Multiattribute Utility Theory Approach for ITS Planning

ITS market package screening is one of the fundamental tasks in Intelligent Transportation System (ITS) planning. Recognizing that the state-of-the-art still falls short of developing a local ITS market package plan in a systematic manner, this paper presents a Multi-Attribute Utility Theory (MAUT) approach to address this problem. The MAUT model was constructed based on ITS planning objectives and available data resources. With the calculation of aggregated utilities, the market packages were ranked so decision makers can make rational choices accordingly. Sensitivity analysis was conducted to examine how changes in performance measure weights would affect the final ranking results. Based on the original MAUT model, uncertainties that may influence final outcomes were further investigated. Instead of using deterministic assessments, the benefit levels of an ITS package in achieving a certain goal were evaluated using probabilistic assessments. The resultant rankings of the ITS alternatives were then assessed using the expected utility values. A comparative study was performed on the original MAUT model and the MAUT model that integrated uncertainties. The results indicated that the uncertainties in the benefits of ITS market packages slightly affected the final rankings of the alternatives. Compared to the conventional market package screening method, the MAUT approach provides decision makers more detailed information and data in order to better understand which ITS strategies are more suitable to address the local transportation problems and user needs.