The objective of the study on which the paper is based was to explore the application of fully Bayesian methods for before-after road safety studies. Several variations of the methodology were evaluated with a simulated dataset in which hypothetical treatments were randomly assigned to high accident locations to mimic the common site selection process in road jurisdictions. It was confirmed that the fully Bayesian method can provide promising results in accounting for the regression-to-the-mean that results from this biased site selection process. The fully Bayesian method was then applied to California rural intersection data to evaluate the safety effect of conversion from unsignalized to signalized control. The results were then compared with those from the empirical Bayesian method, currently the accepted approach for conducting unbiased before-after evaluations. This comparison was generally favorable.
Abstract