Research Centre for Territory, Transports and Environment, University of Porto, Rua Doutor Roberto Frias s/n, Porto, Portugal.
Research Centre for Territory, Transports and Environment, University of Porto, Rua Doutor Roberto Frias s/n, Porto, Portugal.
Accid Anal Prev. 2023 Oct;191:107201. doi: 10.1016/j.aap.2023.107201. Epub 2023 Jul 22.
The human-environment-vehicle triad and how it relates to crashes has long been a topic of discussion, in which the human factor is consistently seen as the leading cause. Recently, more sophisticated approaches to Road Safety have advocated for a road-driver interaction view, in which human characteristics influence road perception and road environment affects driver behavior. This study focuses on road-driver interaction by using a driving simulator. The objective is to investigate how the driver profile influences driving performance and the effects of three countermeasures (peripheral transverse lines before and after the beginning of the curves and roadside poles in the curves). Fifty-six middle-aged male participants drove a non-challenging rural highway simulated scenario based on a real road where many single-vehicle crashes occurred. The drivers' profiles were assessed through their behavioral history measured by a validated version of the Driver Behavior Questionnaire (DBQ) comprising three dimensions: Errors (E), Ordinary Violations (OV), and Aggressive Violations (AV). The relationship between speed and trajectory measures and drivers' profiles was investigated using random-parameter models with heterogeneity in the means. The models' results showed that the DBQ subscale scores in OV explained a considerable part of the heterogeneity found in drivers' performance. Furthermore, the heterogeneity in the means caused by the DBQ subscale scores in OV and E in the presence of peripheral transverse lines indicates a difference in how drivers react to the countermeasures. The peripheral lines were more efficient than roadside poles to moderate speed but did not positively influence all drivers' trajectories. Although the peripheral lines could be seen as an alternative to change driver behavior in a non-challenging or monotonous road environment, the design used in this study should be reviewed.
人机环境三联体及其与事故的关系一直是讨论的主题,其中人为因素一直被视为主要原因。最近,更复杂的道路安全方法提倡道路-驾驶员交互的观点,其中人的特征影响道路感知,道路环境影响驾驶员行为。本研究通过驾驶模拟器关注道路-驾驶员交互。目的是研究驾驶员特征如何影响驾驶性能以及三种对策(曲线起点和终点的外围横向线和曲线中的路边杆)的影响。56 名中年男性参与者根据一条真实道路上发生过许多单车事故的模拟场景,驾驶非挑战性的农村公路。通过对驾驶员行为问卷(DBQ)的验证版本进行行为历史评估来评估驾驶员的特征,该问卷由三个维度组成:错误(E)、普通违规(OV)和攻击性违规(AV)。使用具有均值异质性的随机参数模型研究了速度和轨迹测量值与驾驶员特征之间的关系。模型结果表明,OV 中的 DBQ 子量表分数解释了驾驶员性能中发现的异质性的很大一部分。此外,在存在外围横向线的情况下,由 OV 和 E 的 DBQ 子量表分数引起的均值异质性表明驾驶员对对策的反应存在差异。外围线比路边杆更有效地降低速度,但并不影响所有驾驶员的轨迹。虽然外围线可以被视为改变非挑战性或单调道路环境中驾驶员行为的一种替代方法,但应审查本研究中使用的设计。