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首页> 外文会议>International Conference on HCI in Mobility, Transport, and Automotive Systems;International Conference on Human-Computer Interaction >Understanding Take-Over in Automated Driving: A Human Error Analysis
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Understanding Take-Over in Automated Driving: A Human Error Analysis

机译：在自动化驾驶中了解接收：人为错误分析

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Automation offers a new way of driving, but often the human error (HE) in the process of take-over results in adverse effects of unrecognized risks. Hence, the impact of HE in safety of automated driving remains a major problem. This paper proposed a Human error analysis method based on analysis of the root cause of HEs events to understand the process of take-over and identify root cause of take-over failure in automated driving. Simulated driving practice with videos and questionnaire were conducted to identify the main factors leading to HEs in take-over. Human factors events diagram was used to better understand take-over as a human factor event and to provide information for root cause of takeover failure recognition. The results reveal that the most common failure mode in take-over is cognition error caused by driver poor mental state such as driver fatigue and reaction ability, followed by control error caused by inappropriate take-over request (TOR). Determination of these failure modes provide evidence for increasing or repairing barriers in the process of take-over. The suggested cognition-corresponding model of take-over showed that take-over is a complex human-machine interaction process, thus the causes of HEs should be discussed from a multi-dimensional perspective, and explored through empirical research.
机译：自动化提供了一种新的驾驶方式，但通常在接收过程中的人为错误（他）导致无法识别的风险的不利影响。因此，他在自动驾驶安全性的影响仍然是一个主要问题。本文提出了一种基于分析HES事件的根本原因的人为误差分析方法，了解接收过程的过程，识别自动驾驶中接收失败的根本原因。使用视频和问卷模拟驾驶实践，以确定接管中的主要因素。人类因素事件图用于更好地理解接收作为人类因子事件，并为收购失败识别的根本原因提供信息。结果表明，接管中最常见的故障模式是由驾驶员疲劳和反应能力等驾驶员较差和反应能力引起的认知误差，然后是由不适当的接管请求（Tor）引起的控制误差。这些失效模式的确定提供了增加或修复接管过程中的障碍的证据。建议的认知 - 相应的接收模型表明，接管是复杂的人机相互作用过程，因此应该从多维视角讨论他的原因，并通过经验研究探索。

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