Massachusetts Institute of Technology, Center for Transportation Logistics, AgeLab, Cambridge, Massachusetts.
Traffic Inj Prev. 2023;24(4):356-361. doi: 10.1080/15389588.2023.2189990. Epub 2023 Mar 29.
Advanced driver assistance systems are increasingly available in consumer vehicles, making the study of drivers' behavioral adaptation and the impact of automation beneficial for driving safety. Concerns over driver's being out-of-the-loop, coupled with known limitations of automation, has led research to focus on time-critical, system-initiated disengagements. This study used real-world data to assess drivers' response to, and recovery from, automation-initiated disengagements by quantifying changes in visual attention, vehicle control, and time to steady-state behaviors.
Fourteen drivers drove for one month each a Cadillac CT6 equipped with Super Cruise (SC), a partial automation system that, when engaged, enables hands-free driving. The vehicles were instrumented with data acquisition systems recording driving kinematics, automation use, GPS, and video. The dataset included 265 SC-initiated disengagements identified across 5,514 miles driven with SC.
Linear quantile mixed-effects models of glance behavior indicated that following SC-initiated disengagement, the proportions of glances to the Road decreased (Q50=0.91, Q50=0.69; Q85=1.0, Q85=0.79), the proportions of glances to the Instrument Cluster increased (Q50=0.14, Q50=0.25; Q85=0.34, Q85=0.45), and mean glance duration to the Road decreased by 4.86 sec in Q85. Multinomial logistic regression mixed-models of glance distributions indicated that the number of transitions between glance locations following disengagement increased by 43% and that glances were distributed across fewer locations. When driving hands-free, take over time was significantly longer (2.4 sec) compared to when driving with at least one hand on the steering wheel (1.8 sec). Analysis of moment-to-moment distributional properties of visual attention and steering wheel control following disengagement indicated that on average it took drivers 6.1 sec to start the recovery of glance behavior to the Road and 1.5 sec for trend-stationary proportions of at least one hand on the steering wheel.
Automation-initiated disengagements triggered substantial changes in driver glance behavior including shorter on-road glances and frequent transitions between Road and Instrument Cluster glance locations. This information seeking behavior may capture drivers' search for information related to the disengagement or the automation state and is likely shaped by the automation design. The study findings can inform the design of more effective driver-centric information displays for smoother transitions and faster recovery.
高级驾驶员辅助系统在消费车辆中越来越普及,因此研究驾驶员的行为适应和自动化的影响对于驾驶安全具有重要意义。由于担心驾驶员脱离驾驶状态,再加上对自动化的已知限制,研究人员将重点放在时间关键、系统发起的脱离上。本研究使用真实世界的数据来评估驾驶员对自动化引发的脱离的反应和恢复能力,方法是通过量化视觉注意力、车辆控制和稳定状态行为的时间变化来评估驾驶员的反应和恢复能力。
14 名驾驶员每人驾驶一辆配备超级巡航(Super Cruise,SC)的凯迪拉克 CT6 一个月,SC 是一种部分自动化系统,当启用时可以实现免提驾驶。车辆配备了数据采集系统,可记录驾驶运动学、自动化使用、GPS 和视频。数据集包括在配备 SC 的 5514 英里行驶里程中识别出的 265 次 SC 引发的脱离。
线性分位数混合效应模型的扫视行为分析表明,在 SC 引发的脱离后,扫视道路的比例减少(Q50=0.91,Q50=0.69;Q85=1.0,Q85=0.79),扫视仪表板的比例增加(Q50=0.14,Q50=0.25;Q85=0.34,Q85=0.45),道路的平均扫视时间减少了 4.86 秒,Q85 中的秒数。扫视分布的多项逻辑回归混合模型分析表明,脱离后扫视位置的转换次数增加了 43%,扫视分布的位置减少了。当免提驾驶时,接管时间明显更长(2.4 秒),而至少有一只手放在方向盘上时接管时间更短(1.8 秒)。脱离后对视觉注意力和方向盘控制的瞬间分布特性的分析表明,驾驶员平均需要 6.1 秒才能开始恢复对道路的扫视行为,需要 1.5 秒才能达到至少一只手放在方向盘上的稳定趋势比例。
自动化引发的脱离会引发驾驶员扫视行为的重大变化,包括在道路上的扫视时间更短,以及在道路和仪表板扫视位置之间的频繁转换。这种寻求信息的行为可能会捕捉到驾驶员对脱离或自动化状态的信息搜索,并且很可能是由自动化设计塑造的。研究结果可以为更有效的以驾驶员为中心的信息显示提供信息,以实现更平稳的过渡和更快的恢复。