Do we trust automated vehicles? A driving simulator study
DOI: 10.1016/j.trpro.2024.02.023
archive: archived pipeline: cataloged verified
Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)
Summary
This study investigates the evolution of driver trust in automated vehicles (AVs) following direct exposure to a Level-2 automated system. While prior research has extensively examined initial trust levels using questionnaire-based methods, there is a lack of understanding regarding how trust dynamically changes after actual interaction with AV technology. The authors aim to assess variations in trust before and after simulator exposure and identify which driver characteristics and behavioral traits modulate this evolution. The experimental design utilized a driving simulator at the University of Padua, involving 57 participants aged 21–29. The session consisted of a five-minute manual driving phase for familiarization, followed by a 15-minute automated driving phase. During the automated phase, participants encountered potentially risky scenarios, such as sudden braking and near-misses, but the system was programmed to handle these safely without requiring intervention. Trust was measured objectively by recording whether participants took control of the vehicle (interpreted as a lack of trust) and subjectively through pre- and post-trial questionnaires assessing general trust levels. Additional data included demographic information, vehicle ownership status, and self-reported driving styles via the Multidimensional Driving Style Inventory (MDSI). Results indicated that 42% of participants intervened to take control, despite the system’s capability to manage the scenarios safely. Logistic regression analysis revealed that drivers with higher self-reported scores for distracted (dissociative) and risky driving behaviors were significantly less likely to intervene, suggesting a tendency toward over-trusting the automation. Subjective trust scores decreased significantly after the trial, particularly for those who had intervened. Drivers who owned Level-1 or Level-2 vehicles reported higher initial trust than those with conventional vehicles, though both groups experienced a decline in trust post-exposure. Additionally, male drivers showed a greater reduction in trust compared to females, implying that females may have held more realistic initial expectations of the technology. The study concludes that trust in automated driving is a dynamic mental model that evolves with experience, challenging the validity of relying solely on stated-preference approaches to gauge user acceptance. The findings highlight that initial trust levels can be misleading, as firsthand exposure often leads to a reevaluation of the system’s capabilities. The authors emphasize the importance of using driving simulators or virtual reality methods to assess trust more accurately. Furthermore, the observed over-trusting behavior among distracted and risk-prone drivers raises safety concerns, underscoring the need for further research into how driver characteristics influence interaction with automated systems.
Key finding
Drivers who intervened to take control of the automated vehicle experienced a significant decrease in subjective trust after the trial, whereas those with higher self-reported distracted and risky driving behaviors were less likely to intervene, suggesting a potential for over-trusting.
Methodology
simulator
Sample size: 57
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. Discovered via author_sweep_intake on 2026-05-28.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 2 | 2026-05-28 |
| archive | success | openalex | — | — | 9 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-04 |
| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | — | — | — | 1 | 2026-05-28 |
| promote | success | — | — | — | 1 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | partial | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified_with_issues.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- trust calibration
- acceptance adoption
- trust in automation foundations
- automation
- automation surprise
- 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
- Methodological Resource: validation psychometrics, tool software