Validation of a Full Bayes methodology for observational before-after road safety studies and application to evaluation of rural signal conversions.
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 with no safety effect 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 by estimating no safety effect can account 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 stop 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 in that FB can provide similar results as EB.
Lan
Bo
B
Department of Civil Engineering, Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada. blan@ryerson.ca
Persaud
Bhagwant
B
Lyon
Craig
C
Bhim
Ravi
R
D000063:Accidents, Traffic / Q000517:prevention & control* / Q000706:statistics & numerical data; D001334:Automobile Driving / Q000331:legislation & jurisprudence; D001499:Bayes Theorem; D002140:California; D004779:Environment Design; D006801:Humans; D016012:Poisson Distribution; D012424:Rural Population