title: Parallel risks of automobile collisions and thefts: a potential means of separating driver and vehicle factors.
abstract: This paper examines the value of data published by the Highway Loss Data Institute (HLDI) on the collision frequency of different automobile models as a potential guide to vehicle safety. It is argued that these data fail to control for factors other than design, including vehicle usage and driving quality. An alternative measure of collision risk, controlled for some of these factors, is constructed employing the fact that theft risk is determined by many of the same usage characteristics as collision risk. This alternative measure is validated by demonstrating that it is a more effective predictor of injury risk than collision frequency. In conclusion it is argued that if HLDI collision data are to provide a more useful guide to the relative design safety of different automobile models, the data need to be controlled for a wider range of potentially confounding factors.
authors.affiliation: Rutgers, State University of New Jersey, Newark.
authors.forename: S
authors.initials: S
authors.lastname: Field
authors.forename: R V
authors.initials: RV
authors.lastname: Clarke
mesh_terms: D000056:Accident Prevention; D000063:Accidents, Traffic / Q000517:prevention & control / Q000706:statistics & numerical data; D000293:Adolescent; D000328:Adult; D000368:Aged; D001334:Automobile Driving; D001336:Automobiles / Q000706:statistics & numerical data; D004867:Equipment Design; D006801:Humans; D007346:Insurance, Accident / Q000706:statistics & numerical data; D008875:Middle Aged; D012307:Risk Factors; D012449:Safety; D013800:Theft / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000453:epidemiology