Effects of User Interfaces on Take-Over Performance: A Review of the Empirical Evidence
DOI: 10.3390/info12040162
archive: archived pipeline: cataloged verified
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Summary
This literature review examines the impact of user interfaces (UI) on driver take-over performance in automated vehicles, specifically focusing on SAE Level 3 and Level 4 automation where drivers may disengage from the driving task. The study addresses the critical safety challenge of transitioning control from the automation system to the human driver, a process that requires rapid rebuilding of situational awareness and alertness. While previous reviews have analyzed factors like time budgets or secondary tasks, this paper uniquely quantifies the effectiveness of "advanced UIs"—such as contextual messaging, augmented reality, and specific information displays—compared to simple signals like basic alarms. The authors aim to identify which UI designs effectively guide drivers during take-over requests (TORs) to enhance safety and acceptance. The authors conducted a systematic review of empirical studies published between 2013 and 2020. They applied strict inclusion criteria, requiring studies to involve SAE Level 3 or higher automation, include transitions from automated to manual mode, utilize human participants in simulators or real vehicles, and provide objective data on take-over time or quality. After screening 180 papers, 25 studies met all criteria. These studies were categorized based on UI factors such as modality (auditory, visual, tactile), information type (vehicle status, surrounding context, guiding instructions), and urgency levels. The review analyzed outcomes including take-over time (e.g., first-gaze time, hands-on time) and take-over quality (e.g., lane positioning, time to collision), as well as subjective measures of trust and situational awareness. The analysis of the 25 studies revealed distinct patterns in UI effectiveness. Auditory TORs with high urgency consistently resulted in shorter take-over times, whereas visual-only signals yielded the longest reaction times. Multi-modal signals did not necessarily improve performance over auditory-only signals. Notably, TORs displayed directly on non-driving-related task devices or via augmented reality did not significantly affect take-over time. However, advanced UIs providing additional explanations of the take-over situation, surrounding information, and vehicle status significantly improved drivers' situational awareness in four out of five relevant studies. While most studies reported positive effects of advanced UIs, some showed no significant benefits or even negative effects, potentially due to information overload. For instance, adding visual text to auditory TORs sometimes increased reaction times. The authors conclude that advanced user interfaces can enhance the safety and acceptance of automated driving by improving situational awareness and guiding transitions. However, the mixed results highlight the need for systematic UI testing across various driving conditions and driver characteristics to avoid information overload. The review suggests that future UI design should focus on calibrating driver trust and enhancing situational awareness in diverse scenarios. The findings underscore that while auditory urgency is effective for speed, contextual information is crucial for quality of control, necessitating a balanced approach to UI design in higher-level automation.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-20 |
| archive | success | openalex | — | — | 5 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- automation
- takeover transitions
- automation surprise
- hud ar windshield
- ehmi external hmi
- automation complacency bias
Information type
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- Applied Guidance: design guidelines
- Methodological Resource: measurement protocol
- Theoretical Contribution: conceptual framework