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<p>Road crash severity is a multifactorial outcome shaped by the complex interplay of human, vehicular, infrastructural, and temporal determinants. This study employs a Multivariate Regression (SUR) model to holistically analyze these determinants on Ethiopia’s Debre Markos–Bahir Dar Highway, capturing critical interdependencies among fatal, serious, slight, and property-damage-only (PDO) crash outcomes. The analysis reveals a distinct and policy-relevant hierarchy of determinant sensitivity (Fatal &gt; PDO &gt; Serious &gt; Slight), fundamentally guided by empirical strength, societal cost, and strategic preventive rationale. Key findings identify male, middle-aged, and inexperienced drivers as high-risk cohorts, with vehicle type (notably buses and passenger car), specific collision dynamics (side/rear-end/run-off), temporal patterns (afternoon/night), and road geometry-including the counterintuitive high-risk of straight sections and downgrades-as principal factors elevating severity. The significant sensitivity of PDO crashes to factors like unlicensed driving and over-speeding underscores their role as critical precursors to severe injuries, necessitating their prioritization in proactive safety management. The implications demand an integrated, evidence-based policy framework. This study concludes by recommending targeted interventions: graduated licensing and demographically-tailored training for high-risk drivers; strategic infrastructure investment in pedestrian protection, speed controlling, and sight-distance improvements; enhanced vehicle regulation against overloading; and temporal enforcement leveraging telematics and automated systems. Supported by robust model fit (R<sup>2</sup> = 0.472–0.678; <i>p</i> &lt; 0.001), this research provides a multivariate foundation for scenario-informed safety strategies. The findings are vital for advancing Ethiopia’s Safe System goals and offer a transferable model for regions with similar traffic and infrastructural profiles, enabling sustained reductions across all crash severities through prioritized, cost-effective intervention.</p>

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Modeling and analyzing crash severity determinants across severity levels for evidence based road safety strategies on the Debre Markos to Bahir Dar highway

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月13日

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  • Gedefaye Geremew

摘要

Road crash severity is a multifactorial outcome shaped by the complex interplay of human, vehicular, infrastructural, and temporal determinants. This study employs a Multivariate Regression (SUR) model to holistically analyze these determinants on Ethiopia’s Debre Markos–Bahir Dar Highway, capturing critical interdependencies among fatal, serious, slight, and property-damage-only (PDO) crash outcomes. The analysis reveals a distinct and policy-relevant hierarchy of determinant sensitivity (Fatal > PDO > Serious > Slight), fundamentally guided by empirical strength, societal cost, and strategic preventive rationale. Key findings identify male, middle-aged, and inexperienced drivers as high-risk cohorts, with vehicle type (notably buses and passenger car), specific collision dynamics (side/rear-end/run-off), temporal patterns (afternoon/night), and road geometry-including the counterintuitive high-risk of straight sections and downgrades-as principal factors elevating severity. The significant sensitivity of PDO crashes to factors like unlicensed driving and over-speeding underscores their role as critical precursors to severe injuries, necessitating their prioritization in proactive safety management. The implications demand an integrated, evidence-based policy framework. This study concludes by recommending targeted interventions: graduated licensing and demographically-tailored training for high-risk drivers; strategic infrastructure investment in pedestrian protection, speed controlling, and sight-distance improvements; enhanced vehicle regulation against overloading; and temporal enforcement leveraging telematics and automated systems. Supported by robust model fit (R2 = 0.472–0.678; p < 0.001), this research provides a multivariate foundation for scenario-informed safety strategies. The findings are vital for advancing Ethiopia’s Safe System goals and offer a transferable model for regions with similar traffic and infrastructural profiles, enabling sustained reductions across all crash severities through prioritized, cost-effective intervention.