Takeover Requests in Highly Automated Truck Driving: How Do the Amount and Type of Additional Information Influence the Driver–Automation Interaction?
DOI: 10.3390/mti2040068
archive: archived pipeline: cataloged verified
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Summary
This study investigates how the amount and type of additional information provided during takeover requests influence driver–automation interaction in highly automated truck driving (Level 3). While vehicle automation offers benefits like increased efficiency and comfort, it introduces risks such as loss of situational awareness and inappropriate trust. Previous research has largely focused on passenger cars, leaving a gap in understanding the specific needs of professional truck drivers, who face unique pressures and longer driving hours. The authors aimed to evaluate three Human–Machine Interface (HMI) concepts to determine whether providing additional information about the remaining time until takeover improves acceptance, workload, user experience, and controllability. The researchers conducted a within-subjects driving simulator study with 30 professional truck drivers. Participants experienced three HMI concepts differing in informational content: Concept A provided no additional information (“Please take over”); Concept B provided time-based information (“Please take over in 10 s”); and Concept C provided distance-based information (“Please take over in 220 m”). The simulation involved a dynamic truck simulator where participants engaged in a non-driving-related task (reading) while the automated system handled driving. Six traffic scenarios were modeled, including four critical situations requiring driver takeover. Data were collected using standardized questionnaires assessing acceptance, workload (DALI), user experience (UEQ), and controllability, alongside video recordings of takeover performance. Results indicated that all three concepts achieved good ratings, but those offering additional information significantly outperformed the minimal information concept. Concept B (time-based) and Concept C (distance-based) received significantly higher scores for usefulness and satisfaction compared to Concept A. Specifically, Concept C yielded the lowest workload ratings, particularly reducing situational stress and interference with secondary tasks. Controllability ratings were also significantly better for Concepts B and C compared to A. In terms of user experience, Concepts B and C scored higher on efficiency and dependability. Qualitative feedback and quantitative data suggested that truck drivers preferred the distance-based format (Concept C), likely due to their professional familiarity with distance metrics. Driving errors occurred independently of the HMI concept, attributed to simulator steering vagueness rather than interface design. The study concludes that providing additional information during takeover requests positively enhances driver–automation interaction by improving acceptance, reducing workload, and increasing perceived controllability. For professional truck drivers, distance-based information is particularly effective. These findings emphasize the importance of detailed system feedback in HMI design for automated trucks to mitigate out-of-the-loop effects and support safe takeovers. The results suggest that HMI strategies should prioritize transparency and detailed status information to foster appropriate trust and situational awareness in highly automated driving environments.
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | openalex | — | — | 5 | 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 | partial | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified_with_issues.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- automation
- takeover transitions
- automation surprise
- mode awareness
- trust calibration
- situational awareness
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).
- Empirical Findings: self report data, behavioral performance data
- Theoretical Contribution: conceptual framework