2860 Delft University of Technology, The Netherlands.
Hum Factors. 2020 Mar;62(2):211-228. doi: 10.1177/0018720819894757. Epub 2020 Jan 29.
We investigated a driver monitoring system (DMS) designed to adaptively back up distracted drivers with automated driving.
Humans are likely inadequate for supervising today's on-road driving automation. Conversely, backup concepts can use eye-tracker DMS to retain the human as the primary driver and use computerized control only if needed. A distraction DMS where perceived false alarms are minimized and the status of the backup is unannounced might reduce problems of distrust and overreliance, respectively. Experimental research is needed to assess the viability of such designs.
In a driving simulator, 91 participants either supervised driving automation (), drove with different forms of DMS-induced backup control (; ), or drove without any automation. All participants performed a visual N-back task throughout.
Supervised driving automation increased visual distraction and hazard non-responses compared to backup and conventional driving. improved response generation compared to . Across entire driving trials, the backup improved lateral performance compared to conventional driving. Without negatively impacting safety, the DMS reduced unnecessary automated control compared to the DMS conditions. produced low satisfaction ratings, whereas satisfaction was on par with automated driving. There were no appreciable negative consequences attributable to the driving automation.
We have demonstrated preliminary feasibility of DMS designs that incorporate driving context information for distraction assessment and suppress their status indication.
An appropriately designed DMS can enable benefits for automated driving as a backup.
我们研究了一种驾驶员监控系统（DMS），旨在通过自动化驾驶来辅助分心的驾驶员。
人类可能不足以监督当今道路上的驾驶自动化。相反，备用方案可以使用眼动追踪 DMS 来保持人类作为主要驾驶员，并仅在需要时使用计算机控制。感知虚假警报最小化且备用状态不公开的分心 DMS 可能分别减少不信任和过度依赖的问题。需要进行实验研究来评估此类设计的可行性。
在驾驶模拟器中，91 名参与者要么监督自动驾驶（），要么在不同形式的 DMS 诱导备份控制下驾驶（; ），要么在没有任何自动化的情况下驾驶。所有参与者在整个过程中都执行了视觉 N 回任务。
与备份和常规驾驶相比，监督自动驾驶增加了视觉干扰和危险无响应。与 相比， 提高了响应生成能力。在整个驾驶试验中，备份比常规驾驶提高了横向性能。在不影响安全性的情况下，与 相比， 减少了不必要的自动化控制。产生了较低的满意度评分，而 与自动驾驶的满意度相当。没有可归因于 自动驾驶的明显负面影响。
我们已经初步证明了将驾驶情境信息纳入分心评估并抑制其状态指示的 DMS 设计的可行性。
设计得当的 DMS 可以为自动化驾驶作为备份提供好处。
