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A stochastic modeling and analysis approach to strategic traffic flow management under weather uncertainty

Abstract:

In this article, we introduce a promising framework for representing an air traffic flow (stream) and flow-management action operating under weather uncertainty. We propose to use a meshed queuing and Markov-chain model-specifically, a queuing model whose service-rates are modulated by an underlying Markov chain describing weather-impact evolution-to capture traffic management in an uncertain environment. Two techniques for characterizing flow-management performance using the model are developed, namely 1) a master-Markov-chain representation technique that yields accurate results but at relatively high computational cost, and 2) a jump-linear system-based approximation that has promising scalability. The model formulation and two analysis techniques are illustrated with numerous examples. Based on this initial study, we believe that the interfaced weather-impact and traffic-flow model analyzed here holds promise to inform strategic flow contingency management in NextGen. © 2011 by The MITRE Corporation. Published by the American Institute of Aeronautics and Astronautics, Inc.