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首页> 外文会议>GMM-Symposium on Automotive meets Electronics >Non-driving related tasks in highly automated driving - Effects of task modalities and cognitive workload on take-over performance
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Non-driving related tasks in highly automated driving - Effects of task modalities and cognitive workload on take-over performance

机译：高度自动化驾驶中与非驾驶相关的任务-任务模式和认知工作量对接管绩效的影响

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In highly automated driving, the driver is allowed to temporarily engage in non-driving related tasks (NDR-tasks). However, when reaching a system limit, the driver needs to take back vehicle control within a reasonable amount of time. Previous studies found impairments in take-over performance while engaged in NDR-tasks, but little is known about the impact of specific task characteristics. In the present driving simulator study 14 participants used a highly automated driving system on a motorway track and faced six critical take-over situations. Based on assumptions of Wicken's multiple resource theory different variables were systematically manipulated: The demands of the NDR-task (modalities, cognitive workload) and the time budget of the take-over situation (6 vs. 8 s). Compared to an auditory task, take-over times tended to be longer for a visual-manual task, particularly when the task had a high cognitive load. Drivers did not brake faster, but stronger in the more time critical take-over situation. Further research is necessary to validate the results with a larger sample of participants and to extend the findings to other NDR-tasks and scenarios. Knowledge about the impact of different NDR-tasks provides possible approaches for adaptive HMI concepts or might help regulators making decisions on allowed NDR-tasks in automated driving.
机译：在高度自动化的驾驶中，允许驾驶员临时从事与非驾驶相关的任务（NDR任务）。但是，当达到系统极限时，驾驶员需要在合理的时间内收回车辆控制权。先前的研究发现，在执行NDR任务时，接管性能会受到损害，但对特定任务特征的影响知之甚少。在当前的驾驶模拟器研究中，有14名参与者在高速公路上使用了高度自动化的驾驶系统，并面临着6个严重的接管情况。基于Wicken的多资源理论的假设，系统地操纵了不同的变量：NDR任务的需求（方式，认知工作量）和接管情况的时间预算（6 vs. 8 s）。与听觉任务相比，视觉手动任务的接管时间往往更长，尤其是在任务具有较高的认知负荷时。驾驶员的刹车速度没有提高，但在时间紧迫的接管情况下却表现得更强劲。有必要进行进一步的研究，以用更大的参与者样本验证结果，并将研究结果扩展到其他NDR任务和方案。有关不同NDR任务影响的知识为自适应HMI概念提供了可能的方法，或者可以帮助监管机构对自动驾驶中允许的NDR任务做出决策。

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