探索右转安全措施对信号灯控制交叉路口电动自行车与重型车辆冲突的影响

IF 5.7 1区 工程技术 Q1 ERGONOMICS
Chenxiao Zhang , Yongfeng Ma , Tarek Sayed , Yanyong Guo , Shuyan Chen , Yuanhang Fu
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引用次数: 0

摘要

电动自行车骑行者在通过交叉路口时的一个主要安全隐患是遇到同方向右转的重型车辆,这往往会造成严重的人员伤亡。最近,中国一些城市在交叉路口实施了右转安全改善措施(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,在右转互动过程中,电动自行车骑行者和重型汽车驾驶者的风险认知和行为会发生动态变化,不同右转安全措施的安全效果尚不明确。本研究旨在探讨右转安全措施对电动自行车-重型车辆(EB-HV)在信号灯控制交叉口右转冲突的安全影响。研究从航拍视频数据中提取右转冲突及潜在影响因素,包括右转警示设施的特征、电动自行车骑行者和重型车辆驾驶者的特征和行为、环境因素以及交通相关因素。此外,还选取并计算了交通冲突指标,如碰撞时间(TTC)、碰撞后时间(PET)和挤压(Jerk)。采用多项式和二元对数模型对 EB-HV 右转冲突严重程度和驾驶员让行行为进行估计和分析。结果显示(a) 右转警告设施可降低轻微和严重的 EB-HV 右转冲突概率,而执法摄像头的存在可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) 重型车辆右转前车速和加速度的增加与驾驶员的不正当让行行为和更高的 EB-HV 右转冲突严重性密切相关;(c) 电动自行车骑行者的攻击性行为会增加严重冲突的概率,尤其是在没有右转警告设施的交叉路口。根据研究结果,我们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,并改善电动自行车骑行者的过街安全。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the impact of right-turn safety measures on E-bike-heavy vehicle conflicts at signalized intersections

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.

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来源期刊
CiteScore
11.90
自引率
16.90%
发文量
264
审稿时长
48 days
期刊介绍: Accident Analysis & Prevention provides wide coverage of the general areas relating to accidental injury and damage, including the pre-injury and immediate post-injury phases. Published papers deal with medical, legal, economic, educational, behavioral, theoretical or empirical aspects of transportation accidents, as well as with accidents at other sites. Selected topics within the scope of the Journal may include: studies of human, environmental and vehicular factors influencing the occurrence, type and severity of accidents and injury; the design, implementation and evaluation of countermeasures; biomechanics of impact and human tolerance limits to injury; modelling and statistical analysis of accident data; policy, planning and decision-making in safety.
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