Estimating driver's crash risk based on the extended Bradley-Terry model

Abstract

Quantifying driver crash risks has been difficult because the exposure data are often incompatible with crash frequency data. Induced exposure methods provide a promising idea that a relative measurement of driver crash risks can be derived solely from crash frequency data. This paper describes an application of the extended Bradley–Terry model for paired preferences to estimating driver crash risks. We estimate the crash risk for driver groups defined by driver–vehicle characteristics from log-linear models in terms of a set of relative risk scores by using only crash frequency data. Illustrative examples using police-reported crash data from Hawaii are presented.