自动驾驶解释出错会降低乘客信任与驾驶信心，且受情境影响更大。
What Did My Car Say? Impact of Autonomous Vehicle Explanation Errors and Driving Context On Comfort, Reliance, Satisfaction, and Driving Confidence
- 通过模拟实验测试解释错误对乘客的影响
- 错误导致舒适度、依赖感、信心等全面下降
- 高风险情境下错误影响更严重，需个性化适配
在一项包含232名参与者的真实模拟驾驶研究中，我们考察了自动驾驶车辆（AV）解释错误、驾驶情境特征（感知危害与驾驶难度）及个人特质（先前信任度与专业性）对乘客舒适度、控制偏好、对车辆能力的信心以及解释满意度的影响。结果显示，解释错误对所有指标均有负面影响。令人意外的是，在相同驾驶条件下，解释错误仍显著降低了对车辆驾驶能力的评价。错误的严重性和潜在危害程度加剧了负面效应。情境危害与驾驶难度直接作用于各评价结果，并调节错误与结果之间的关系。先前信任度与专业性与各项评分正相关。研究强调，必须构建准确、情境自适应且个性化的自动驾驶解释系统，以建立信任、促进依赖、提升满意度和信心。最后提出设计、研究与部署层面的建议。
原文摘要 · Abstract (English)
Explanations for autonomous vehicle (AV) decisions may build trust, however, explanations can contain errors. In a simulated driving study (n = 232), we tested how AV explanation errors, driving context characteristics (perceived harm and driving difficulty), and personal traits (prior trust and expertise) affected a passenger's comfort in relying on an AV, preference for control, confidence in the AV's ability, and explanation satisfaction. Errors negatively affected all outcomes. Surprisingly, despite identical driving, explanation errors reduced ratings of the AV's driving ability. Severity and potential harm amplified the negative impact of errors. Contextual harm and driving difficulty directly impacted outcome ratings and influenced the relationship between errors and outcomes. Prior trust and expertise were positively associated with outcome ratings. Results emphasize the need for accurate, contextually adaptive, and personalized AV explanations to foster trust, reliance, satisfaction, and confidence. We conclude with design, research, and deployment recommendations for trustworthy AV explanation systems.
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