Roadway classifications and the accident injury severities of heavy-vehicle drivers

- Heavy-vehicle driver injury severity is analyzed by roadway classification.
- Mixed logit model is estimated to identify significant contributing injury severity factors.
- Parameter transferability test is conducted to determine if separate models should be fit.
- Parameter estimates are statistically different by roadway classification.
- Injury severity factors, their effect, and magnitude are considerably different by roadway classification.

Previous heavy-vehicle (a truck with a gross vehicle weight rating greater than 10,000 pounds) injury severity studies have disaggregated data by factors such as urban/rural and time-of-day, yet a focus on contributing factors by roadway classification is lacking. Taking this into consideration, the current study aims to extend traditional heavy-vehicle driver injury severity analyses, through the application of a mixed logit modeling framework, by determining statistically significant injury severity contributing factors by roadway classification. In the course of identifying statistically significant injury severity factors, a parameter transferability test is conducted to determine if roadway classifications need to be considered separately for safety analyses. Empirical results show that roadway classifications need be modeled separately with a high level of confidence, as the estimated parameters are statistically different by classification based on corresponding chi-square statistics and degrees of freedom. The majority of significant contributing factors are exclusive to a specific road classification, however, two factors were found to impact injury severity regardless of classification while some factors were significant for two classifications. Findings from this study can prompt future work to focus on injury severity, as well as other safety measures, by roadway classification and/or other subpopulations within crash datasets.