Citation

Jovanis PP, Chang HL. Transp. Res. Rec. 1986; 1068: 42-51.

Copyright

(Copyright © 1986, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

unavailable

PMID

unavailable

Abstract

Consideration of highway safety studies in a time-space domain is used to introduce the concept that different study designs result in different underlying probability distributions describing accident occurrence. Poisson regression is proposed as a superior alternative to conventional linear regression for many safety studies because it requires smaller sample sizes and has other desirable statistical properties. Models are estimated using accident, travel mileage, and environmental data from the Indiana Toll Road. A pooled model including all accidents revealed that accident occurrence increases with automobile vehicle miles of travel (VMT), truck VMT, and hours of snowfall. Segmentation of the data into subsets that describe different types of collisions revealed that automobile accidents are much more sensitive to environmental conditions than are truck accidents. Use of the segmentation technique allowed a much clearer understanding of the effects of travel mileage on accident occurrence than could have been obtained from the pooled data alone.

Language: en

Keywords

HIGHWAY ACCIDENTS; STATISTICAL METHODS - Regression Analysis; MATHEMATICAL TECHNIQUES - Time Domain Analysis; MECHANICAL VARIABLES MEASUREMENT - Distance