Motor vehicle drivers' injuries in train-motor vehicle crashes

The three injury severity models evaluated were: ordered probit, multinomial logit and random parameter logit. A comparison of the three models based on different criteria showed that the random parameter logit model and multinomial logit model were more suitable for injury severity analysis of motor vehicle drivers involved in crashes at highway-rail grade crossings. Some of the factors that increased the likelihood of more severe crashes included higher train and vehicle speeds, freight trains, older drivers, and female drivers. Where feasible, reducing train and motor vehicle speeds and nighttime lighting may help reduce injury severities of motor vehicle drivers.