As the starting point of any transportation related study, an accurate analysis and forecast for transportation demand is important for appropriate planning of necessary technological improvements. Multiple modeling and simulation techniques are available, including bottom-up agent-based modeling and top-down system dynamics. The purpose of this research is to build a multi-modal transportation model using the System Dynamics approach (Ground and Air Modes Explorer) supported by an existing agent-based model Mi. These two complementary models were calibrated against each other to ensure equivalency of the outputs within a given range of input values. The system dynamics model matched historic data and generated future forecasts for various scenarios including different economic situations, capacity constraints on the air transportation system, and the introduction of a new point-to-point air service. This new model can be used as a surrogate of the computationally expensive agent-based model, allowing quick exploration of multiple scenarios.
展开▼
