Estimating truck accident rate and involvements using linear and Poisson regression models

Abstract

During the past few years, vehicle miles of travel (VMT) for large trucks having six or more wheels in contact with the road and having a gross weight greater than 10,000 lbs, have been steadily increasing. This has resulted in an increased interaction between large trucks and other vehicles which is being manifested in an increasing rate of fatal accidents involving large trucks. For example, between 1982 and 1984, fatal accident rates for 100 million VMT for large trucks in Virginia, increased by 54% while the rate for other vehicles (passenger cars, vans and pickups) remained approximately constant at less than a 0.3% increase. In order to arrest this increasing trend in large truck fatal accident rates, it is necessary that appropriate counter measures be developed. For this to be done, however, it is necessary to identify those factors that are associated with large truck accidents. A recent analysis of large truck accident data in Virginia, indicated that certain traffic and highway geometric characteristics may be associated with the occurrence of large truck accidents. In order to identify these specific characteristics and determine the extent to which they influence accident rates, a study was conducted with the primary objective of establishing relationships between large truck accidents, and traffic and roadway geometric variables. This paper presents mathematical relationships obtained through multiple linear and Poisson Regression Analyses, relating the number of truck involved accidents per year at a section of highway with traffic and geometric variables. These models indicate that the slope change rate (absolute curve of slope changes in the vertical direction divided by the highway segment), the average daily traffic, the percent of trucks and the difference in speed between trucks and non‐trucks influence the number of truck involved accidents at a given stretch of highway.