Towards Understanding Human-Technology Migration: Internal Interaction in Automated Road Vehicles
DOI: 10.54941/ahfe1005857
archive: archived pipeline: cataloged verified
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Summary
This paper addresses the emerging challenge of "human systems migration" in the context of automated road vehicles, specifically focusing on internal interactions between drivers and vehicle automation. As vehicle automation evolves from early static systems to dynamic cooperative systems, research has shifted from human-computer interaction to human-machine cooperation. However, significant safety concerns arise during transitions between different automation levels (upward, sideways, or downward migration) and when drivers switch between vehicles with varying automation capabilities. The authors identify a gap in current research regarding how these migrations impact human-machine interaction, cooperation, and Human-Machine Interface (HMI) design. The work is part of the German DFG-funded MiRoVA project, aiming to understand the positive and negative impacts of automation migration on driver behavior and system safety. The study outlines a research concept based on the Human Systems Exploration (HSE) turbine model. The methodology involves an iterative design exploration process within a static driving simulator. Initially, interaction patterns are explored using the "Theatre Method," where design team members emulate system roles to simulate interactions with drivers. These qualitative patterns are then formalized into state machines and probabilistic networks. The simulator environment includes a driving automation system capable of basic maneuvers, an interaction mediator for HMI control and conflict resolution, and a pattern handler to manage developed interaction patterns. The goal is to validate these patterns experimentally with representative drivers and stakeholders, while also considering broader interactions with other road users and vulnerable participants in future iterations. The paper identifies specific safety risks associated with different migration paths. Upward migration (increasing automation) risks over-reliance and over-confidence, particularly in the "uncanny and unsafe valley" between SAE levels two and three/four, where drivers may overestimate system capabilities. Sideways migration (changing vehicles with similar automation levels but different HMIs) can cause confusion or conflict, such as when switching from radar-based to vision-based systems that perform differently under specific conditions. Downward migration (decreasing automation) poses risks of over-familiarization, where drivers may fail to react quickly in emergencies because they expect automation features that are no longer present. The authors argue that managing these changes relies heavily on HMI design, yet little research has addressed migration as a change management process. The significance of this work lies in its aim to deepen the scientific understanding of automation migration’s impact on human-machine cooperation and to facilitate the practical application of this knowledge in research, development, and policy. By integrating findings into broader traffic system simulations, the project seeks to guide the safe integration of automated systems into complex road traffic scenarios. The paper concludes by emphasizing the need to address the shortcomings of current research to ensure that drivers can effectively account for changes in automation levels and environmental conditions, thereby reducing the risk of incidents and accidents.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-06 |
| archive | success | canonical_url | — | — | 1 | 2026-06-09 |
| extract | success | cached | — | — | 2 | 2026-06-09 |
| 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 | 2026-06-06 |
| 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.
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- Theoretical Contribution: conceptual framework