Cross-Cultural Investigation of the Effects of Explanations on Drivers' Trust, Preference, and Anxiety in Highly Automated Vehicles
DOI: 10.1177/03611981221100528
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Summary
This study investigates how cultural background and explanation timing influence drivers’ trust, preference, and anxiety toward highly automated vehicles (AVs). Motivated by the need to address barriers to AV acceptance and the lack of research on cross-cultural human-automation interaction, the authors examined whether Hall’s high-context versus low-context cultural framework affects how drivers respond to AV explanations. The research aimed to determine if cultural norms regarding communication and authority impact the effectiveness of different explanation strategies in automated driving scenarios. The researchers conducted a video-based online survey with 118 participants from China, India, the United States, and other countries. Participants viewed simulated SAE Level 4 driving scenarios involving unexpected events, such as swerving vehicles or road hazards. The study employed a mixed-design with two independent variables: explanation conditions and cultural context. The four explanation conditions were: no explanation, explanations provided seven seconds before the AV action, explanations provided within one second after the action, and a permission-required condition where the AV explained its intent and asked for driver approval before acting. Cultural context was measured using a validated inventory, while trust, preference, and anxiety were assessed using established Likert-scale questionnaires. Linear mixed models were used to analyze the interactions between cultural context and explanation conditions. The results indicated that cultural context significantly influenced trust and preference, but only when explanations were provided. Participants from higher-context cultures (e.g., China, India) reported higher trust and preference for the AV compared to those from lower-context cultures (e.g., the United States). This cultural effect was most pronounced in the permission-required condition, where the AV asked for driver approval after explaining its actions. Regarding explanation timing, participants across all cultural groups preferred explanations given before the AV acted over those given after or none at all. However, neither cultural context nor explanation conditions had a significant effect on driver anxiety. The findings suggest that AV interface design should account for cultural differences to enhance global acceptance. Specifically, the study recommends providing explanations before AV actions to reduce uncertainty. Furthermore, for users from high-context cultures, incorporating permission-seeking mechanisms may increase trust and preference by aligning with cultural norms regarding authority and responsibility. These results imply that culturally sensitive, adaptive interfaces could improve human-AV interaction, though the authors note limitations regarding the use of simulated videos rather than real-world driving and the focus on a single cultural dimension.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | — | — | — | 1 | 2026-05-05 |
| archive | success | canonical_url | — | — | 19 | 2026-06-09 |
| extract | success | cached | — | — | 2 | 2026-06-09 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | partial | normalization | — | — | 8 | 2026-05-28 |
| promote | success | — | — | — | 1 | 2026-05-05 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-09 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 1 | 2026-06-09 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-09; verification: verified.
Topics
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- acceptance adoption
- trust calibration
- automation
- automation surprise
- trust in automation foundations
- cultural cross national
Information type
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- Empirical Findings: self report data