Meeting User Needs in Vehicle Automation
DOI: 10.54941/ahfe1002432
archive: archived pipeline: cataloged verified
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Summary
This paper summarizes the findings of the German national project AutoAkzept, which aimed to enhance the acceptance of connected, cooperative, and automated mobility (CCAM) by reducing subjective user uncertainty. The authors argue that uncertainty impairs trust and acceptance, motivating the development of "user-focused automation." This design philosophy centers on two fundamental human needs: the Need to Understand (NTU), requiring systems to be transparent and predictable, and the Need to Be Understood (NTBU), requiring systems to recognize user states and adapt accordingly. The research evaluated technological solutions for assessing user activities and states, creating individual user profiles, and adapting vehicle behavior through information transfer, interior setup, routing, and driving style. The study employed three primary use cases involving SAE Level 4 automation, tested via driving simulators, online studies, and real-vehicle experiments. In the "Mobile Office" use case, researchers developed methods to assess user activity and stress using video-based body joint tracking and electrocardiogram data. Machine learning models classified activities with high accuracy (e.g., 93% for mobile office work). Studies on interior adaptation revealed that users valued both automated adjustments to their activity and the ability to manually control lighting, suggesting a hybrid approach is optimal. Routing adaptations that extended automated driving sections were also found useful for completing work tasks. In the "Robotaxi" use case, the focus was on adaptive internal human-machine interfaces (iHMI) to address NTU. An online study with 106 participants determined that users desired earlier system feedback for vulnerable road users, particularly children (68% wanted feedback upon first visibility). Simulator studies with 50 participants showed that context-adaptive iHMIs improved trust and experience for high-trust users, while permanent information displays benefited low-trust users. Additionally, research on driving style individualization identified manual driving style, technical affinity, and gender as significant, though moderate, predictors for initial system settings. A separate study using physiological sensors and contextual data achieved up to 80% precision in detecting subjective discomfort. The "Kinetosis" use case addressed motion sickness through anticipatory light cues. A study with 16 participants demonstrated that an LED light-band providing direction-resolved signals significantly reduced kinetosis symptoms in highly sensitive users. Overall, the AutoAkzept project confirms that automated vehicles can effectively assess user states and activities. By adapting system behavior to meet the NTU and NTBU, designers can positively influence user experience, thereby fostering trust and promoting the broader acceptance of automated driving technologies.
Key finding
User-focused automation strategies, including adaptive human-machine interfaces and interior adjustments tailored to individual user states and needs, significantly reduce subjective uncertainty and improve trust and acceptance in automated vehicles.
Methodology
mixed_methods
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-05 |
| archive | success | canonical_url | — | — | 1 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-07 |
| chunk | success | chunk | — | — | 1 | 2026-06-07 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-07 |
| promote | success | — | — | — | 1 | 2026-06-05 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- acceptance adoption
- automation
- automation surprise
- ehmi external hmi
- trust calibration
- passenger motion sickness comfort
Information type
What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).
- Applied Guidance: design guidelines
- Empirical Findings: self report data
- Theoretical Contribution: conceptual framework