Influence of an Innovative HMI for Highly Automated Driving on Trust

Rauh, Nadine; Günther-Gommlich, Tina; Maas, Kira-Alyssa; Hollander, Cornelia; Beggiato, Matthias · 2026 · Crossref

DOI: 10.1007/978-3-032-03488-5_6

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Summary

This study investigates how drivers’ trust in a novel Human-Machine Interface (HMI) for highly automated vehicles evolves over time and how this trust is influenced by system reliability and driver characteristics. The research focuses on the "Mediator" system, developed within the European MEDIATOR project, which coordinates between human drivers and autonomous vehicles based on respective fitness levels and environmental factors. The authors argue that adequate trust is essential for the successful adoption and safe usage of automated driving systems, as it determines whether drivers accept system recommendations and avoid inappropriate interference. To examine these dynamics, the researchers conducted a driving simulator study with 74 participants. The experimental design featured four sequential test drives of approximately ten minutes each, utilizing a fixed-order within-subject design. Condition 1 involved manual driving to establish a baseline. Condition 2 introduced assisted driving (SAE Level 2) in foggy conditions, requiring driver monitoring. Condition 3 utilized autopilot mode (SAE Level 3), allowing drivers to engage in secondary tasks. Condition 4 replicated Condition 3 but included an unexpected system behavior: a late and abrupt braking maneuver during a close approach to a traffic jam. Trust was measured at five points using the Trust in Automation questionnaire, and driver characteristics, including affinity for technology and age, were recorded. The results demonstrated that drivers exhibited high initial trust in Mediator after receiving detailed information, supporting the hypothesis of positive initial expectations. Trust increased significantly after the first two successful automated drives, confirming that repeated positive experiences bolster confidence. However, trust decreased significantly after the fourth drive, where participants experienced the unpredictable braking maneuver. Despite this momentary drop, the overall trust rating after all drives remained higher than the initial expected trust and higher than the rating immediately following the negative experience. This indicates that trust is robust when built on a foundation of early reliability. Additionally, drivers with a higher affinity for technology showed significantly higher trust levels across most measurement points. Contrary to hypotheses, driver age did not significantly influence trust in this sample. The study concludes that trust in automated driving systems is dynamic and context-dependent. While negative or unexpected system behaviors can temporarily reduce trust, a strong foundation of reliability can make trust resilient. The findings highlight the importance of calibrating driver expectations through clear communication of system capabilities and limitations. The authors emphasize that while simulator studies provide controlled insights, future research must examine trust development in real-world traffic, where the consequences of system errors are more severe, to ensure optimal system usage and safety.

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StageOutcomeToolModelPromptAttemptsCompleted
discover success Crossref 1 2026-06-05
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 2026-06-05
summarize success llm qwen3.6-27b-prismaquant summ-v5 1 2026-06-09
tag success vector_similarity 15 2026-06-11
verify partial 1 2026-06-09

Summary generated by qwen3.6-27b-prismaquant on 2026-06-09; verification: verified_with_issues.

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