Drowsiness and Decision Making During Long Drives: A Driving Simulation Study
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Summary
This study investigates the relationship between subjective self-assessments of drowsiness, objective physiological measures, and driving performance during long overnight drives, with a specific focus on how these factors influence drivers’ decisions to stop for rest. Motivated by evidence that drowsy driving contributes significantly to fatal crashes and that drivers often underestimate their impairment, the research aims to determine if drivers are accurate judges of their own drowsiness and what cues drive their break-taking behavior. The researchers conducted a driving simulation study using the NADS miniSim. Ninety participants, aged 21–55, underwent partial sleep deprivation protocols before driving a 150-mile highway loop at night for up to three hours. To replicate real-world motivational tradeoffs, participants were offered monetary incentives for completing the drive quickly but faced penalties for road departures or crashes, encouraging a balance between speed and safety. Drowsiness was measured subjectively using the Karolinska Sleepiness Scale (KSS) and objectively via video-coded eyelid closures, specifically a modified Percent Eyelid Closure (PERCLOS) metric. Driving performance was assessed using Standard Deviation of Lane Position (SDLP). Participants could choose to stop at designated rest areas, where they could nap, consume caffeine, or engage in other activities. Results indicated that both subjective KSS ratings and objective PERCLOS values increased significantly over the course of the drive, with severe drowsiness indicators, such as microsleeps, appearing within the first 40 minutes. While a statistically significant positive correlation existed between KSS and PERCLOS, the alignment was poor; self-assessments were often miscalibrated relative to objective physiological data. Crucially, self-rated drowsiness was the primary predictor of whether a driver would take a break. Objective drowsiness levels and driving performance metrics, including lane deviation, were not significantly associated with the likelihood of stopping. Many participants continued driving despite reporting high levels of subjective drowsiness and exhibiting objective signs of impairment. The findings suggest that drivers rely heavily on their subjective perception of drowsiness to make safety-critical decisions, even though these perceptions are unreliable indicators of actual physiological impairment. Because drivers may continue operating vehicles despite high objective drowsiness and degraded performance, the study concludes that public education efforts should emphasize that self-perceived alertness is not a safe proxy for fitness to drive. Drivers are encouraged to stop and rest before feeling severely drowsy, as their internal assessments may underestimate the risk they pose to themselves and others.
Key finding
Self-ratings of drowsiness were the key predictor of drivers' likelihood to take a break, despite being poorly aligned with objective measures of drowsiness and driving performance.
Methodology
simulator
Sample size: 90
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 (6 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 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | partial | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified_with_issues.
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Information type
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- Empirical Findings: physiological data, behavioral performance data
- Methodological Resource: validation psychometrics