Studying driving behavior and risk perception: a road safety perspective in Egypt
DOI: 10.1186/s44147-021-00059-z
archive: archived pipeline: cataloged verified
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Summary
This study addresses the critical issue of road safety in Egypt, a developing nation that accounts for a disproportionate share of global road crash fatalities. Motivated by the lack of accurate government crash databases and sporadic research on driver behavior in the region, the authors aim to quantify the impact of human factors—specifically driving behavior, risk perception, and demographics—on roadway crashes. The research focuses on three distinct groups: private car drivers, truck drivers, and public transportation drivers, seeking to map the relationship between their personal attributes, violation history, and crash involvement. To achieve these objectives, the researchers developed and administered a Driver Behavior Questionnaire (DBQ), marking the first implementation of this instrument in Egypt. The survey comprised 35 questions across four sections: demographic characteristics, traffic violations and crash history, driving behavior, and risk perception. Risk perception was assessed subjectively by exposing participants to visual scenarios depicting local traffic conditions, such as overloading or pedestrian crossings, which they rated on a safety scale. Data collection involved both online questionnaires and field interviews conducted in Cairo and Giza in early 2019. After eliminating incomplete responses, the final dataset included 824 participants, comprising private car, taxi, bus, truck, and public transit drivers. The study utilized descriptive analysis and negative binomial models to predict expected crash frequency based on variables such as age, driving experience, personality traits, and specific behaviors. The findings indicate that human factors are the primary cause of crashes, with the failure to maintain a safe following distance identified as a major contributor. The negative binomial models successfully predicted crash frequencies based on personal attributes and behavioral patterns. The study highlights that aggressive behaviors, such as speeding and tailgating, along with demographic factors like age and experience, significantly influence crash likelihood. Additionally, the visual scenario assessments provided insights into how drivers perceive risk in specific local contexts, revealing gaps between perceived safety and actual hazardous conditions. The significance of this research lies in its provision of evidence-based recommendations for Egyptian authorities. The authors suggest implementing traffic management and noise control acts, raising awareness of driving etiquette, enforcing driving hour regulations, and establishing specific training programs for beginner drivers. By validating the DBQ technique combined with risk perception scenarios, the study offers a robust methodological framework for understanding driver characteristics and behaviors in contexts lacking comprehensive crash data. These findings contribute to the broader field of traffic safety by demonstrating how targeted interventions addressing human behavior can mitigate crash rates in developing countries.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-19 |
| archive | success | canonical_url | — | — | 1 | 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 | 2026-06-19 |
| 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.
Topics
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- novice drivers
- cultural cross national
- sex gender
- traffic safety culture
- decision making risk perception
- behavioral adaptation risk compensation
Information type
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- Empirical Findings: observational prevalence
- Theoretical Contribution: theory or model, computational model