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Driving performance, sleepiness, fatigue, and mental workload throughout the time course of semi‐automated driving—Experimental data from the driving simulator
Human Factors and Ergonomics in Manufacturing ( IF 2.4 ) Pub Date : 2020-10-14 , DOI: 10.1002/hfm.20875
Sylwia I. Kaduk 1 , Aaron P. J. Roberts 1 , Neville A. Stanton 1
Affiliation  

Automation offers the potential to mitigate or reduce the risks related to driving. There are some new challenges for drivers related to semi‐automated driving. Some of them are associated with suboptimal mental workload or prolonged need for sustained attention. This paper presents the results of an experiment investigating differences in manual driving before and after the automated phase in the scenario simulating a time‐course of semi‐automated driving. Sample size: 52 participants with two experimental sessions each day and night session. The experiment used a driving simulator to create a semi‐automated driving scenario comprising manual driving, the automated phase, and manual driving. The following questionnaires were collected: Karolinska Sleepiness Scale, Take‐Over Readiness Scale (developed for this research project, included in Appendix), Samn–Perelli Fatigue Scale, and NASA‐TLX. Driving performance significantly decreased after the automated phase (e.g., standard deviation of the steering wheel angle was 255.73 before vs. 287.11 after automation) and the effect was more profound during the night. Participants were sleepier and more fatigued after the automated phase, and assessed mental workload as lower. The results of the questionnaires did not correlate with driving performance. The results of the experiment suggest that manual driving could deteriorate after the automated phase, and that driver might not be able to assess their fitness to drive at the moment of take‐over of manual driving.

中文翻译:

在半自动驾驶的整个过程中,驾驶性能,困倦,疲劳和精神负担—来自驾驶模拟器的实验数据

自动化具有减轻或降低驾驶相关风险的潜力。与半自动驾驶相关的驾驶员面临一些新挑战。其中一些与精神工作量不足或长期需要持续关注有关。本文介绍了一个实验结果,该实验研究了在模拟半自动驾驶的时间过程中自动驾驶阶段之前和之后的手动驾驶差异。样本量:52名参与者,每天晚上进行两次实验。该实验使用驾驶模拟器创建了半自动驾驶场景,包括手动驾驶,自动阶段和手动驾驶。收集了以下问卷:Karolinska嗜睡量表,接管准备量表(针对该研究项目而开发,包括在附录中),Samn-Perelli疲劳量表和NASA-TLX。在自动化阶段之后,驾驶性能显着下降(例如,方向盘角的标准偏差为255.73,而自动化之后为287.11),并且在夜间效果更为明显。自动化阶段后,参与者更加困倦和疲劳,并评估了其精神工作量较低。问卷调查的结果与驾驶成绩无关。实验结果表明,在自动驾驶阶段之后,手动驾驶可能会恶化,并且在接管手动驾驶时,驾驶员可能无法评估自己的驾驶适应性。方向盘转角的标准偏差为255.73,而自动化后为287.11),夜间效果更为明显。自动化阶段后,参与者更加困倦和疲劳,并评估了其精神工作量较低。问卷调查的结果与驾驶成绩无关。实验结果表明,在自动驾驶阶段之后,手动驾驶可能会恶化,并且在接管手动驾驶时,驾驶员可能无法评估自己的驾驶适应性。方向盘转角的标准偏差为255.73,而自动化后为287.11),夜间效果更为明显。自动化阶段后,参与者更加困倦和疲劳,并评估了其精神工作量较低。问卷调查的结果与驾驶成绩无关。实验结果表明,在自动驾驶阶段之后,手动驾驶可能会恶化,并且在接管手动驾驶时,驾驶员可能无法评估自己的驾驶适应性。
更新日期:2020-12-20
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