Designing for Trust and Situational Awareness in Automated Vehicles: Effects of Information Type and Error Type

Yaohan Ding, Lesong Jia, Na Du
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Abstract

Trust and situational awareness (SA) are crucial to the adoption and safety of automated vehicles (AVs). Appropriate design of AV explanations could promote drivers’ acceptance, trust, and SA, enabling drivers to get more benefits from the technology. This study investigated the effects of error type and information type of AV explanations on drivers’ trust and SA. We recruited 300 participants for an online video study with a 3 (information type) × 2 (error type) mixed design. Linear mixed model analyses showed that compared with false alarms, misses were associated with more trust decrease after the error and more trust decrease after the post-error recovery. Compared with why information, how information was associated with lower SA generally and risked potential over-trust in false alarms. Therefore, we recommend deploying AV decision systems that are less miss-prone and including why information in AV explanations.
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自动驾驶车辆的信任和态势感知设计:信息类型和错误类型的影响
信任和态势感知(SA)对于自动驾驶汽车(AVs)的采用和安全至关重要。合理设计自动驾驶讲解,可以促进驾驶员的接受度、信任度和SA,使驾驶员从自动驾驶技术中获得更多的收益。本研究考察了自动驾驶解释的错误类型和信息类型对驾驶员信任和SA的影响。我们招募了300名参与者进行在线视频研究,采用3(信息类型)× 2(错误类型)混合设计。线性混合模型分析表明,与假警报相比,误报与错误后信任下降和错误后恢复后信任下降相关。与“为什么信息”、“信息是如何与低SA联系在一起的”和“虚假警报中潜在的过度信任风险”相比。因此,我们建议部署不容易出错的自动驾驶决策系统,并在自动驾驶解释中包含为什么信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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