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A novel driver hazard perception sensitivity model based on drivers' characteristics: A simulator study

机译:一种基于驱动因素特征的新型驾驶员危害感觉敏感模型:模拟器研究

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Objective: Considering the high annual number of fatal driving accidents in Iran, any approach for reducing the number or severity of driving accidents is a positive step toward decreasing accident-related losses. Accidents can often be avoided by a timely reaction of the driver. One of the steps before reacting to a hazard is perception. Some driver characteristics may affect road hazard perception. In this research, it was assumed that various driver characteristics, including demographic characteristics and cognitive characteristics, have an impact on driver perception.Methods: The driving simulator used in this research provides various scenarios; for example, passing a pedestrian or animal across the road or placing fixed objects in a 2-lane separated rural road for 2 groups of experienced and inexperienced drivers under day and night lighting conditions. The go/no-go test was carried out in order to assess drivers' attention to driving tasks and inhibitory control. A structural equation model (SEM) was used to estimate the relation between driver characteristics and sensitivity to road hazard perception. A new hazard perception index was proposed based on the time intervals in the hazard vulnerability.Results: The results show that the most effective variables in the analysis of sensitivity to hazard perception are driving experience (in kilometers) during the last 3 years and road lighting conditions. Moreover, hazard perception sensitivity was improved by better inhibitory control, selective attention, and decision making, more carefulness, the average amount of daily sleep, and marital status.Conclusion: The results of this research may be useful in educating and advertising programs. It also could enhance sensitivity to perception of hazards such as pedestrians, animals, and fixed obstacles among young and novice drivers.
机译:目标:考虑到伊朗每年发生的致命驾驶事故数量很高,任何减少驾驶事故数量或严重程度的方法都是减少事故相关损失的积极步骤。司机的及时反应往往可以避免事故。对危险做出反应之前的一个步骤是感知。一些驾驶员特征可能会影响道路危险感知。在本研究中,假设各种驾驶员特征,包括人口统计特征和认知特征,对驾驶员感知有影响。方法:本研究中使用的驾驶模拟器提供各种场景;例如,在白天和夜间照明条件下,让两组经验丰富和缺乏经验的驾驶员穿过道路,或在两车道分隔的乡村道路上放置固定物体。为了评估驾驶员对驾驶任务和抑制性控制的注意力,进行了通过/不通过测试。采用结构方程模型(SEM)评估驾驶员特征与道路危险感知敏感性之间的关系。基于危险脆弱性的时间间隔,提出了一种新的危险感知指数。结果:结果表明,在危险感知敏感性分析中,最有效的变量是过去3年的驾驶经验(以公里为单位)和道路照明条件。此外,通过更好的抑制控制、选择性注意和决策、更谨慎、每日平均睡眠量和婚姻状况,危险感知敏感性得到了改善。结论:本研究的结果可能对教育和广告项目有用。它还可以提高年轻和新手驾驶者对行人、动物和固定障碍物等危险感知的敏感性。

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