Agent-based modeling frameworks to support sustainable transportation applications: The examples of parking choice modeling and green routing evaluation
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The search for sustainable transportation strategies hinges on the availability of transportation modeling frameworks that are sensitive enough to reflect the impact of proposed strategies and policies, and to evaluate new and emerging ideas and applications designed to make the system more sustainable. Motivated by this urgent need, this doctoral study aims at utilizing agent-based modeling and simulation (ABMS) principles to develop advanced transportation modeling frameworks that can support sustainable transportation planning and applications. Within this broader context, the study focuses on two major case studies. The first study involves developing an agent-based transportation model of a university campus capable of accurately modeling the parking search process. A unique feature of the model is that it includes a sequential game-theoretic neo-additive capacity model to model parking behavior under uncertainty. The model accounts for drivers' psychological characteristics (i.e. optimistic and pessimistic attitudes) regarding parking availability in their most desirable lot, traits that are shown to play a major role in determining drivers' parking choices. To demonstrate the model's validity and potential applications, it is used to model north campus transportation system of University at Buffalo (UB), The State University of New York and to quantify the environmental cost of the parking search process, a cost that turns out to be substantial. The second case study considered in this dissertation focuses on evaluating the likely environmental benefits of an Intelligent Transportation Systems (ITS) that involves providing dynamic route guidance to travelers based on their lowest emissions or fuel consumption route. To do this, an integrated microscopic traffic-emissions model is developed by interfacing the Transportation ANalysis and SIMulation System (TRANSIMS) with the Motor Vehicle Emission Simulator (MOVES) emissions model developed by the Environmental Protection Agency (EPA). The integrated model is then used to evaluate the benefits of "green" routing in the Greater Buffalo-Niagara metropolitan area. Results indicate that green routing could result in significant reductions in emissions, but that this naturally comes at the expense of an increased travel time. Assuming a traffic stream of only passenger cars, green routing is shown to result in an almost 13% reduction in Carbon Monoxide (CO) emissions, and a corresponding 8% increase in travel time for the case study.