Institute for Transport Studies, University of Leeds, Leeds LS2 9JT, UK.
Hum Factors. 2012 Oct;54(5):762-71. doi: 10.1177/0018720812442087.
A driving simulator study compared the effect of changes in workload on performance in manual and highly automated driving. Changes in driver state were also observed by examining variations in blink patterns.
With the addition of a greater number of advanced driver assistance systems in vehicles, the driver's role is likely to alter in the future from an operator in manual driving to a supervisor of highly automated cars. Understanding the implications of such advancements on drivers and road safety is important.
A total of 50 participants were recruited for this study and drove the simulator in both manual and highly automated mode. As well as comparing the effect of adjustments in driving-related workload on performance, the effect of a secondary Twenty Questions Task was also investigated.
In the absence of the secondary task, drivers' response to critical incidents was similar in manual and highly automated driving conditions. The worst performance was observed when drivers were required to regain control of driving in the automated mode while distracted by the secondary task. Blink frequency patterns were more consistent for manual than automated driving but were generally suppressed during conditions of high workload.
Highly automated driving did not have a deleterious effect on driver performance, when attention was not diverted to the distracting secondary task.
As the number of systems implemented in cars increases, an understanding of the implications of such automation on drivers' situation awareness, workload, and ability to remain engaged with the driving task is important.
一项驾驶模拟器研究比较了手动和高度自动化驾驶中工作负荷变化对性能的影响。通过检查眨眼模式的变化,还观察了驾驶员状态的变化。
随着车辆中越来越多的先进驾驶员辅助系统的加入,驾驶员的角色可能会从手动驾驶的操作员转变为高度自动化汽车的监管者。了解这些进步对驾驶员和道路安全的影响很重要。
这项研究共招募了 50 名参与者,他们分别在手动和高度自动化模式下驾驶模拟器。除了比较驾驶相关工作负荷调整对性能的影响外,还研究了次要的二十问任务的影响。
在没有次要任务的情况下,驾驶员在手动和高度自动化驾驶条件下对关键事件的反应相似。当驾驶员在自动化模式下分心于次要任务时需要重新控制驾驶时,表现最差。与自动化驾驶相比,手动驾驶的眨眼频率模式更一致,但在高工作负荷下通常会受到抑制。
当注意力不被分心的次要任务分散时,高度自动化驾驶不会对驾驶员的性能产生不利影响。
随着汽车中实施的系统数量的增加,了解这种自动化对驾驶员的情境意识、工作负荷和保持对驾驶任务参与能力的影响非常重要。