Automotive Human Factors Research Center, National Institute of Advanced Industrial Science and Technology, Japan.
Automotive Human Factors Research Center, National Institute of Advanced Industrial Science and Technology, Japan.
J Safety Res. 2020 Feb;72:231-238. doi: 10.1016/j.jsr.2019.12.019. Epub 2020 Jan 13.
During SAE level 3 automated driving, the driver's role changes from active driver to fallback-ready driver. Drowsiness is one of the factors that may degrade driver's takeover performance. This study aimed to investigate effects of non-driving related tasks (NDRTs) to counter driver's drowsiness with a Level 3 system activated and to improve successive takeover performance in a critical situation. A special focus was placed on age-related differences in the effects.
Participants of three age groups (younger, middle-aged, older) drove the Level 3 system implemented in a high-fidelity motion-based driving simulator for about 30 min under three experiment conditions: without NDRT, while watching a video clip, and while switching between watching a video clip and playing a game. The Karolinska Sleepiness Scale and eyeblink duration measured driver drowsiness. At the end of the drive, the drivers had to take over control of the vehicle and manually change the lane to avoid a collision. Reaction time and steering angle variability were measured to evaluate the two aspects of driving performance.
For younger drivers, both single and multiple NDRT engagements countered the development of driver drowsiness during automated driving, and their takeover performance was equivalent to or better than their performance without NDRT engagement. For older drivers, NDRT engagement did not affect the development of drowsiness but degraded takeover performance especially under the multiple NDRT engagement condition. The results for middle-aged drivers fell at an intermediate level between those for younger and older drivers. Practical Applications: The present findings do not support general recommendations of NDRT engagement to counter drowsiness during automated driving. This study is especially relevant to the automotive industry's search for options that will ensure the safest interfaces between human drivers and automation systems.
在 SAE 级别 3 自动驾驶中，驾驶员的角色从主动驾驶员转变为待命驾驶员。困倦是可能降低驾驶员接管性能的因素之一。本研究旨在探讨在激活 3 级系统的情况下，非驾驶相关任务 (NDRT) 如何对抗驾驶员困倦，并在危急情况下提高后续接管性能。特别关注年龄相关差异的影响。
三个年龄组（年轻、中年、老年）的参与者在高保真基于运动的驾驶模拟器中驾驶 3 级系统约 30 分钟，在三种实验条件下：无 NDRT、观看视频剪辑和在观看视频剪辑和玩游戏之间切换。通过卡氏睡眠量表和眨眼持续时间测量驾驶员的困倦程度。在驾驶结束时，驾驶员必须接管车辆控制并手动变道以避免碰撞。测量反应时间和转向角度变化来评估驾驶性能的两个方面。
对于年轻驾驶员，单一和多种 NDRT 参与都可以抵消自动驾驶过程中驾驶员困倦的发展，并且他们的接管性能与不参与 NDRT 时的性能相当或更好。对于老年驾驶员，NDRT 参与并不会影响困倦的发展，但会降低接管性能，尤其是在多种 NDRT 参与的情况下。中年驾驶员的结果处于年轻和老年驾驶员之间的中间水平。
本研究结果不支持在自动驾驶过程中普遍建议使用 NDRT 来对抗困倦。本研究特别适用于汽车行业寻找确保人类驾驶员和自动化系统之间最安全接口的选项。
