Safety Performance Function Development for Analysis of Bridges

Abstract

Bridges are an integral infrastructure component and, as such, have been the subject of extensive research efforts related to structural performance. However, there has been little study on the traffic safety performance of bridges, which have very different physical and operational characteristics compared with regular roadway facilities. This study develops safety performance functions (SPFs) for overall vehicle crashes and single-vehicle crashes occurring on major highway bridges in Alabama. The bridge characteristic data and crash information are obtained from three different databases. Geographic information systems (GIS) are used to spatially represent bridges as vectors and associate crashes to the bridges based on location attributes from the crash data. SPFs of several functional forms are developed and investigated for identifying the best model using negative binomial regression. The models are validated by comparing their relative predictive capabilities. This paper recommends models that fit the Alabama data well. These models can be used for estimating the expected number of crashes on bridges along major highways in Alabama.