A logistic model of the effects of roadway, environmental, vehicle, crash and driver characteristics on hit-and-run crashes.

Leaving the scene of a crash without reporting it is an offence in most countries and many studies have been devoted to improving ways to identify hit-and-run vehicles and the drivers involved. However, relatively few studies have been conducted on identifying factors that contribute to the decision to run after the crash. This study identifies the factors that are associated with the likelihood of hit-and-run crashes including driver characteristics, vehicle types, crash characteristics, roadway features and environmental characteristics. Using a logistic regression model to delineate hit-and-run crashes from nonhit-and-run crashes, this study found that drivers were more likely to run when crashes occurred at night, on a bridge and flyover, bend, straight road and near shop houses; involved two vehicles, two-wheel vehicles and vehicles from neighboring countries; and when the driver was a male, minority, and aged between 45 and 69. On the other hand, collisions involving right turn and U-turn maneuvers, and occurring on undivided roads were less likely to be hit-and-run crashes.