title: Tobit analysis of vehicle accident rates on interstate highways.
abstract: There has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a continuous variable that is left-censored at zero. Using data from vehicle accidents on Indiana interstates, the estimation results show that many factors relating to pavement condition, roadway geometrics and traffic characteristics significantly affect vehicle accident rates.
authors.affiliation: School of Civil Engineering, 550 Stadium Mall Drive, Purdue University, West Lafayette, IN 47907-2051, United States. panast@purdue.edu
authors.forename: Panagiotis Ch
authors.initials: PCh
authors.lastname: Anastasopoulos
authors.forename: Andrew P
authors.initials: AP
authors.lastname: Tarko
authors.forename: Fred L
authors.initials: FL
authors.lastname: Mannering
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001334:Automobile Driving / Q000706:statistics & numerical data*; D001336:Automobiles / Q000706:statistics & numerical data*; D006801:Humans; D007196:Indiana; D015233:Models, Statistical; D012044:Regression Analysis; D018570:Risk Assessment; D014481:United States