A Digital-Twin Based Airspace Corridor Design and Dynamic Configuration for High-density UAS Traffic Management

This paper proposes a dynamic airspace corridor planning method based on a complex urban digital twin model. The method fully considers multiple environmental factors such as urban microclimate variations, signal interference, temporary no-fly zones and building density. It can generate highly accurate gridded airspace information in real time, enabling safe and efficient airspace corridor planning for large-scale, high-density and dynamically changing multi-UAV cooperative operations. This study adopts a divide-and-conquer approach that combines fluid models, the A* path planning algorithm, and Laplace equation solving to construct adaptive, obstacle-avoiding, high-density airspace corridors within hierarchical subregions. Through refined airspace zoning control and dynamic optimization, the system strictly enforces safety intervals throughout the planning process, ensuring the minimum safety distance between corridors and minimising the potential collision risks between UAVs. The proposed dynamic airspace corridor planning method has been evaluated in a randomly generated environment and an urban digital twin model. Experimental results show that even in complex urban environments with dense high-rise buildings and drastic wind speed variations, the method can still quickly construct a feasible airspace corridor network. In addition, using a graph-theory based local optimisation algorithm, the method can achieve dynamic, seamless interconnection of multi-segment airspace corridors and flexibly adjust deployment strategies for redundant corridors. In the event of emergencies or drastic environmental changes, these redundant corridors can serve as emergency bypass routes, ensuring that UAVs can avoid obstacles and safely maintain continuous flight,