Frequency and Quality of Exposure to Adaptive Cruise Control and Impact on Trust, Workload, and Mental Models
DOI: 10.1016/j.aap.2023.107130
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Summary
This study investigates how the frequency and quality of exposure to Adaptive Cruise Control (ACC) influence drivers’ mental models, trust, and workload. The research addresses a critical safety gap: many drivers possess incomplete or inaccurate mental models of Advanced Driver Assistance Systems (ADAS), leading to misuse, mistrust, or operational errors, particularly when encountering edge-case events where system limitations are exposed. The authors aimed to determine whether structured exposure to routine and rare ACC edge cases could improve drivers’ understanding of the technology’s capabilities and limitations. The researchers conducted a longitudinal driving simulator study with 16 novice ACC users. Participants were randomly assigned to one of two groups: “Regular Exposure,” which encountered routine edge-case events and non-events, and “Enhanced Exposure,” which encountered both routine and rare edge-case events. Each participant completed four simulator sessions separated by approximately one week. Each session involved a drive featuring five specific scenarios designed to test ACC limits, such as poor visibility, erratic lane changes, or deteriorated lane markings. Data were collected using a 54-item mental model survey, a trust survey, and the NASA Task Load Index to measure workload. The mental model survey scored responses based on both accuracy and confidence, penalizing high-confidence incorrect answers. The results demonstrated that drivers’ mental models of ACC improved significantly with increased exposure frequency. Furthermore, the quality of exposure had a substantial impact: the Enhanced Exposure group achieved significantly higher mental model scores (mean = 8.1) compared to the Regular Exposure group (mean = 5.8). However, this improved understanding came with trade-offs in other metrics. Participants in the Enhanced Exposure group reported significantly lower trust in the ACC system and higher mental demand workload than those in the Regular Exposure group. There was no significant effect of exposure frequency on trust or workload, but the type of exposure (routine vs. rare edge cases) significantly differentiated these outcomes. These findings highlight the complex relationship between driver education, system trust, and cognitive load. While exposure to rare edge cases effectively corrects misconceptions and builds accurate mental models, it simultaneously reduces trust and increases mental workload. This suggests that while experience is crucial for safe ADAS operation, the method of delivering that experience matters. The study implies that simply increasing exposure may not be sufficient; strategies must balance the need for accurate mental models with the risk of inducing distrust or excessive cognitive load. The authors conclude that providing drivers with appropriate, safe exposure to system limitations is essential for realizing the safety benefits of ADAS, but the optimal method for doing so remains a challenge for the industry.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 2 | 2026-05-28 |
| archive | success | canonical_url | — | — | 7 | 2026-06-09 |
| extract | success | cached | — | — | 2 | 2026-06-09 |
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| chunk | success | chunk | — | — | 1 | 2026-06-04 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | semantic_scholar | — | — | 5 | 2026-05-08 |
| promote | success | — | — | — | 1 | 2026-05-07 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-09 |
| tag | success | vector_similarity | — | — | 15 | 2026-06-11 |
| verify | success | — | — | — | 1 | 2026-06-09 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-09; verification: verified.
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- Empirical Findings: self report data, observational prevalence
- Theoretical Contribution: computational model