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Driver Inattention During Vehicle Automation: How Does Driver Engagement Affect Resumption Of Control?

机译:车辆自动化期间驾驶员疏忽:驾驶员参与如何影响恢复控制?

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摘要

This driving simulator study, conducted as part of the EC-funded AdaptIVe project, investigated the effect of level of distraction during automation (Level 2 SAE) on drivers’ ability to assess automation uncertainty and react to a potential collision scenario. Drivers’ attention to the road was varied during automation in one of two driving screen manipulation conditions: occlusion by light fog and occlusion by heavy fog. Vehicle-based measures, drivers’ eye movements and response profiles to events after an automation uncertainty period were measured during a highly automated drive containing one of these manipulations, and compared to manual driving. In two of seven uncertainty events, a lead vehicle braked, causing a critical situation. Drivers' reactions to these critical events were compared in a between-subjects design, where the driving scene was manipulated for 1.5 minutes. Results showed that, during automation, drivers’ response profile to a potential collision scenario was less controlled and more aggressive immediately after the transition, compared to when they were in manual control. With respect to screen manipulation in particular, drivers in the heavy fog condition collided with the lead vehicle more often and also had a lower minimum headway compared to those in the light fog condition.
机译:作为EC资助的AdaptIVe项目的一部分进行的这项驾驶模拟器研究,研究了自动化过程中的注意力分散程度(2级SAE)对驾驶员评估自动化不确定性和对潜在碰撞情况做出反应的能力的影响。在自动驾驶过程中,驾驶员在两种驾驶屏幕操纵条件中对道路的关注程度有所不同:轻雾遮挡和大雾遮挡。在包含这些操作之一的高度自动化驾驶过程中,测量了基于车辆的测量,驾驶员的眼球运动以及对自动化不确定期后事件的响应曲线,并将其与手动驾驶进行了比较。在七个不确定性事件中的两个中,领先车辆制动,从而导致严重情况。在受试者之间的设计中比较了驾驶员对这些关键事件的反应,在该设计中,驾驶场景被操纵了1.5分钟。结果表明,在自动化过程中,与手动控制相比,驾驶员在过渡后对潜在碰撞场景的响应曲线受到的控制较少,并且更具攻击性。特别是在屏幕操作方面,重雾条件下的驾驶员与领头车辆发生碰撞的频率更高,并且与轻雾条件下的驾驶员相比,其最小前进距离也更低。

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