Road influence on the development on driver fatigue
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Summary
This review paper addresses the under-researched influence of road infrastructure on the development of driver fatigue, a factor responsible for up to 40% of traffic accidents involving professional drivers. While fatigue is traditionally categorized under the "human" factor in road safety frameworks (alongside vehicle, road, and environment), the authors argue that specific road characteristics significantly contribute to fatigue onset. The study aims to systematize indicators related to driver fatigue that should be integrated into modern road safety assessment tools, such as road safety audits and impact assessments. The methodology consists of a comprehensive literature review analyzing scientific databases (ScienceDirect, PubMed, Springer, Transportation Research Board) and gray literature. The authors synthesized findings from studies utilizing two primary approaches: the analysis of traffic accident databases and the assessment of driver attitudes and self-reported behaviors. Key studies reviewed include analyses of Finnish accident data by Radun and Summala (2004), which identified high-risk periods and road types, and experimental studies by Ronen et al. (2014) and Reyner and Horne (2002) examining the efficacy of countermeasures like energy drinks and rest breaks on monotone roads. The findings indicate that fatigue-related accidents are strongly associated with specific temporal and environmental conditions, occurring most frequently between midnight and 6:00 AM, during summer months, and on monotonous road sections with long straightaways and low traffic intensity. Driver demographics also play a role, with young males (under 35) and older drivers (over 65) showing higher susceptibility. The review highlights that while human factors (sleep duration, age, gender) and vehicle factors are well-documented, the "road" factor is often overlooked. Experimental evidence suggests that monotone environments exacerbate fatigue, though interventions like caffeine consumption and short rest breaks can temporarily mitigate performance degradation. The significance of this work lies in its proposal of specific, measurable indicators for road safety evaluations to prevent fatigue-related crashes. The authors recommend incorporating metrics such as the percentage of road sections with straightaways longer than 500 meters, the proportion of roads with monotone surroundings, traffic intensity levels, and the availability of designated rest areas. Additionally, they suggest monitoring the installation of warning systems like rumble strips on long, straight sections. By reclassifying fatigue as an element influenced by road design, the paper advocates for infrastructure-based interventions to complement human-centric safety measures, providing a foundation for future research into acceptable straightaway lengths and the definition of "monotone" environments.
Key finding
Road characteristics, particularly monotonous environments and long straight sections, significantly influence the development of driver fatigue and should be systematically evaluated in road safety assessments.
Methodology
review
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-05 |
| archive | success | canonical_url | — | — | 1 | 2026-06-06 |
| extract | success | cached | — | — | 3 | 2026-06-10 |
| clean | success | clean | — | — | 1 | 2026-06-07 |
| chunk | success | chunk | — | — | 1 | 2026-06-07 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-07 |
| enrich | success | openalex | — | — | 3 | 2026-07-02 |
| promote | success | — | — | — | 1 | 2026-06-05 |
| 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.
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Information type
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- Empirical Findings: physiological data, crash risk outcomes
- Theoretical Contribution: theory or model