Dynamic Airspace Management for Enhanced ATM Safety and Efficiency (original) (raw)
2018, Proceedings of the 31th Congress of the International Council of the Aeronautical Sciences (ICAS 2018), Belo Horizonte, Brazil
The steadily increasing air traffic demand has highlighted a need to evolve existing Air Traffic Flow Management (ATFM) methodologies by increasing automation support in airborne and ground-based systems and more flexible modulation of air traffic controller workload. Dynamic Airspace Management (DAM) aims at optimising the demand-capacity balance in all airspace regions at all times with a particular focus on capacity modulation measures. In this paper, we propose a novel DAM approach supporting the dynamic morphing of airspace sector boundaries based on an optimal-control formulation. The Eulerian continuity principle is used to model the air traffic flow at a macroscopic scale and workload-based capacity constraints are considered to determine the optimal variations in sector volumes. The demand levels are determined and the traffic flow theory based on the principle of continuity is used to propagate the demand across airspace sectors, approximated as 2D polygons. The newly developed sector morphing framework will be integrated into next-generation ATFM decision support systems to drive adaptive human-machine interfaces and interactions supporting more efficient exploitation of airspace resources.
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