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

TL;DR

This study investigates how explanation errors in autonomous vehicles, combined with driving context and personal traits, influence passenger trust, reliance, satisfaction, and confidence, highlighting the importance of accurate and personalized explanations.

Contribution

It provides empirical evidence on the effects of explanation errors and context on passenger perceptions, emphasizing the need for adaptive, accurate AV explanations.

Findings

Explanation errors reduce trust and reliance.

Harmful and difficult contexts amplify negative effects.

Prior trust and expertise improve outcome ratings.

Abstract

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.