Fatigue Among Indonesian Commercial Vehicle Drivers: A Study Examining Changes in Subjective Responses and Ocular Indicators
DOI: 10.14716/ijtech.v14i5.4856
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Summary
This study investigates the progression of fatigue and sleepiness among Indonesian commercial vehicle drivers, addressing a critical road safety issue in Indonesia where traffic accidents have risen significantly. While fatigue is a known contributor to crashes involving commercial buses and trucks, it has rarely been quantified in real-world field settings. The research specifically examines how prolonged driving duration affects subjective sleepiness and ocular indicators, with the goal of characterizing fatigue levels to inform safety strategies and work-rest schedules. The experimental design involved 12 male commercial shuttle drivers, aged 30–40, with extensive driving experience. Participants completed two consecutive driving sessions of approximately 2.5 hours each on a highway, separated by a 15-minute rest period. Data collection included subjective assessments using the Karolinska Sleepiness Scale (KSS) and objective ocular measurements recorded via dashboard-mounted cameras. The ocular parameters analyzed offline were blink frequency, blink duration, percent of eye closure (PERCLOS), and microsleep episodes. These metrics were calculated in 1-minute windows every 20 minutes throughout the driving tasks. Statistical analysis employed non-parametric tests, including Wilcoxon Signed-Rank and Friedman tests, to evaluate changes in fatigue indicators as a function of driving duration and to correlate subjective and objective measures. The results indicated that the first 2.5-hour driving session induced a moderate level of sleepiness, with KSS scores peaking toward the end of the trip. However, the subsequent 2.5-hour session resulted in excessive fatigue, despite the intervening 15-minute rest. Subjective KSS scores reached moderate levels of sleepiness much faster in the second trip compared to the first. Ocular parameters generally increased with driving duration, though patterns varied; blink frequency and microsleep showed inverted U-shaped curves in the first trip, while blink duration and PERCLOS consistently increased during the second trip. Blink duration emerged as the most consistent indicator of fatigue, showing markedly greater values at the end of the second trip. All eye-blink parameters were closely correlated with subjective KSS scores, with blink duration and PERCLOS showing the strongest associations. The study concludes that prolonged driving significantly increases fatigue, and a 15-minute rest period is insufficient to mitigate the effects of cumulative driving time. Blink duration is identified as a robust, non-invasive objective measure for detecting driver fatigue, correlating strongly with subjective reports. These findings suggest that current work-rest schedules for commercial drivers may be inadequate and highlight the potential for using ocular indicators in real-time fatigue detection technologies. The results provide empirical evidence for stakeholders, such as transportation authorities and shuttle companies, to revise driver rostering and implement better fatigue mitigation strategies to enhance road safety.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | OpenAlex-citations | — | — | 1 | 2026-06-20 |
| archive | success | unpaywall | — | — | 2 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-20 |
| chunk | success | chunk | — | — | 1 | 2026-06-20 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-20 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-20 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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- Empirical Findings: physiological data
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