Dynamic Airspace Control via Spatial Network Morphing

In the coming years, a plethora of new and autonomous aircraft will fill the airspace, approaching a density similar to the ground traffic below. At the same time, human pilots that use the prevailing navigational tools and decision processes will continue to fly along flexible trajectories, now contending with inflexible non-human agents. As the density of the airspace increases, the number of potential conflicts also rises, leading to a possibly disastrous cascade effect that can fail even the most advanced tactical see-and-avoid algorithms. Any engineered solution that maintains safety in the airspace must satisfy both the computational requirements for effective airspace management as well as the political issue that human-pilots should maintain priority in the airspace. To this end, the research presented here expands on a concept of air traffic management called the Lane-Based Approach and describes a method for morphing the underlying spatial network to effectively deal with multiple potential conflicts. The spatial-network, which represents a model of the airspace occupied by autonomous aircraft, is mutated with respect to extrapolated human-piloted trajectories, leading to a real-world execution that modifies the trajectories of multiple vehicles at once. This reduces the number of pairwise deconfliction operations that must occur to maintain safe separation and reduces the possibility of a cascade effect. An experiment using real Automatic Dependent Surveillance-Broadcast (ADS-B) data, representing human-piloted aircraft trajectories, and simulated autonomous aircraft will demonstrate the proposed method.