开发一个高度自动驾驶场景来调查用户干预:当事情出错时

S. Faltaous, Tonja Machulla, M. Baumann, L. Chuang
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引用次数: 1

摘要

当前的车辆自动化水平(即SAE-L2)要求用户保持警惕,并在自动车辆无法正常运行时进行干预。在这项工作中,我们开发了一个场景,用于调查在没有系统故障通知的情况下人类如何反应。为了开发更好的通知来引起用户的干预,有必要首先了解人类如何干预,即使没有车内通知的帮助。我们提供了如何使用Unity(游戏引擎)在驾驶模拟器中实现这一功能的描述。此外,我们报告初步结果。总体而言,我们发现参与者在环境能见度较低的情况下更加兴奋和谨慎,尽管能见度与车辆自动化失败的可能性无关。我们提出了如何改进当前情景的建议,以供后续研究使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing a Highly Automated Driving Scenario to Investigate User Intervention: When Things Go Wrong
Current levels of vehicle automation (i.e., SAE-L2) require users to be vigilant and to intervene when automated vehicles fail to perform appropriately. In this work, we developed a scenario for investigating how humans respond, in the absence of notifications for system failure. In order to develop better notifications to elicit user intervention, it is necessary to first understand how humans would intervene, even without the aid of in-vehicle notifications. We provide a description of how this is implemented in a driving simulator using Unity, a game engine. In addition, we report preliminary results. Overall, we found that participants were more aroused and cautious under conditions of low environment visibility, even though visibility had no bearing on the likelihood of vehicle automation to fail. We present recommendations for how the current scenario could be improved for subsequent research.
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