From Driving to Quality Time: Deriving User Requirements for Interiors of Highly Automated Vehicles
DOI: 10.54941/ahfe1005538
archive: archived pipeline: cataloged verified
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Summary
This paper addresses the design challenges associated with the interiors of SAE Level 4 highly automated vehicles, where drivers become passengers and engage in non-driving related activities (NDRAs). The transition from driving to passenger status eliminates traditional design constraints but introduces complex requirements for optimizing NDRA experiences, which are crucial for future product differentiation. The authors aim to reduce design uncertainty and high error costs in the concept phase by deriving reliable, user-centered requirements and layout recommendations. The study is part of the KAI project, which seeks to develop software tools to support interior developers in resolving conflicts between cost, packaging, and user experience. To achieve this, the authors propose a method to analyze data from a Co-Creation (CC) study conducted in 2022. The study involved 30 participants who arranged component placeholders in a seating-buck mock-up to design interiors for four specific NDRAs: working on a laptop, relaxing, reading, and talking to passengers, across two travel scenarios. This generated 120 datasets. The methodological approach involves four stages: data collection, digitalization and structuring, numerical and geometric analysis, and interpretation. The analysis utilized ergonomic criteria, including fields of view and reach ranges based on DIN EN ISO 14738 and production ergonomics standards, to evaluate component positioning. Participants’ motivations for their design choices were also recorded and clustered to identify implicit needs, such as the desire for safety or control. The results demonstrate that NDRAs significantly influence preferred interior layouts, affecting seat configurations, component selection, and positioning. For instance, working on a laptop favored central single seats to provide an individual, distraction-free workspace, with screens positioned on the windshield or front seat backs to allow orthogonal viewing of both the screen and the road. Key components for this activity included desks, power outlets, and docking stations, all requiring high reachability and visibility. In contrast, relaxing and reading showed more diverse designs, with less pronounced component interaction. Vis-à-vis seating was preferred for talking to passengers to facilitate communication. The analysis translated these findings into structured, solution-neutral user requirements and specific layout recommendations for each NDRA, such as providing accessible desks and adjustable lighting for work, or diffuse lighting and storage for reading. The significance of this work lies in providing a systematic method to translate user motivations and geometric data into actionable design requirements for NDRA-centered interiors. The derived recommendations serve as a foundation for concept development and integration into automated design tools like KAI. The study highlights that while flexibility is key, practical constraints such as safety and weight may necessitate purpose-built interiors for specific activities rather than a single universal layout. The authors conclude that such methods are essential for ensuring interior design evolves alongside automation technology and changing user needs, though further research is needed to define NDRAs more precisely and improve study immersion.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | pdftotext | — | — | 4 | 2026-08-10 |
| clean | success | clean | — | — | 2 | 2026-08-10 |
| chunk | success | chunk | — | — | 2 | 2026-08-10 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 2 | 2026-08-10 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 17 | 2026-08-11 |
| verify | success | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.
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- Applied Guidance: design guidelines