Structural Design of UAV Approach and Departure Procedures in Urban Obstacle Environments

With the growing demand for unmanned aerial vehicle (UAV) operations in urban low-altitude airspace, the structure of vertiport approach and departure airspace will become a critical factor in capacity limitation and safe operations. To address the core bottleneck of high-density operations in future Urban Air Mobility (UAM), this research investigates an optimal design method for UAV approach and departure airspace structures at vertiports. A structured multi-layer funnel-shaped hybrid airspace model is constructed, and an airspace efficiency optimization function is designed. Genetic algorithms are employed to optimize the airspace parameters. The airspace optimization design was calculated within urban obstacle spaces. Through comparative analysis with six typical airspace configurations in terms of operational efficiency, and under different obstacle environments and UAV operational intervals, it is found that the designed airspace demonstrates significant balance in overall performance, while the design algorithm maintains stable effectiveness across various conditions. The results indicate that strategies relying simply on enlarging airspace dimensions to enhance capacity involve clear performance trade-offs. In contrast, a relatively compact funnel-shaped structure achieves coordinated optimization across multiple metrics by eliminating radial gradients and simplifying flight paths. The proposed genetic algorithm-based optimal design method for UAV approach and departure structures in urban obstacle spaces can effectively identify the optimal parameter combinations, ensuring the safety of UAV operations in urban environments and improving the operational efficiency of vertiport airspace.