title: A procedure for allocating a safety improvement budget among treatment types.
abstract: Highway agencies often have to decide how to allocate a road safety budget among different safety treatments. While some of the traditional resource allocation procedures can provide information to assist in making this decision, they are not tailor-made for this specific problem. In particular, uncertainty in accident frequency estimates can lead to difficulties if the procedure is inherently deterministic. A procedure is presented for using recent safety estimation theory and benefit-cost analysis to accommodate uncertainty in accident frequency estimates while addressing the specific decision-making problem at hand. In the procedure, a site can be treated if the difference between the safety benefit and the treatment cost--the net benefit--is large enough. Recognizing that safety benefits vary across sites and treatment types, the procedure allows a budget to be allocated to different programmes but ensures that the smallest net benefit--the net marginal benefit threshold--is the same for all programmes. The procedure estimates the number and costs of sites for each treatment type for which the net benefit exceeds a specific threshold that is adjusted such that the total treatment cost is in line with the available budget. While this methodology can be useful for agencies responsible for road safety improvements, the data requirements could pose a problem for some jurisdictions. A further difficulty is that the computations required are extensive, particularly in cases where uncertainty to other data items requires the use of sensitivity analysis. To facilitate these computations, a computer programme is available from the authors.
authors.affiliation: Department of Civil Engineering, Ryerson Polytechnical University, Toronto, Canada.
authors.forename: B
authors.initials: B
authors.lastname: Persaud
authors.forename: A
authors.initials: A
authors.lastname: Kazakov
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control*; D002017:Budgets; D003657:Decision Making; D006801:Humans; D017059:Models, Econometric; D009864:Ontario; D012449:Safety