Abstract
A new airspace design concept, tube networks, could enable high-density operations with less air traffic control workload. To construct tubes optimally, it is necessary to identify the commonality of flight trajectories. This paper proposes a new strategy to cluster great circle flight trajectories for forming tubes. The Hough transform is applied to identify groups or clusters of great circle trajectories that could form the tube networks. The genetic algorithm is then applied to optimize the tube network. Results show that small deviations from great circle routes could yield tubes that accommodate significant traffic levels within feasible computational time.
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