Many Intelligent Transportation Systems (ITS) are aging, experiencing significant maintenance needs, or becoming functionally obsolete. The primary output of this thesis is a methodology for prioritizing the maintenance and replacement of aging or obsolete ITS infrastructure. The methodology is structured such that existing ITS are prioritized according to the need for their obsolescence to be addressed and such that candidate interventions for those ITS are ranked. The methodology is designed to be practical to implement and widely applicable to disparate ITS technologies and is based on certain principles of transportation asset management and multi-criteria decision analysis methods from systems engineering. The major research contribution is thus a new application of existing techniques. This thesis includes a case study that applies part of the methodology to 31 Variable Message Signs on the outer loop of the Interstate-64 beltway in the Hampton Roads metropolitan area of Virginia. The assets are ranked using historical work order data from maintenance records and traffic volume data. The major recommendation is the implementation of the methodology in the form of an automated system that continuously receives data and updates asset priority to inform obsolescence management decisions. It is recommended that the system eventually be integrated into a comprehensive, automated ITS asset management system and that the maintenance data gathered for existing ITS be used for predicting life cycle costs of future ITS investments.