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A jump-linear model based sensitivity study for optimal air traffic flow management under weather uncertainty

Abstract:

In this paper, we develop an analytical approach to planning air traffic flow management (TFM) strategies under uncertain weather. To do that, we model the dynamics of an air traffic flow under uncertain weather as a discrete jump-linear system, which enacts the tracking of transient traffic congestion statistics. We then conduct a sensitivity analysis of traffic congestion to disturbances introduced by mean inflow rate and flow restriction constraint. The integrated framework of jump-linear modeling and sensitivity analysis permits optimal planning for flow bkp_redistribution and flow restriction redesign. We demonstrate the design procedure through an example of a major flow splitting into multiple flows that enter a bank of weather zones.