Department of Psychology, University of Groningen, Groningen, the Netherlands; BMW Group Research and Development, Munich, Germany.
Department of Psychology, University of Groningen, Groningen, the Netherlands.
Accid Anal Prev. 2021 Nov;162:106397. doi: 10.1016/j.aap.2021.106397. Epub 2021 Sep 24.
In the current study we investigated if drivers of conditionally automated vehicles can be kept in the loop through lane change maneuvers. More specifically, we examined whether involving drivers in lane-changes during a conditionally automated ride can influence critical take-over behavior and keep drivers' gaze on the road. In a repeated measures driving simulator study (n = 85), drivers drove the same route three times, each trial containing four lane changes that were all either (1) automated, (2) semi-automated or (3) manual. Each ride ended with a critical take-over situation that could be solved by braking and/or steering. Critical take-over reactions were analyzed with a linear mixed model and parametric accelerated failure time survival analysis. As expected, semi-automated and manual lane changes throughout the ride led to 13.5% and 17.0% faster maximum deceleration compared to automated lane changes. Additionally, semi-automated and manual lane changes improved the quality of the take-over by significantly decreasing standard deviation of the steering wheel angle. Unexpectedly, drivers in the semi-automated condition were slowest to start the braking maneuver. This may have been caused by the drivers' confusion as to how the semi-automated system would react. Additionally, the percentage gaze off-the-road was significantly decreased by the semi-automated (6.0%) and manual (6.6%) lane changes. Taken together, the results suggest that semi-automated and manual transitions may be an alarm-free instrument which developers could use to help maintain drivers' perception-action loop and improve automated driving safety.
在当前的研究中，我们研究了条件自动化车辆的驾驶员是否可以通过变道操作保持在循环中。更具体地说，我们研究了在有条件的自动驾驶过程中让驾驶员参与变道操作是否会影响关键接管行为，并使驾驶员保持对道路的关注。在一项重复测量驾驶模拟器研究（n=85）中，驾驶员三次驾驶相同的路线，每次试验包含四个变道，分别为（1）自动、（2）半自动或（3）手动。每次骑行都以一个关键的接管情况结束，可以通过刹车和/或转向来解决。通过线性混合模型和参数加速失效时间生存分析来分析关键接管反应。正如预期的那样，整个骑行过程中的半自动和手动变道导致最大减速度分别比自动变道快 13.5%和 17.0%。此外，半自动和手动变道通过显著降低转向盘角度的标准差，提高了接管的质量。出乎意料的是，半自动条件下的驾驶员启动制动操作最慢。这可能是由于驾驶员对半自动系统的反应感到困惑。此外，半自动（6.0%）和手动（6.6%）变道显著降低了驾驶员视线离开道路的百分比。总的来说，研究结果表明，半自动和手动过渡可能是一种无警报的工具，开发人员可以使用它来帮助保持驾驶员的感知-动作循环，并提高自动驾驶的安全性。
