Cognitive Underpinnings of Beliefs and Confidence in Beliefs about Fully Automated Vehicles
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Summary
This study investigates the cognitive factors influencing consumers’ beliefs and their confidence in those beliefs regarding fully automated vehicles (FAVs). The research addresses a critical gap in transportation psychology: while public attitudes toward self-driving cars are mixed, little is known about the certainty with which these views are held or the cognitive underpinnings of that certainty. Understanding judgmental confidence is vital because it determines the likelihood of technology adoption, the extremity of opinions, and the susceptibility of beliefs to change. The authors hypothesized that consumers would be confident in their opinions despite low actual knowledge, and that this confidence would be driven by perceived knowledge and general self-confidence rather than expertise. The researchers conducted a survey with 114 participants recruited from Amazon Mechanical Turk, limited to U.S.-based "Masters" workers. Participants completed measures of general self-confidence, trust in technology, perceived knowledge of FAVs, and actual knowledge (assessed via an eight-item true/false quiz). They also reported their beliefs about FAV safety and benefits, their overall evaluation of the technology, and their intentions to purchase or support legislation for FAVs. Confidence and certainty in these judgments were measured on four-point scales. The results revealed that while participants held generally favorable views of FAVs, their actual knowledge was low, with 42.1% scoring at or below chance on the knowledge quiz. Despite this lack of expertise, 72% of respondents reported being "somewhat" or "highly" certain in their judgments. Crucially, judgmental confidence was not correlated with actual knowledge but was strongly correlated with perceived knowledge and general self-confidence. Mediation analysis indicated that general self-confidence influenced judgmental confidence by increasing perceived knowledge. Furthermore, confidence was associated with opinion extremity; highly confident individuals expressed either very positive or very negative views. Notably, those with the least knowledge held the most negative views, yet they did so with high confidence, suggesting these negative beliefs are resistant to persuasion. The study concludes that consumer confidence in FAV opinions is driven by superfluous cognitions—specifically perceived knowledge and general self-confidence—rather than factual expertise. This finding has significant implications for the adoption of autonomous vehicles, as confidently held negative beliefs among uninformed consumers may hinder acceptance and policy support. The results suggest that efforts to influence public opinion must address not just factual knowledge but also the psychological mechanisms that generate unwarranted certainty in judgments.
Key finding
Consumer confidence in beliefs about fully automated vehicles is predicted by perceived knowledge and general self-confidence rather than actual expertise, with the least knowledgeable participants holding the most negative views.
Methodology
survey
Sample size: 114
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_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
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| enrich | success | — | — | — | 1 | 2026-05-23 |
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| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 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
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- acceptance adoption
- trust calibration
- decision making risk perception
- automation surprise
- situational awareness
Information type
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- Empirical Findings: self report data