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Existing traffic analysis tools such as microscopic traffic simulation models and macroscopic/static travel demand forecasting methods have inherent methodological limits and, as a results, fall short in providing adequate modeling capability when faced with the ever-increasing complexity of today’s transportation systems. In the meanwhile, computational and algorithmic innovation in other areas offers a promising opportunity, once incorporated, to leapfrog from existing analysis capabilities. The over-arching objective of this research is to develop a theoretically sound, behaviorally robust, and computationally efficient simulation-based traffic analysis modeling system that seamlessly integrates the agent-based modeling and simulation (ABMS) concept and methodologies with existing and emerging vehicular simulation tools, to explore the untapped possibilities of traffic modeling and analysis functionalities not available using traditional approaches. Our proposed model system – dubbed VASTO (Evolutionary Agent System for Transportation Outlook) – incorporates innovative ideas in agent-based system design, configuration and implementation.

For more information please check VASTO project website: VASTO
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