title: Identifying repeat DUI crash factors using state crash records.
abstract: The objective of this study is to identify high risk factors that are closely related to repeat DUI crashes using readily available information from the state crash records. Survival analysis was used and a Cox proportional hazards model was developed using the police-reported crash records in the state of Louisiana. A variety of variables were found to be significant in predicting repeat DUI crashes. The factors included the characteristics of the drivers (gender, race, and age), the types of the vehicle (light truck/pick up truck or other), the characteristics of the crash (hit-and-run, driver violations, and whether the driver is arrested), the type of location (residential area or other), and the characteristics of the roadway (highway type and roadway type). This study provides a comprehensive picture of the repeat DUI crashes. The model can quantitatively predict the relative hazards of repeat DUI crashes. It can be used to identify the characteristics of the crash-involved DUI drivers who are at greatest risk of being involved in a subsequent DUI crash, allowing to apply appropriate remedial measures to reduce the risk.
authors.affiliation: Louisiana Transportation Research Center, Louisiana State University, Baton Rouge, LA 70808, USA. cehfu@lsu.edu
authors.forename: Haoqiang
authors.initials: H
authors.lastname: Fu
mesh_terms: D000063:Accidents, Traffic; D000328:Adult; D001741:Black or African American; D000367:Age Factors; D000435:Alcoholic Intoxication / Q000150:complications* / Q000453:epidemiology* / Q000208:ethnology; D001334:Automobile Driving; D004779:Environment Design; D005260:Female; D006801:Humans; D008145:Louisiana / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D012308:Risk Management; D012737:Sex Factors; D044465:White People; D055815:Young Adult