Institute for Transport Studies, University of Leeds, Leeds, UK.
Inj Prev. 2017 Aug;23(4):281-286. doi: 10.1136/injuryprev-2016-042155. Epub 2016 Sep 21.
A proposed advantage of vehicle automation is that it relieves drivers from the moment-to-moment demands of driving, to engage in other, non-driving related, tasks. However, it is important to gain an understanding of drivers' capacity to resume manual control, should such a need arise. As automation removes vehicle control-based measures as a performance indicator, other metrics must be explored.
This driving simulator study, conducted under the European Commission (EC) funded AdaptIVe project, assessed drivers' gaze fixations during partially-automated (SAE Level 2) driving, on approach to critical and non-critical events. Using a between-participant design, 75 drivers experienced automation with one of five out-of-the-loop (OOTL) manipulations, which used different levels of screen visibility and secondary tasks to induce varying levels of engagement with the driving task: 1) no manipulation, 2) manipulation by light fog, 3) manipulation by heavy fog, 4) manipulation by heavy fog plus a visual task, 5) no manipulation plus an n-back task.
The OOTL manipulations influenced drivers' first point of gaze fixation after they were asked to attend to an evolving event. Differences resolved within one second and visual attention allocation adapted with repeated events, yet crash outcome was not different between OOTL manipulation groups. Drivers who crashed in the first critical event showed an erratic pattern of eye fixations towards the road centre on approach to the event, while those who did not demonstrated a more stable pattern.
Automated driving systems should be able to direct drivers' attention to hazards no less than 6 seconds in advance of an adverse outcome.
车辆自动化的一个被提议的优势是，它可以让驾驶员从驾驶的瞬间需求中解脱出来，从事其他与驾驶无关的任务。然而，了解驾驶员在需要时重新恢复手动控制的能力是很重要的。由于自动化将车辆控制相关的措施从性能指标中去除，因此必须探索其他指标。
这项在欧盟委员会（EC）资助的自适应项目下进行的驾驶模拟器研究，评估了驾驶员在部分自动化（SAE 级别 2）驾驶时，接近关键和非关键事件时的注视固定点。使用参与者之间的设计，75 名驾驶员经历了五种不同的脱离环路（OOTL）操作的自动化，这些操作使用了不同的屏幕可见度和二级任务，以诱导对驾驶任务的不同程度的参与：1）无操作，2）轻度雾操作，3）重度雾操作，4）重度雾加视觉任务操作，5）无操作加 n-back 任务操作。
OOTL 操作影响了驾驶员在被要求关注不断变化的事件后第一次注视的焦点。差异在一秒内解决，视觉注意力分配随着重复事件而适应，但 OOTL 操作组之间的碰撞结果没有不同。在第一个关键事件中发生碰撞的驾驶员在接近事件时，眼睛注视点的模式不稳定，而没有发生碰撞的驾驶员则表现出更稳定的模式。
自动化驾驶系统应该能够在不利结果发生前至少 6 秒将驾驶员的注意力引导到危险上。
