This paper introduces the use of discrete-time Markov chain models to represent the spatial-temporal behaviour of air traffic configurations near terminal areas. The airspace is first discretised using a rectangular grid and the occupancy status of each grid cell over each time interval is recorded. Each unique grid occupancy combination is then vectorised to define a unique state. Using the Baum-Welch algorithm, the transition probability between the set of possible states is then determined. Using real air traffic data, the approach is used to model the air traffic behaviour around a large Australian airport. The model is evaluated using hold out data and applied to the novel application of dynamic airspace allocation for integrated unmanned aircraft operations.
Air Traffic Configuration Modelling and Dynamic Airspace Allocation using Discrete-Time Markov Chains
01.10.2019
1542814 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Dynamic Airspace Configuration
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