| description abstract | According to the National Academy of Engineering, innovations such as intelligent transportation systems, alternative fuels, and smart grids are critical to enhancing the resilience and sustainability of infrastructure systems. One key to realizing infrastructure innovations is effective policymaking based on a comprehensive analysis of the system. However, policy analysis in infrastructure systems is difficult because of the existence of complex adaptive behaviors and uncertainties. The objective of this paper is to create an ex-ante analysis framework using Agent-Based simulation to facilitate incorporation of uncertainties and complex adaptive behaviors of stakeholders in the analysis of infrastructure policies. The proposed framework includes three phases: definition, abstraction, and implementation. First, the steps in each phase will be discussed. Then, the application of the framework is demonstrated for the assessment of financial innovation policies for U.S. transportation infrastructure. Using hybrid agent-based/system dynamics techniques, a computational model is created to simulate the micro behaviors of state departments of transportation, private institutional investors, and the public. The results of the model include the visualization of the outcomes of different policies and the identification of the desired policy landscapes. The proposed framework provides policymakers with an integrated methodology through which an infrastructure policy problem is formulated, micro behaviors of the agents are modeled, the policy landscape is created, and the desired scenarios are identified. | |
