title: Characteristics of rear-end accidents at signalized intersections using multiple logistic regression model.
abstract: Multi-vehicle rear-end accidents constitute a substantial portion of the accidents occurring at signalized intersections. To examine the accident characteristics, this study utilized the 2001 Florida traffic accident data to investigate the accident propensity for different vehicle roles (striking or struck) that are involved in the accidents and identify the significant risk factors related to the traffic environment, the driver characteristics, and the vehicle types. The Quasi-induced exposure concept and the multiple logistic regression technique are used to perform this analysis. The results showed that seven road environment factors (number of lanes, divided/undivided highway, accident time, road surface condition, highway character, urban/rural, and speed limit), five factors related to striking role (vehicle type, driver age, alcohol/drug use, driver residence, and gender), and four factors related to struck role (vehicle type, driver age, driver residence, and gender) are significantly associated with the risk of rear-end accidents. Furthermore, the logistic regression technique confirmed several significant interaction effects between those risk factors.
authors.affiliation: Department of Civil and Environmental Engineering, College of Engineering, University of Central Florida, Orlando, 32826, USA. yxd22222@yahoo.com
authors.forename: Xuedong
authors.initials: X
authors.lastname: Yan
authors.forename: Essam
authors.initials: E
authors.lastname: Radwan
authors.forename: Mohamed
authors.initials: M
authors.lastname: Abdel-Aty
mesh_terms: D000063:Accidents, Traffic / Q000145:classification* / Q000706:statistics & numerical data; D000328:Adult; D000368:Aged; D001334:Automobile Driving; D019992:Databases as Topic; D004779:Environment Design; D005260:Female; D005431:Florida / Q000453:epidemiology; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D018570:Risk Assessment; D012307:Risk Factors; D012449:Safety