Investigating the difference in factors influencing the injury severity between daytime and nighttime speeding-related crashes

Abstract

This study investigates the differences in the factors affecting the injury severity of speeding-related crashes occurring in the daytime and nighttime. Two log-likelihood ratio tests are conducted to validate whether speeding-related crashes classified by daytime and nighttime should be modeled separately. The result proves that separate modeling is necessary. Two correlated random parameter order probit models with heterogeneity in means are conducted using the data collected from 2018 to 2020 in the United States. Model estimation results show that urban areas, speed limits, and young and older drivers are temporal instability. Angle crashes, head-on crashes, intersections, downhill, exceeding the speed limit, drunk driving, and motorcycles are statistically significant in both models with an increased crash severity. Interaction and heterogeneity effects between random parameters are also reported. For instance, large trucks driving above the speed limit are more likely to increase the probability of severe injury.