School of Transportation, Southeast University, Nanjing 211189, China; Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing 211189, China; Department of Civil Engineering, The University of British Columbia, Canada.
School of Transportation, Southeast University, Nanjing 211189, China; Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing 211189, China.
Accid Anal Prev. 2024 Oct;206:107722. doi: 10.1016/j.aap.2024.107722. Epub 2024 Jul 20.
A major safety hazard for e-bike riders crossing an intersection is encountering heavy vehicles turning right in the same direction, which often results in severe casualties. Recently, some cities in China have implemented right-turn safety improvement treatments (i.e., right-turn yielding rules and right-turn warning facilities) at intersections to reduce the occurrence of such accidents. However, the risk perception and behavior of e-bike riders and heavy vehicle drivers dynamically change during the right-turn interaction process, and the safety effects of different right-turn safety measures remain unclear. This study aims to investigate the safety effect of right-turn safety measures on E-Bike-Heavy Vehicle (EB-HV) right-turn conflicts at signalized intersections. The right-turn conflicts and potential influencing factors are extracted from aerial video data, including characteristics of right-turn warning facilities, characteristics and behavior of e-bike riders and heavy vehicle drivers, environmental factors, and traffic-related factors. Moreover, traffic conflict indicators such as the Time to Collision (TTC), Post Encroachment Time (PET), and Jerk are selected and calculated. Multinomial and binary logit models are used to estimate and analyze the EB-HV right-turn conflict severity and drivers yielding behavior. The results reveal that: (a) right-turn warning facilities can decrease the probability of slight and severe EB-HV right-turn conflicts, while the presence of law enforcement cameras could prompt heavy vehicle drivers to comply with the yielding rules and adopt more cautious behavior; (b) increased heavy vehicle speed and acceleration before turning right have strong correlation to illegitimate yielding behavior of the driver and higher EB-HV right-turn conflict severity; and (c) aggressive behavior of e-bike rider increases the severe conflict probability, especially at intersections without right-turn warning facilities. Based on the study findings, several practical implications are suggested to reduce the risk of EB-HV right-turn conflicts, enhance the effectiveness of right-turn safety measures, and improve crossing safety for e-bike riders.
电动自行车骑手在交叉口遇到与自己同一方向右转的重型车辆是一个主要的安全隐患,这通常会导致严重的伤亡。最近,中国的一些城市在交叉口实施了右转安全改进措施(即右转让行规则和右转警示设施),以减少此类事故的发生。然而,电动自行车骑手和重型车辆驾驶员在右转交互过程中的风险感知和行为是动态变化的,不同右转安全措施的安全效果尚不清楚。本研究旨在探讨右转安全措施对信号交叉口电动自行车-重型车辆(EB-HV)右转冲突的安全效果。从航拍视频数据中提取右转冲突和潜在影响因素,包括右转警示设施的特点、电动自行车骑手和重型车辆驾驶员的特点和行为、环境因素以及与交通相关的因素。此外,还选择和计算了时间碰撞(TTC)、侵入后时间(PET)和急动度等交通冲突指标。采用多项和二项逻辑回归模型来估计和分析 EB-HV 右转冲突的严重程度和驾驶员让行行为。结果表明:(a)右转警示设施可以降低轻微和严重的 EB-HV 右转冲突的概率,而执法摄像头的存在可以促使重型车辆驾驶员遵守让行规则并采取更谨慎的行为;(b)重型车辆在右转前的速度和加速度增加与驾驶员不合法让行行为以及更高的 EB-HV 右转冲突严重程度有很强的相关性;(c)电动自行车骑手的激进行为增加了严重冲突的概率,特别是在没有右转警示设施的交叉口。基于研究结果,提出了一些实用建议,以降低 EB-HV 右转冲突的风险,提高右转安全措施的有效性,改善电动自行车骑手的通行安全。