Collisions between heavy trucks and passenger cars are a major concern because of the severity of injuries. This research has two objectives. One is to examine the impact of various factors on injuries to passenger car occupants involved in such collisions. Due to the complex interaction of factors influencing injury levels in truck-car collisions, the ordered probit model is used to identify specific variables significantly influencing levels of injury in two-vehicle rear-end involvements on divided roadways. Another objective is to demonstrate the use of the ordered probit in this complex highway safety problem. A set of vehicle, occupant, roadway, and environmental factors expected to influence injury severity was developed. Given two-vehicle passenger car-truck rear-end collisions, the variables that increase passenger vehicle occupant injury severity include darkness; high speed differentials; high speed limits; grades, especially when they are wet; being in a car struck to the rear (as opposed to being in a car striking a truck to the rear); driving while drunk; and being female. The interaction effects of cars being struck to the rear with high speed differentials and car rollovers were significant. Variables decreasing severity include snowy or icy roads, congested roads, being in a station wagon struck to the rear (as opposed to a sedan), and using a child restraint. With injuries ordered in five classes from no injury to fatalities, the marginal effects of each factor on the likelihood of each injury class are reported.
Applying the Ordered Probit Model to Injury Severity in Truck-Passenger Car Rear-End Collisions
Transportation Research Record
Transportation Research Record: Journal of the Transportation Research Board ; 1635 , 1 ; 63-71
1998-01-01
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Applying the Ordered Probit Model to Injury Severity in Truck-Passenger Car Rear-End Collisions
Online Contents | 1998
|Analysis of large truck crash severity using heteroskedastic ordered probit models
Online Contents | 2011
|Crash Injury Severity Analysis Using Bayesian Ordered Probit Models
British Library Online Contents | 2009
|