Cross Sectional Crash Severity Analysis among Various Vehicle Driver Characteristics

Rassafi, Amir Abbas; Yazdani, Mirbahador; Shirini, Bahram · 2018 · Crossref

DOI: 10.28991/cej-03091146

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Summary

This study investigates the influence of driver characteristics—specifically gender, age, and educational level—on crash severity across three distinct vehicle categories: passenger cars, heavy vehicles, and pickup trucks. Motivated by the high cost of accidents in developing countries like Iran and the lack of comparative analysis across vehicle types in existing literature, the research aims to identify high-risk drivers to inform licensing policies and safety training. The analysis utilizes crash data from Iranian suburban roads recorded between 2009 and 2012, comprising 194,041 damage-only, 9,677 injury, and 1,303 fatality crashes. The researchers employed ordered logit models to account for the ordinal nature of crash severity (damage, injury, fatality). Using NLOGIT software, they applied a backward elimination method to select significant independent variables, excluding those with p-values greater than 0.05. Sensitivity analysis was subsequently performed to quantify the impact of each variable on crash probabilities. The study focused on demographic factors available in the reported data, noting that gender was only analyzed for passenger car drivers due to the absence of female driver data for heavy vehicles and pickup trucks. The results indicate consistent trends regarding age and education across all vehicle categories. For every category, an increase in driver age significantly decreased the probability of severe crashes, with the strongest negative coefficient observed in passenger car drivers (-0.010). Conversely, lower educational levels were associated with higher crash severity. In passenger car models, uneducated drivers showed the highest positive coefficient (1.289), followed by those with less than a high school diploma. Similar positive coefficients for uneducated drivers were found in heavy vehicle (1.039) and pickup truck (0.775) models. Notably, for passenger car drivers, female drivers exhibited a higher probability of severe crashes compared to males (coefficient 0.186), which the authors attribute to physical fragility and potential difficulties in vehicle control on suburban roads. Sensitivity analysis revealed that a one-year increase in age for passenger car drivers reduces injury crash probability by 0.046%, while uneducated pickup truck drivers have a 4.9% higher probability of injury crashes compared to their educated counterparts. The study concludes that driver age and education are critical determinants of crash severity, with older and more educated drivers experiencing less severe outcomes. The finding that female passenger car drivers face higher severity risks highlights the need for gender-specific safety considerations. These insights suggest that traffic safety interventions, such as targeted training and licensing requirements, should be tailored to specific vehicle categories and driver demographics to effectively mitigate crash severity in suburban environments.

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Topics

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• sex gender
• demographic disparities
• pre crash contributing factors

Information type

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• Empirical Findings: crash risk outcomes