Effects of vehicle-type mismatch and at-fault role in two-vehicle speeding-related crashes on driver injury severity involving cars, sport utility vehicles, and pickup trucks

Introduction: Speeding-related crashes involving passenger cars and light trucks (SUVs and pickup trucks) pose significant safety concerns due to vehicle mass differences and crash dynamics. Understanding how these factors interact with roadways, environmental, and driver characteristics is critical for developing targeted interventions. Method: This study analyzed 2023 Pennsylvania police-reported crash data for two-vehicle speeding-related collisions between cars and SUVs or pickup trucks using mixed logit models with heterogeneity in means and variances. The analysis was stratified by at-fault vehicle type and by vehicle-pairing configurations, specifically those characterized by substantial differences in physical mass and body form (e.g., car–SUV and car–pickup truck combinations and their respective reciprocal pairings). Marginal effects were estimated to assess changes in the probabilities of injury outcomes across spatial and temporal, roadway, environmental, vehicle, and driver characteristics. Results: The estimated model results indicate elevated severe injury risk when heavier vehicles are involved under specific configurations, notably head-on crashes with SUVs at-fault and speeding on curved segments, especially when pickup trucks are at fault. Rear-end crashes showed lower severe injury risk but substantially higher odds of minor injury when pickup trucks were at-fault. Weekend and nighttime crashes increased severity, while rainy conditions slightly reduced injury risk. Even low-speed exceedances (within 5 mph of the posted speed limit) significantly increased the likelihood of severe injury. Driver-level heterogeneity emerged, with younger drivers generally facing lower severe injury risk, and gender, restraint use, and licensing status influencing severity patterns. Practical Applications: The findings of this study support targeted interventions, including weekend speed enforcement, curve-focused engineering treatments, nighttime visibility improvements, rear-end mitigation for pickup trucks, seat belt campaigns, and adoption of advanced vehicle technologies. Despite the smaller sample sizes for car–pickup truck crashes, the patterns are operationally meaningful and actionable for highway agencies, law enforcement, policymakers, and industry stakeholders.