title: Identifying the factors contributing to the severity of truck-involved crashes.
abstract: To address the dilemma between the need for truck transportation and the costs related to truck-involved crashes, the key is to identify the risk factors that significantly affect truck-involved crashes. The objective of this research is to estimate the effects of the characteristics of traffic, driver, geometry, and environment on severity of truck-involved crashes. Based on four crash severity categories (fatal/incapacitating, non-incapacitating, possible injury, and no injury/property damage only), a multinomial logit model is conducted to identify the risk factors. The investigation of risk ratios indicates that lower traffic volume with higher truck percentage is associated with more serious traffic crash with fatal/incapacitating injury while a non-standard geometric design is the main cause of non-incapacitating crashes. The influences of weather are significant for the possible-injury crashes while driver condition is the principal cause of no-injury/property-damage-only crashes. In addition, the statistical results demonstrate that the influence of the truck percentage is significant. One-unit change in the truck percentage will cause more than one times probability of being in an injury.
authors.affiliation: a Center of Transportation Research , The University of Tennessee , 600 Henley Street, Knoxville , 37996 TN , USA.
authors.forename: Chunjiao
authors.initials: C
authors.lastname: Dong
authors.forename: Stephen H
authors.initials: SH
authors.lastname: Richards
authors.forename: Baoshan
authors.initials: B
authors.lastname: Huang
authors.forename: Ximiao
authors.initials: X
authors.lastname: Jiang
mesh_terms: D000063:Accidents, Traffic / Q000145:classification* / Q000706:statistics & numerical data*; D000328:Adult; D000066448:Driving Under the Influence; D004779:Environment Design; D004867:Equipment Design; D005260:Female; D006801:Humans; D015601:Injury Severity Score; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D018986:Motor Vehicles / Q000706:statistics & numerical data*; D012307:Risk Factors; D012309:Risk-Taking; D012737:Sex Factors; D013714:Tennessee; D014887:Weather
keywords: MNL model; crash severity; traffic safety; trucks