Stephenson Alice C, Eimontaite Iveta, Caleb-Solly Praminda, Morgan Phillip L, Khatun Tabasum, Davis Joseph, Alford Chris
Health and Applied Sciences, University of the West of England, Bristol, United Kingdom.
Bristol Robotics Laboratory, University of the West of England, Bristol, United Kingdom.
Front Psychol. 2020 Sep 18;11:571961. doi: 10.3389/fpsyg.2020.571961. eCollection 2020.
Driving cessation for some older adults can exacerbate physical, cognitive, and mental health challenges due to loss of independence and social isolation. Fully autonomous vehicles may offer an alternative transport solution, increasing social contact and encouraging independence. However, there are gaps in understanding the impact of older adults' passive role on safe human-vehicle interaction, and on their well-being. 37 older adults (mean age ± SD = 68.35 ± 8.49 years) participated in an experiment where they experienced fully autonomous journeys consisting of a distinct stop (an unexpected event versus an expected event). The autonomous behavior of the vehicle was achieved using the Wizard of Oz approach. Subjective ratings of trust and reliability, and driver state monitoring including visual attention strategies (fixation duration and count) and physiological arousal (skin conductance and heart rate), were captured during the journeys. Results revealed that subjective trust and reliability ratings were high after journeys for both types of events. During an unexpected stop, overt visual attention was allocated toward the event, whereas during an expected stop, visual attention was directed toward the human-machine interface (HMI) and distributed across the central and peripheral driving environment. Elevated skin conductance level reflecting increased arousal persisted only after the unexpected event. These results suggest that safety-critical events occurring during passive fully automated driving may narrow visual attention and elevate arousal mechanisms. To improve in-vehicle user experience for older adults, a driver state monitoring system could examine such psychophysiological indices to evaluate functional state and well-being. This information could then be used to make informed decisions on vehicle behavior and offer reassurance during elevated arousal during unexpected events.
对于一些老年人来说，停止驾驶可能会由于失去独立性和社会隔离而加剧身体、认知和心理健康方面的挑战。全自动驾驶车辆可能提供一种替代交通解决方案，增加社交接触并鼓励独立性。然而，在理解老年人在安全人车交互中的被动角色及其幸福感的影响方面存在差距。37名老年人（平均年龄±标准差=68.35±8.49岁）参与了一项实验，他们体验了由不同停车场景（意外事件与预期事件）组成的全自动旅程。车辆的自主行为采用奥兹巫师方法实现。在旅程中获取了信任和可靠性的主观评分，以及驾驶员状态监测数据，包括视觉注意力策略（注视持续时间和次数）和生理唤醒（皮肤电导率和心率）。结果显示，两种类型事件的旅程结束后，主观信任和可靠性评分都很高。在意外停车期间，明显的视觉注意力集中在事件上，而在预期停车期间，视觉注意力则指向人机界面（HMI）并分布在中央和周边驾驶环境中。反映唤醒增加的皮肤电导率水平仅在意外事件后持续升高。这些结果表明，在被动全自动驾驶过程中发生的安全关键事件可能会缩小视觉注意力范围并提高唤醒机制。为了改善老年人的车内用户体验，驾驶员状态监测系统可以检查此类心理生理指标，以评估功能状态和幸福感。然后，这些信息可用于对车辆行为做出明智决策，并在意外事件中唤醒增强时提供安慰。
