01044960

Component

The objective of this study is to identify high risk factors that are closely related to repeat DUI crash 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 record in the state of Louisiana. A variety of variables were found significant in predicting DUI recidivism. The factors include the characteristics of the drivers (gender, race, and age), the types of the vehicle (car, light truck/pick up, and other), the driver attitudes to the BAC test (refusal or not), the characteristics of the crash (severity, driver violations, and whether the driver is arrested), the type of location (residential area or not), and the characteristics of the roadway (functional classification and roadway type). The results of this study provide a more comprehensive picture of the repeat DUI crashes. The model can quantitatively predict the relative hazards of DUI recidivism. It can be used to create profiles of the repeat DUI offenders, identify DUI offenders who are at greatest risk of being involved in a subsequent DUI crash so that appropriate remedial measures are applied to reduce the risk.

01042056

07-1003

English

19p

2007

Transportation Research Board 86th Annual Meeting

CD-ROM

Figures (6) ; References (24) ; Tables (1)

Alcohol breath tests; Blood alcohol levels; Crash causes; Demographics; Drunk driving; High risk drivers; Linear regression analysis; Mathematical models; Pickup trucks; Recidivism; Risk analysis; Statistical analysis

Data and Information Technology; Highways; Safety and Human Factors; Security and Emergencies; Society; I83: Accidents and the Human Factor

Transportation Research Board Annual Meeting 2007 Paper #07-1003

BTRIS, TRIS, TRB

Feb 8 2007 5:35PM