title: Factors associated with automobile accidents and survival.
abstract: This paper develops an econometric model for vehicles' inherent mortality rate and estimates the probability of accidents and survival in the United States. Logistic regression model is used to estimate probability of survival, and censored regression model is used to estimate probability of accidents. The estimation results indicated that the probability of accident and survival are influenced by the physical characteristics of the vehicles involved in the accident, and by the characteristics of the driver and the occupants. Using restrain system and riding in heavy vehicle increased the survival rate. Middle-aged drivers are less susceptible to involve in an accident, and surprisingly, female drivers are more likely to have an accident than male drivers. Riding in powerful vehicles (high horsepower) and driving late night increase the probability of accident. Overall, the driving behavior and characteristics of vehicle does matter and affects the probabilities of having a fatal accident for different types of vehicles.
authors.affiliation: Department of Urban Planning and Engineering, Yonsei University, 134 Shinchon-dong, Seodaemun-gu, Seoul 120-749, South Korea. hskim66@yonsei.ac.kr
authors.forename: Hong Sok
authors.initials: HS
authors.lastname: Kim
authors.forename: Hyung Jin
authors.initials: HJ
authors.lastname: Kim
authors.forename: Bongsoo
authors.initials: B
authors.lastname: Son
mesh_terms: D000063:Accidents, Traffic / Q000401:mortality / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D001334:Automobile Driving / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D017059:Models, Econometric; D011336:Probability; D012044:Regression Analysis; D012307:Risk Factors; D016019:Survival Analysis