Users’ Understanding of Automated Vehicles and Perception to Improve Traffic Safety –Results from a National Survey
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Summary
This study addresses the public’s understanding of automated vehicles (AVs) and the sources of distrust regarding these technologies. While AVs are deployed for their potential to reduce crashes, empirical evidence of safety benefits remains inconclusive, and public unease persists. The AAA Foundation for Traffic Safety conducted a nationwide survey to assess people’s understanding of AVs, their expectations and concerns, and the rationales behind their distrust. The research employed a three-phase methodology: pre-survey focus groups, a national survey, and post-survey follow-up interviews. Focus groups in Texas and Maryland helped develop the questionnaire and a video explaining SAE automation levels. The survey was administered as part of the 2018 Traffic Safety Culture Index to a nationally representative sample of 3,349 respondents (ages 16+) via an online panel. Analysis focused on 2,582 licensed drivers who had driven in the past 30 days. Post-survey interviews with 93 respondents provided qualitative insights into specific concerns. Results indicated that 68% of respondents reported a very good or excellent understanding of AV levels after viewing the explanatory video. Respondents perceived higher levels of automation (Levels 4–5) as more effective than lower levels (Levels 2–3) in preventing crashes caused by dangerous behaviors like distracted or drowsy driving. However, trust in AVs for crash prevention decreased as automation levels increased; nearly 30% strongly distrusted Level 5 vehicles, compared to only 6% for Level 2. Concerns also escalated with automation level, with technology malfunction being the primary worry across all levels. Other significant concerns included over-reliance on technology, vehicle hacking, and confusion about when to take control. Qualitative interviews revealed that distrust stemmed from unfamiliarity, perceived unreliability, negative media coverage, and fears that AVs could not handle all crash scenarios or ethical decisions. Notably, trust in Level 5 AVs increased as respondents’ understanding of the technology improved. The study concludes that while the public recognizes the potential safety benefits of full automation, current distrust is driven by perceived unreliability and lack of rigorous testing. The findings highlight the need for safer, more reliable technology and emphasize the critical role of public education and awareness. Improving public understanding of AV capabilities and limitations is essential to increasing trust and facilitating the safe adoption of these technologies.
Key finding
Americans trusted lower AV automation levels more for crash prevention but perceived higher levels as more effective against risky driving behaviors, with fully automated Level 5 drawing the greatest distrust despite greater perceived effectiveness; trust in higher automation increased as respondents' understanding of the technology increased.
Methodology
mixed_methods
Sample size: 2582
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 bulk_ingest_aaa_foundation on 2026-05-23 (5 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | aaa_foundation | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- acceptance adoption
- trust calibration
- automation surprise
- situational awareness
- automation
- driverless ads
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
- Theoretical Contribution: conceptual framework