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.

Original document

The different versions of the original document can be found in:

• http://pdfs.semanticscholar.org/8a47/bf6ce4abcf97e76f6a3a2233fad42fefe353.pdf

• http://arc.aiaa.org/doi/pdf/10.2514/6.2011-6514,

http://dx.doi.org/10.2514/6.2011-6514

• http://www.researchgate.net/profile/Craig_Wanke/publication/268292589_A_Stochastic_Modeling_and_Analysis_Approach_to_Strategic_Traffic_Flow_Management_under_Weather_Uncertainty/links/54c0f02c0cf28a6324a463fd.pdf,

http://arc.aiaa.org/doi/pdf/10.2514/6.2011-6514,

https://academic.microsoft.com/#/detail/2323086495