为什么不解释?解释对人类对自动驾驶感知的影响

Daniel Omeiza, Konrad Kollnig, Helena Webb, M. Jirotka, L. Kunze
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引用次数: 6

摘要

自动驾驶汽车(AVs)有可能改变我们通勤、旅行和运输货物的方式。然而,自动驾驶汽车在社会上的应用需要人们理解、接受和信任它们。易懂的解释可以帮助不同的自动驾驶汽车利益相关者评估自动驾驶汽车的行为,从而增加他们的信心并培养信任。在一项用户研究(N = 101)中,我们检查了AV提供的不同解释类型(基于调查性查询)及其对使用信任决定因素的人的影响。我们的定量和定性分析表明,在评估驾驶事件时,带有因果归因的解释提高了任务绩效和理解,但没有直接提高感知信任。这强调了需要采取额外的措施和研究来增强人们对自动驾驶汽车的信任。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Why Not Explain? Effects of Explanations on Human Perceptions of Autonomous Driving
Autonomous vehicles (AVs) have the potential to change the way we commute, travel, and transport our goods. The deployment of AVs in society, however, requires that people understand, accept, and trust them. Intelligible explanations can help different AV stakeholders to assess AVs' behaviours, and in turn, increase their confidence and foster trust. In a user study (N = 101), we examined different explanation types (based on investigatory queries) provided by an AV and their effect on people using the trust determinant factors. Our quantitative and qualitative analysis shows that explanations with causal attributions improved task performance and understanding when assessing driving events but did not directly improve perceived trust. This underlines the potential need for additional measures and research to enhance trust in AVs.
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