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Understanding the factors that affect crash severity at intersections is essential to develop strategies to alleviate safety deficiencies. This paper identifies and compares the significant factors affecting crash severity at signalized and stop-controlled intersections in urban and rural areas in Alabama using recent five-year crashes. A random forest model was used to rank variable significance and a binary logit model was applied to identify the significant factors at both intersection types in urban and rural areas. Four separate models (urban signalized, urban stop-controlled, rural signalized, and rural stop-controlled) were developed. New variables that were not previously explored were used in this study, such as the roadway type (one-way vs. two-way) and traffic control functioning (yes or no). It was found that one-way roadways were associated with a reduction in crash severity at urban signalized intersections. In all four models, rear-end crashes showed lesser severity than side impacts. Head-on crashes, higher speed limits, and curved sections showed higher severity in urban signalized and stop-controlled intersections. In rural stop-controlled intersections, right-turning maneuvers had a severity reduction. Female drivers showed 15% and 45% higher severity likelihood (compared to males) at urban and rural signalized intersections, respectively. Strategies to alleviate crash severity are proposed.

Comparison of Crash Severity Risk Factors at Signalized and Stop-Controlled Intersections in Urban and Rural Areas in Alabama