Conceptual Framework for Dynamic Optimal Airspace Configuration for Urban Air Mobility

Abstract

In this work, a framework for optimizing the configuration of service areas in airspace into disparate partitions is demonstrated in the context of urban air mobility (UAM) operations. This framework is applied to a conceptual UAM airspace configuration, where a free-flight-based routing service and a corridor-based routing service are dynamically allocated to control different portions of the airspace over time, based on traffic demand. This allocation seeks to determine the least amount of structured coordination (in terms of active flight corridors) needed to safely meet traffic demand. This framework integrates several modeling components, including a novel spatiotemporal graph theoretic UAM traffic model capable of optimizing vehicle trajectories while maintaining multiple flight constraints. Airspace complexity and trajectory efficiency metrics are both implemented to quantify the overall safety and cumulative cost of routing a set of missions according to a given airspace configuration. Finally, spatial airspace partitions are managed using a support vector machine-based algorithm. Metrics are then applied to optimize the airspace configurations, according to desired objectives. Simulated results show that this framework can produce airspace configurations that ensure safety, while providing trajectory efficiency more effectively than purely uniform free-flight or corridor-based flight. This is demonstrated for both low- and high-density traffic scenarios.