Prioritization of safety countermeasures for the state of Louisiana using fuzzy inference systems

In this study a fuzzy inference system is proposed for prioritization of countermeasures aimed at improving safety in the state of Louisiana. Countermeasures are prioritized based on their collective performance on cost, expected crash reduction and the severity of the problem they address. These three decision parameters can have six permutations in terms of their relative importance in decision making. In order to make the prioritization procedure handier for decision makers, the inference system is capable of being run under all six possible cases. Current safety standards influence the importance attached to crash reduction performance and severity of the problem area addressed. Similarly, the available budget will influence the importance of cost in the process. The analyst thus selects one of the six permutations of decision criteria that best reflects their hierarchical order of importance in the situation being analyzed. In developing the procedure, input on problem severity was gathered from previous research on safety conditions in Louisiana, and research conducted as part of the development of the Traffic Safety Manual was used to estimate cost and the crash reduction potential of individual countermeasures