Opel Automobile GmbH, Rüsselsheim, Germany.
WIVW GmbH, Veitshöchheim, Germany.
Hum Factors. 2018 Sep;60(6):870-881. doi: 10.1177/0018720818768199. Epub 2018 Apr 4.
Aim of the study was to evaluate the impact of different non-driving related tasks (NDR tasks) on takeover performance in highly automated driving.
During highly automated driving, it is allowed to engage in NDR tasks temporarily. However, drivers must be able to take over control when reaching a system limit. There is evidence that the type of NDR task has an impact on takeover performance, but little is known about the specific task characteristics that account for performance decrements.
Thirty participants drove in a simulator using a highly automated driving system. Each participant faced five critical takeover situations. Based on assumptions of Wickens's multiple resource theory, stimulus and response modalities of a prototypical NDR task were systematically manipulated. Additionally, in one experimental group, the task was locked out simultaneously with the takeover request.
Task modalities had significant effects on several measures of takeover performance. A visual-manual texting task degraded performance the most, particularly when performed handheld. In contrast, takeover performance with an auditory-vocal task was comparable to a baseline without any task. Task lockout was associated with faster hands-on-wheel times but not altered brake response times.
Results showed that NDR task modalities are relevant factors for takeover performance. An NDR task lockout was highly accepted by the drivers and showed moderate benefits for the first takeover reaction.
Knowledge about the impact of NDR task characteristics is an enabler for adaptive takeover concepts. In addition, it might help regulators to make decisions on allowed NDR tasks during automated driving.
本研究旨在评估不同非驾驶相关任务（NDR 任务）对高度自动化驾驶中接管性能的影响。
在高度自动化驾驶期间，可以允许驾驶员临时从事 NDR 任务。然而，当系统达到极限时，驾驶员必须能够接管控制权。有证据表明，NDR 任务的类型会对接管性能产生影响，但对于导致性能下降的具体任务特征知之甚少。
三十名参与者在模拟器中使用高度自动化的驾驶系统进行驾驶。每位参与者都要面对五个关键的接管情况。基于 Wickens 的多重资源理论的假设，对典型 NDR 任务的刺激和反应模式进行了系统的操纵。此外，在一个实验组中，任务与接管请求同时被锁定。
任务模式对接管性能的几个衡量指标有显著影响。视觉-手动输入文本任务的性能下降最为明显，尤其是在手持设备上执行时。相比之下，使用听觉-语音任务的接管性能与没有任务的基线相当。任务锁定与更快的手到轮上时间相关，但不会改变制动响应时间。
结果表明，NDR 任务模式是接管性能的相关因素。驾驶员非常接受 NDR 任务锁定，并且在第一次接管反应中显示出适度的优势。
了解 NDR 任务特征的影响是自适应接管概念的基础。此外，它可能有助于监管机构在自动驾驶期间就允许的 NDR 任务做出决策。
