Intelligent Transportation Systems (ITS) aim at reducing travel times by making more efficient use of the existing transportation infrastructure through the use of state-of-the-art information technology solutions. It is, however, important to determine the impact of these technologies before any deployment decisions are made. In this paper, we propose a new evaluation methodology that incorporates a full marginal cost (FMC) approach with microscopic simulation as the basis for comparing the effectiveness of ITS technologies. The use of the FMC approach allows us to observe the impact of an ITS technology not only on travel times but also on other cost categories such as accident costs, infrastructure and environmental costs. Our proposed methodology employs microscopic simulation as a tool for accurately estimating the impact of VMS route guidance on congestion levels that are in turn used as the input to the FMC functions. The use of microscopic simulation in the context of FMC methodology allows us to capture the real impact of ITS technologies. In this paper, a detailed case study that evaluates the effectiveness of traveler information via Variable Message Signs in a highly congested network in South Jersey (SJ) is presented. The study network is modeled and calibrated using PARAMICS simulation software. The simulation routine is modified to model a realistic VMS routing algorithm and route choice behavior using the Advanced Programming Interface (API) option of PARAMICS. The effectiveness of several VMS location scenarios is determined in this simulation model based on Full Marginal Cost reductions obtained for trips along the main route between SJ and Philadelphia CBD. Microscopic simulation based FMC values are shown to be effective measures that can be used to make sound policy decisions. This is due to the fact that the FMC values can be analyzed in terms of their individual components to understand the impact of the reductions in travel times on externalities, such as congestion, air pollution, and noise.