He Yi, Sun Changxin, Chang Fangrong
Intelligent Transportation Research Center, Wuhan University of Technology, Wuhan, China.
School of Resources and Safety Engineering, Central South University, Changsha, China.
Accid Anal Prev. 2023 May;184:107013. doi: 10.1016/j.aap.2023.107013. Epub 2023 Feb 28.
The delivery industry has seen dramatic growth in demand and scale in China. Due to the stock limitations and delivery time restrictions, the couriers may commit traffic violations while delivering, resulting in a pessimistic road safety situation. This study aims to reveal critical factors that influence delivery vehicle crash risks. A cross-sectional structured questionnaire survey is conducted to collect demographic attributes, workload, work emotions, risky driving behavior, and road crash involvement data among 824 couriers in three developed regions of China. The collected data is then analyzed through an established path model to identify the contributing factors of delivery road crash risks and risky behaviors. The road crash risk level (RCRL) indicator is defined by taking into consideration both frequency and severity. While the risky behaviors are defined by both their frequency and correlations to crash risks. The results indicate that 1) Beijing-Tianjin Urban Agglomeration has the highest road crash frequency and RCRL; 2) distracted driving and wrong-lane-use are among the top three risky behaviors for both Yangtze River Delta Urban Agglomeration and Pearl River Delta Urban Agglomeration. For Beijing-Tianjin Urban Agglomeration, distracted driving, aggressive driving, and lack of protection are the top three risky behaviors; 3) time demand and personal efforts are important factors contributing to the cognitive workload of couriers; 4) objective workload can affect the cognitive workload and both workloads influence drivers' emotions (anxiety and anger); 5) the objective, cognitive workload, drivers' emotions influence the RCRL through their impacts on risky behavior but in different paths for three agglomerations. The findings highlight the importance of developing targeted countermeasures to reduce the delivery workers' workload, improve their performance on roads, and mitigate severe crash risks.
中国快递行业的需求和规模急剧增长。由于库存限制和配送时间限制,快递员在配送过程中可能会违反交通规则,导致道路安全形势不容乐观。本研究旨在揭示影响配送车辆碰撞风险的关键因素。在中国三个发达地区对824名快递员进行了横断面结构化问卷调查,收集他们的人口统计学特征、工作量、工作情绪、危险驾驶行为和道路碰撞事故参与数据。然后通过一个既定的路径模型对收集到的数据进行分析,以确定导致配送道路碰撞风险和危险行为的因素。道路碰撞风险水平(RCRL)指标是通过考虑频率和严重程度来定义的。而危险行为则是根据其频率以及与碰撞风险的相关性来定义的。结果表明:1)京津冀城市群的道路碰撞频率和RCRL最高;2)分心驾驶和走错车道是长三角城市群和珠三角城市群的三大危险行为之一。对于京津冀城市群来说,分心驾驶、攻击性驾驶和缺乏防护是三大危险行为;3)时间需求和个人努力是导致快递员认知工作量的重要因素;4)客观工作量会影响认知工作量,且两种工作量都会影响驾驶员的情绪(焦虑和愤怒);5)客观、认知工作量、驾驶员情绪通过对危险行为的影响来影响RCRL,但在三个城市群中路径不同。研究结果凸显了制定针对性对策以减轻快递员工作量、提高他们在道路上的表现并降低严重碰撞风险的重要性。