An agent-based approach to modeling airlines, customers, and policy in the U.S. Air Transportation System

We present a modeling approach to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) due to the implementation of potential policies and the introduction of new technologies. Our approach simulates the responses of U.S. commercial airlines and other ATS stakeholders to these changes, which cumulatively result in consequences to the ATS. Our research is built upon an agent-based model-called the Airline Evolutionary Simulation (AIRLINE-EVOS)-which models airline tactical decisions about airfare and schedule, and strategic decisions related to fleet assignments, market prices, network structure, schedule evolution, and equipage of new technologies. AIRLINE-EVOS also models its own heterogeneous population of customer agents that interact with and respond to airline decisions. We describe this model, validation efforts, and a proof-of-concept experiment that demonstrates its capability for assessing policies that balance ATS stakeholder utilities to achieve greater system efficiency, robustness, and safety.