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认知和视觉负荷对自动驾驶接管请求(TOR)后驾驶性能的影响。

Effects of cognitive and visual loads on driving performance after take-over request (TOR) in automated driving.

机构信息

Automotive Human Factors Research Center, National Institute of Advanced Industrial Science and Technology, Japan; Research Center for Child Mental Development, Hamamatsu University School of Medicine, Japan.

Automotive Human Factors Research Center, National Institute of Advanced Industrial Science and Technology, Japan.

出版信息

Appl Ergon. 2020 May;85:103074. doi: 10.1016/j.apergo.2020.103074. Epub 2020 Feb 14.

Abstract

The present study investigated effects of cognitive and visual loads on driving performance after take-over request (TOR) in an automated driving task. Participants completed automated driving in a driving simulator without a non-driving related task, with an easy non-driving related task, and with a difficult non-driving related task. The primary task was to monitor the environment and the system state. An N-back task and a Surrogate Reference Task (SuRT) were adapted to induce cognitive and visual loads respectively. The system followed a front vehicle automatically. Driving performance was measured by responses to a critical event (appearance of a broken-down car) after the automated system issued TOR and then terminated. High subjective difficulty of the N-back task was related to increased time and increased steering angle variance in the time course from onset of steering control to lane change, while high subjective difficulty of SuRT was related to increased steering angle variance in the time course after lane change. This suggests that both cognitive and visual loads affect driving performance after TOR in automated driving, but the effects appear in different time courses.

摘要

本研究调查了在自动驾驶任务中的接管请求(TOR)后,认知和视觉负荷对驾驶表现的影响。参与者在驾驶模拟器中完成自动驾驶,分别在没有非驾驶相关任务、有简单非驾驶相关任务和有困难非驾驶相关任务的情况下进行实验。主要任务是监测环境和系统状态。采用 N-back 任务和替代参考任务(SuRT)分别来诱发认知和视觉负荷。系统自动跟随前车。驾驶表现通过对一个关键事件(一辆抛锚的汽车的出现)的反应来测量,这个关键事件发生在自动化系统发出 TOR 并随后终止之后。N-back 任务的高主观难度与从开始转向控制到变道的时间过程中的转向角度方差增加有关,而 SuRT 的高主观难度与变道后的时间过程中的转向角度方差增加有关。这表明,在自动驾驶中的 TOR 后,认知和视觉负荷都会影响驾驶表现,但影响出现在不同的时间过程中。

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