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Coming back into the loop: Drivers' perceptual-motor performance in critical events after automated driving

机译:回到循环中:自动驾驶后关键事件中驾驶员的感知运动性能

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This driving simulator study, conducted as part of the EU AdaptIVe project, investigated drivers' performance in critical traffic events, during the resumption of control from an automated driving system. Prior to the critical events, using a between-participant design, 75 drivers were exposed to various screen manipulations that varied the amount of available visual information from the road environment and automation state, which aimed to take them progressively further 'out-of-the-loop' (OoTL). The current paper presents an analysis of the timing, type, and rate of drivers' collision avoidance response, also investigating how these were influenced by the criticality of the unfolding situation. Results showed that the amount of visual information available to drivers during automation impacted on how quickly they resumed manual control, with less information associated with slower take-over times, however, this did not influence the timing of when drivers began a collision avoidance manoeuvre. Instead, the observed behaviour is in line with recent accounts emphasising the role of scenario kinematics in the timing of driver avoidance response. When considering collision incidents in particular, avoidance manoeuvres were initiated when the situation criticality exceeded an Inverse Time To Collision value of approximate to 0.3 s(-1). Our results suggest that take-over time and timing and quality of avoidance response appear to be largely independent, and while long take-over time did not predict collision outcome, kinematically late initiation of avoidance did. Hence, system design should focus on achieving kinematically early avoidance initiation, rather than short take-over times.
机译:这项驾驶模拟器研究是EU AdaptIVe项目的一部分,在从自动驾驶系统恢复控制的过程中,研究了驾驶员在关键交通事件中的表现。在关键事件发生之前,使用参与者之间的设计,使75位驾驶员受到了各种屏幕操作的控制,这些屏幕操作改变了道路环境和自动化状态下可用的可视信息量,旨在使他们逐渐“脱离现实”。 -loop”(OoTL)。当前的论文对驾驶员避撞反应的时机,类型和速率进行了分析,并研究了这些因素如何受到展开情况的严重性的影响。结果表明,驾驶员在自动化过程中可用的视觉信息量会影响他们恢复手动控制的速度,而与接管时间变慢相关的信息会减少,但是,这不会影响驾驶员开始避撞动作的时间。取而代之的是,观察到的行为与最近的描述相符,后者强调了情景运动学在驾驶员回避响应时机中的作用。特别是在考虑碰撞事件时,当情况危急程度超过“接近碰撞的反向时间”值大约为0.3 s(-1)时,便开始回避操作。我们的研究结果表明,接管时间,避免反应的时间和质量在很大程度上是独立的,尽管较长的接管时间无法预测碰撞的结果,但从运动学上讲,避开的延迟确实可以。因此,系统设计应着眼于运动学上的早期回避启动,而不是短的接管时间。

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