A multi-year statistical analysis of driver injury severities in single-vehicle freeway crashes with and without airbags deployed

Abstract

This paper seeks to identify factors that influence driver injury severities in single-vehicle freeway crashes when airbags deployed and when airbags did not deploy. Injury-severity models were estimated using random parameters logit models with consideration given to possible heterogeneity in means and variances of the random parameters to account for unobserved heterogeneity. Three years of pre-COVID pandemic crash data (2016, 2017 and 2018) from the state of Alabama were used in the model estimations. Models were estimated with data from all years, but the model formulation allowed the estimated parameters to vary by year. The model estimation results show that there are fundamental differences in crashes where airbags deployed (which tend to be crashes associated with greater energy transfers and variance in such transfers across crashes) relative to crashes where airbags did not deploy (which tend to be crashes associated with lower-speed impacts with less variance in energy transfers across crash observations). Moreover, the effects of most of the explanatory variables on resulting injury severities were found to vary significantly over time. However, explanatory variables such as shoulder and lap belt use, driver gender, newer model year vehicles, passenger car vehicle types, urban-located crashes, collisions with deer, collisions with trees and collisions with cable barriers did not vary significantly over time in either the airbag or non-airbag deployed models, or both. The findings of this study suggest that there is a potential for advances airbag systems to substantially improve safety by closing the injury-severity gap observed between men and women in particular, and that there is a need to further explore the evolution of driver behavior over time, which ultimately determines the effectiveness of ongoing improvements in vehicle and highway safety systems.