Functional safety analysis of SAE conditional driving automation in time-critical situations and proposals for its feasibility

Functional safety analysis of SAE conditional driving automation in time-critical situations and proposals for its feasibility
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时间紧迫情况下 SAE 条件驾驶自动化的功能安全分析及其可行性建议

DOI:
10.1007/s10111-020-00652-x
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发表时间:
2020
期刊:
Cognition, Technology & Work
影响因子:
--
通讯作者:
Yasutaka Michiura
Yasutaka Michiura
中科院分区:
--
文献类型:
--
作者:
Takayuki Hirose;T. Sawaragi;Hideki Nomoto;Yasutaka Michiura

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自动驾驶技术正在迅速发展商用,目标是有条件驾驶自动化或第三级驾驶自动化(LoDA 3)。实现这一目标的最关键挑战之一是在紧急情况下将权力从系统顺利移交给人类驾驶员。然而,它仍在寻找根本解决办法的道路上。这种困难与设想的世界问题密切相关,功能建模的概念可能是解决方案。基于功能建模的思想,对权限传递问题进行了安全分析。利用基于功能共振分析方法(FRAM)的仿真器,讨论了时间临界情况下的权限转移安全性。结果表明,即使在自动驾驶过程中,人类驾驶员参与驾驶活动仍然是必不可少的。我们表明,目前的LoDA 3是一个神话,认为人类驾驶员应该只是在非正常情况下才需要,而在通常情况下,他们可以免于动态驾驶任务(DDTs)。在此基础上,本研究对成功的自动驾驶、有效的人机协作和正确的工件设计提出了一些建议。
The autonomous driving technology is rapidly developed for commercial use, aiming at the conditional driving automation or the third level of driving automation (LoDA 3). One of the most critical challenges for the achievement is the smooth authority transfer from the system to human drivers in an emergency. However, it is still on the way to find out fundamental solutions. The difficulty is closely related to the envisioned world problem, for which the concept of functional modeling could be a solution. This paper presents a safety analysis of the authority transfer problem based on the ideas of functional modeling. We discuss the safety of the authority transfer in a time-critical situation by using a simulator based on the functional resonance analysis method (FRAM). The result shows that the involvement of human drivers in driving activities is still essential even during autonomous driving. We show that the current LoDA 3 is a myth that the human drivers are supposed to be required just in non-normal situations, while they can be free from dynamic driving tasks (DDTs) in usual cases. Based on the result, this work makes some proposals for successful autonomous driving, effective human–machine collaboration, and the right design of artifacts.
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