College of Engineering, Zhejiang Normal University, 688 Yingbin Road, Jinhua, 321004, China; Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Province, Zhejiang Normal University, Zhejiang, 321005, China.
College of Engineering, Zhejiang Normal University, 688 Yingbin Road, Jinhua, 321004, China.
J Safety Res. 2024 Jun;89:262-268. doi: 10.1016/j.jsr.2024.04.004. Epub 2024 Apr 22.
Speeding behavior is a major threat to road traffic safety, which can increase crash risks and result in severe injury outcomes. Although several studies have been conducted to analyze speeding crashes and relevant influential factors, the heterogeneity of variables has not been fully explored. Based on the traffic crash data extracted from the Crash Report Sampling System, the study aims to identify the factors that influence speeding driving with the consideration of variable heterogeneity.
Quasi-induced exposure technique is adopted to identify the disparities in the propensities of speeding for various driving cohorts. The random parameter logit model with heterogeneity in means is employed to examine the factors impacting speeding behavior.
Results indicate that: (a) driving cohorts such as young drivers, male drivers, passenger cars, and pickups appear to have higher propensities of engaging in speeding driving; (b) the propensity of speeding is higher when the driver is drinking, distracted, changing lanes, negotiating a curve, driving in lighted condition, and on curved roads; and (c) the random parameter logit model with heterogeneity in means has better performance as opposed to that without heterogeneity in means.
Speeding behavior can be influenced by various factors in terms of driver-vehicle characteristics, physical condition, driving actions, and environmental conditions.
The findings could serve to develop effective countermeasures to reduce speeding behavior and improve traffic safety.
超速行为是道路交通安全的一大威胁，它会增加事故风险，导致严重的伤害后果。尽管已经有多项研究分析了超速事故和相关影响因素，但变量的异质性尚未得到充分探讨。本研究基于从碰撞报告抽样系统中提取的碰撞数据，旨在考虑变量异质性的情况下，确定影响超速驾驶的因素。
采用拟诱导暴露技术来识别不同驾驶群体超速倾向的差异。采用均值异质的随机参数对数模型来检验影响超速行为的因素。
结果表明：（a）年轻驾驶员、男性驾驶员、乘用车和皮卡等驾驶群体似乎更倾向于超速驾驶；（b）驾驶员饮酒、分心、变道、弯道行驶、在有照明条件下行驶以及在弯道行驶时，超速的倾向更高；（c）均值异质的随机参数对数模型的表现优于无均值异质的随机参数对数模型。
超速行为可能受到驾驶员-车辆特征、身体状况、驾驶行为和环境条件等多种因素的影响。
这些发现可以为制定有效措施减少超速行为和提高交通安全提供参考。
