Behavioral and temporal dynamics of child pedestrian crash injury patterns: evidence from random parameter modeling.

This study investigates the behavioral, environmental, and roadway-related determinants of injury severity in crashes involving child pedestrians (aged under 15), utilizing six years (2017-2022) of crash data from Texas. A random-parameter logit model is employed to account for unobserved heterogeneity in driver behavior, roadway context, temporal conditions, and environmental factors. The results reveal that higher injury severities are significantly associated with crashes occurring on two-lane, two-way roads, at curved alignments, and in areas lacking traffic control, where driver expectancy and pedestrian visibility may be compromised. In contrast, crashes involving backing maneuvers and those in large urban areas are more likely to result in no or minor injuries, possibly reflecting lower vehicular speeds and improved pedestrian-supportive infrastructure. The analysis also identifies year-to-year variability in the effects of key risk factors such as distraction, speeding, and roadway features, indicating the presence of temporal instability in crash dynamics. Crashes occurring during morning and late evening hours are consistently associated with greater injury severity, showing the role of visibility, traffic conditions, and behavioral factors such as driver alertness. These findings have important implications for child pedestrian safety programs and support targeted countermeasures, including improved lighting, traffic calming, signalization at uncontrolled sites, and expanded school-zone protections. By incorporating a behavioral safety lens and accounting for time-varying effects, this study contributes valuable insights for policymakers and practitioners aiming to reduce child pedestrian injuries through context-sensitive and evidence-based interventions.