Large-Truck Involved Crashes: An Exploratory Injury Severity Analysis

In recent years, a growing concern related to large-truck accidents has increased due to potential economic impacts and level of injury severity that can be sustained. Yet, studies related to large-truck involved crashes are scarce and lack human behavior factors that can greatly influence crash outcomes. In this study, the authors present an analysis of data from the fusion of several national data sets addressing large-truck involved injury severity. This is done by considering human, road-environment, and vehicular factors in large-truck involved crashes on U.S. interstates. A random parameter ordered probit model was estimated to predict the likelihood of five injury severity outcomes—fatal, incapacitating, non-incapacitating, possible injury, and no injury. The modeling approach accounts for possible unobserved effects relating to human, vehicular, and road environment factors not present in the data. Estimation findings indicate that the level of injury severity is highly influenced by a number of complex interactions of factors and that the effect of the some of the factors can vary across the observations.

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