What Did My Car Say? Impact of Autonomous Vehicle Explanation Errors and Driving Context On Comfort, Reliance, Satisfaction, and Driving Confidence

要旨

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.

著者
Robert A. Kaufman
University of California, San Diego, La Jolla, California, United States
Aaron Broukhim
University of California San Diego, San Diego, California, United States
David Kirsh
University of California, San Diego, San Diego, California, United States
Nadir Weibel
UC San Diego, La Jolla, California, United States
DOI

10.1145/3706598.3713088

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713088

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Autonomus Vehicle

Annex Hall F204
7 件の発表
2025-05-01 18:00:00
2025-05-01 19:30:00
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