abstract: In China, there are usually no exclusive right-turn phases or right-turn-on-red at signalized intersections. Right-turn crashes account for over 30% of intersection-related crashes, highlighting the critical role of intersection design in traffic safety. However, the relationship between specific design features and crash risk remains unclear. This study identifies key design variables and quantifies their causal effects and heterogeneity on right-turn crashes at signalized intersections. A total of 271 signalized intersections in Suzhou, China, were analyzed from 2022 to 2024. The SHapley Additive exPlanations method was applied to rank variable importance, followed by Generalized Random Forest modeling to estimate both Average and Heterogeneous Intervention Effects (HIEs) while controlling for confounding bias. The minimum right-turn radius and intersection skewness were identified as the most influential factors for total and fatal crashes, respectively. A turning radius of approximately 15 m was associated with the lowest total crash risk, and right-angle intersections were linked to reduced fatal crash rates. A bicycle lane barrier width on the minor road between 1.01 and 3 m also contributed to crash reduction. HIEs showed that smaller turning radii improved safety at high-volume, multi-lane intersections, and skewed intersections with low traffic volumes required special attention. Facilities such as bicycle lanes, physical barriers, and channelization islands enhanced safety performance at skewed intersections. As turning radii increase, expanding the bicycle lane barrier width may be beneficial, although wider barriers should be applied cautiously under low traffic conditions. This study provides a causal inference framework for evaluating right-turn design and offers evidence-based guidance for improving intersection safety in urban environments.

引用:Ziyuan Huang, Xuesong Wang*, Xiao Qin, Mengjiao Wu, Qiming Guo, Guangzhu Luo, Bangyu Wang, Yu Jiang. Causal Inference-Based Analysis of Critical Design Features for Right-turn Crashes at Signalized Intersections. Accident Analysis & Prevention, Volume 232, July 2026, 108544.