Lagrangian Delay Predictive Model for Sector-Based Air Traffic Flow
STANFORD UNIV CA DEPT OF AERONAUTICS AND ASTRONAUTICS
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We derive a control theoretic model of sector-based air traffic flow using hybrid automata theory. This model is Lagrangian, meaning that it models the properties of the system along its trajectories. A subset of this model is used to generate analytic predictions of air traffic congestion we define and derive a dynamic sector capacity which we use to predict the time it takes to overload a given portion of airspace. This result links our approach with Eulerian models, which account for temporal variations of parameters in a fixed volume. We design and validate an air traffic flow simulator, to assess the accuracy of our predictions. The simulator is then used to show that flow scheduling and conflict resolution may be decorrelated under assumptions on aircraft density.
- Numerical Mathematics
- Air Navigation and Guidance