Determine Patterns of Causal Factors of Truck Crash Injury Severity on Urban and Rural Roadways Using Fuzzy Cluster Analysis.

This article focuses on investigating the causal factors influencing injury severity in truck-involved crashes on rural and urban roadways using Fuzzy Cluster Analysis (FCA) applied to Pennsylvania crash data from 2019 to 2023. FCA identified 20 clusters across three injury severity categories—Property Damage Only (PDO), Suspected Minor and Possible Injury, and Fatal and Serious Injury—revealing that urban crashes predominantly involve rear-end or sideswipe collisions with lower severity, while rural crashes are more associated with fatal outcomes involving multiple vehicles and severe collision types. Key common factors across clusters include daylight illumination and licensed drivers, with aggressive driving more prevalent in urban areas and linked to PDO crashes; clear weather and dry roads were frequent conditions in both minor and fatal crashes. The study highlights FCA’s ability to capture complex, overlapping interactions among crash factors, offering nuanced insights beyond traditional models, though it notes limitations such as geographic scope and missing driver- and truck-specific variables, suggesting future research to incorporate broader datasets and alternative clustering methods.