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首页> 外文期刊>Applied Ergonomics >Effects of cognitive and visual loads on driving performance after take-over request (TOR) in automated driving
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Effects of cognitive and visual loads on driving performance after take-over request (TOR) in automated driving

机译:认知和视觉载荷对自动驾驶中接收要求(TOR)后驾驶性能的影响

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摘要

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.
机译:本研究研究了认知和视觉载荷对自动驾驶任务中接管请求(TOR)后的驾驶性能的影响。参与者在没有非驾驶相关任务的情况下在驾驶模拟器中完成自动驾驶,具有轻松的非驾驶相关任务,并且具有困难的非驾驶相关任务。主要任务是监控环境和系统状态。 N背部任务和代理参考任务(Surt)分别适用于引起认知和视觉载荷。系统自动跟随前车。通过对自动化系统发出的TOR然后终止后,通过对临界事件(破碎汽车的外观)进行响应来测量驱动性能。 N-Back任务的高主观难度与从转向控制到车道变化的时间过程中的时间过程中的高度和增加的转向角度方差,而Surt的高主观难度与时间顺利的转向角度方差增加车道改变。这表明,在自动驾驶中,认知和视觉负载都会影响驾驶性能,但效果出现在不同的时间课程中。

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