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.


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    Title :

    Air Traffic Configuration Modelling and Dynamic Airspace Allocation using Discrete-Time Markov Chains


    Contributors:


    Publication date :

    2019-10-01


    Size :

    1542814 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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