Predicting Truck Crash Involvement: A Commercial Driver Behavior-Based Model

With safety as a top priority, the trucking industry has worked diligently to identify novel methods for further reducing an already record low number of truck crashes. In an attempt to realize that goal, this research has utilized an archival research design to identify truck driver behaviors that frequently accompany future crash records. Specifically, the researchers collected two years’ worth of recent crash, violation and conviction data for 582,772 U.S. commercial motor vehicle drivers and found dozens of driver infractions that were significant predictors of future crash involvement. In addition to pinpointing which specific behaviors were significantly linked to commercial vehicle crashes, the researchers quantified the strength of each association, revealing future crash risk increases that ranged from 26 to 96 percent. Beyond measuring individual driver behaviors, principal components analysis was used to group the more than thirty driver infractions from this study into 11 related factors. This smaller set of negative driver behavior categories was then entered into a logistic regression model, which revealed the classes of behaviors that trucking companies and enforcement agencies should be most proactive in targeting for enhanced driver training and enforcement efforts, respectively.