Improving ITS planning with multicriteria decision analysis
Intelligent Transportation Systems (ITS) planning is characterized by making decisions on various ITS strategies. Since the state-of-the-art in ITS planning still falls short of developing ITS plans in a systematic manner, research is needed to understand, formulate, and solve the two major problems identified in ITS planning. Specifically, at the “strategic” level, an innovative approach will be developed to screen the ITS market packages that best address local needs and local transportation problems. At the “executive” level, an appropriate approach will be developed to identify the ITS deployments that are most beneficial to the planning area. In this dissertation, a multi-attribute utility theory (MAUT) model was first constructed and validated for ITS market package screening. ITS market packages were ranked using the values of aggregated utilities and sensitivity analyses were vi conducted to examine how changes in performance measure weights affect the final ranking results. In addition, uncertainties that may influence the final outcomes were further investigated. A comparative study of an original MAUT model and a MAUT model integrating uncertainties indicates that uncertainties can affect the final rankings of the alternatives. Secondly, an ELECTRE method was proposed to address problems resulting from comparing various ITS deployments. A modified ELECTRE-I method was developed to compare a number of ITS alternatives with respect to multiple objectives. By varying the weighting scheme to favor different criteria and performing a sensitivity analysis, the nondominated alternative was identified. A comparative study was conducted on the MAUT and ELECTRE methods. It was found that the MAUT approach and the ELECTRE method can both be applied to ITS deployment comparison problems. In some cases, the differences between them make one more suitable than the other in some cases. Based on the comparative study recommendations were made regarding the application of MAUT and ELECTRE to the decision analysis in ITS planning.