The Long Road Home: Driving Performance and Ocular Measurements of Drowsiness Following Night Shift-Work
DOI: 10.17077/drivingassessment.1497
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Summary
This study investigates the impact of night shift work on driving performance and physiological markers of drowsiness during the commute home, a period identified as particularly vulnerable due to the interaction between circadian rhythms and extended wakefulness. The research addresses the significant safety risk faced by approximately 9.5 million US workers on night or rotating shifts, who often experience poor sleep quality and heightened fatigue. The primary objective was to quantify critical driving events and correlate them with objective physiological indices of drowsiness. The experimental design involved sixteen healthy night shift workers (aged 18–65) who participated in two separate two-hour driving sessions in an instrumented vehicle on a closed-loop track. One session served as a baseline following a night of rest, while the other occurred immediately after a night of shift work. Researchers continuously monitored physiological data, including eye movements, blinks, electroencephalography (EEG), and electrooculography (EOG), alongside driving performance metrics such as lane excursion rates. To assess safety, an investigator blind to the condition used an emergency passenger-side brake pedal to intervene during critical events. Participants also completed subjective ratings of sleepiness and performance every fifteen minutes. The results demonstrated significantly impaired performance following night shift work. Drivers exhibited higher Johns Drowsiness Scores, indicating increased drowsiness that worsened more sharply over the session compared to the post-sleep condition. Objectively, the rate of lane excursions was more than three times higher after night shifts (0.68/min) than after rest (0.20/min). Crucially, all emergency braking events in the study occurred in the post-night shift condition, affecting six out of sixteen drivers, whereas no such events occurred in the post-sleep condition. While drivers reported greater difficulty in lane keeping after night shifts, these subjective ratings did not consistently align with objective performance data, particularly as fatigue intensified toward the end of the drive. The findings highlight a critical disconnect between self-perception and actual capability under fatigue. Nearly 40% of drivers experienced critical events requiring intervention, yet their subjective assessments of their lane-keeping failures were often inaccurate. This suggests that fatigued drivers may have a less realistic appraisal of their performance, increasing crash risk. The study underscores the danger of the post-shift commute, noting that real-world drivers lack the safety net of an alert passenger and secondary brake. These results imply a need for effective countermeasures to mitigate drowsy driving risks among night shift workers.
Key finding
Night shift workers exhibited significantly higher physiological drowsiness, increased lane excursions, and all critical braking events compared to their performance after a night of rest.
Methodology
on_road
Sample size: 16
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | author_sweep | — | — | 2 | 2026-05-28 |
| archive | success | canonical_url | — | — | 1 | 2026-06-04 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
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| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-04 |
| enrich | success | — | — | — | 1 | 2026-05-28 |
| promote | success | — | — | — | 1 | 2026-06-04 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 2 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 15 | 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.
- shift work driving
- drowsiness
- drowsiness detection algorithms
- circadian factors
- truck driver fatigue
- dark adaptation mesopic
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, behavioral performance data
- Theoretical Contribution: theory or model