Gender Differences in DUI Crash Injury Severity: A Partially Constrained Random-Parameter Logit Model Analysis

Driving under the influence (DUI) has long been recognized as a major contributor to traffic accidents. However, the factors influencing the severity of crashes in DUI situations may vary significantly between genders due to physiological and psychological differences. This study analyzes DUI single-vehicle crash data from Texas to construct a random-parameter logit model that captures gender-specific differences in crash severity. A partially constrained method is employed to better identify these gender-specific factors, emphasizing the importance of separately assessing DUI behavior for males and females in traffic safety analysis. The results reveal notable gender differences in the severity of injuries from DUI crashes. A comprehensive evaluation was conducted from four perspectives: driver characteristics, vehicle features, roadway conditions, and environmental factors. Out-of-sample simulations provided additional insights, showing that even at lower blood alcohol concentration (BAC) levels, the probability of severe injury increases significantly. In conclusion, this study not only uncovers the gender-specific mechanisms behind DUI crash severity but also offers valuable empirical evidence for integrating gender considerations into future traffic safety policies and interventions.