Fit for purpose of on-the-road driving and simulated driving: A randomised crossover study using the effect of sleep deprivation
DOI: 10.1371/journal.pone.0278300
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Summary
This study addresses the validity and interchangeability of on-the-road driving, simulated driving, and psychomotor tasks for assessing driving impairment. While driving simulators are widely used in clinical trials due to cost-effectiveness and safety, concerns remain regarding their ecological validity compared to real-world driving. The researchers aimed to determine if these methods measure the same aspects of driving performance by comparing their sensitivity to sleep deprivation, a known impairing factor. The study employed a randomized, two-way crossover design involving 24 healthy male drivers with at least five years of driving experience and an annual mileage of at least 3,000 km. Participants underwent assessments under two conditions: after a well-rested night and after a night of total sleep deprivation. Driving performance was quantified using the Standard Deviation of Lateral Position (SDLP), a metric reflecting lane-keeping stability. On-the-road driving was conducted on a 40 km highway section using a modified vehicle with GPS and Mobileye tracking systems. Simulated driving was performed on a fixed-base simulator for 20 minutes. Additionally, a battery of psychomotor tests, including eye movement tracking, adaptive tracking, and body sway, was administered to evaluate isolated cognitive and motor skills. The results demonstrated that sleep deprivation significantly increased SDLP in both simulated driving (increase of 10 cm) and on-the-road driving (increase of 2.8 cm). The psychomotor test battery also detected significant effects of sleep deprivation across almost all tasks. However, the correlation between on-the-road and simulator SDLP was strong under well-rested conditions (r = 0.63) but disappeared after sleep deprivation (r = 0.31, p = 0.18). Among the psychomotor tasks, only the adaptive tracking test showed a significant correlation with simulator SDLP under sleep-deprived conditions. Subjective visual analogue scale scores correlated with other measures, but objective performance metrics diverged significantly between the driving modalities when impaired. The findings indicate that on-the-road driving, simulated driving, and psychomotor tasks are not interchangeable and likely assess different aspects of driving behavior. The lack of correlation between simulator and on-the-road SDLP under impairment suggests that simulators may not fully replicate the real-world driving experience or the specific effects of fatigue on lane-keeping. Consequently, the choice of assessment method should be guided by the specific research question, as each method captures distinct components of driving performance. This has implications for regulatory acceptance of simulator data in drug registration, highlighting the need for caution when extrapolating simulator results to real-world safety outcomes.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | canonical_url | — | — | 1 | 2026-08-09 |
| extract | success | pdftotext | — | — | 4 | 2026-08-10 |
| clean | success | clean | — | — | 2 | 2026-08-10 |
| chunk | success | chunk | — | — | 2 | 2026-08-10 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 2 | 2026-08-10 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 17 | 2026-08-11 |
| verify | success | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
- sleep deprivation
- drowsiness
- simulator validity fidelity
- drowsiness detection algorithms
- simulator sickness
- time on task
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: physiological data
- Methodological Resource: validation psychometrics, tool software