A hybrid centralized-decentralized traffic control framework for unmanned aerial vehicles in urban low-altitude airspace - Xiangdong Chen; Shen Li; Meng Li (Communications in Transportation Research)
Urban air mobility (UAM) represents a transformative approach to alleviating ground-level congestion by transitioning from two-dimension (2D) to three-dimension (3D) transportation systems. Envisioned as a safe, sustainable, and efficient mode of urban transit, UAM leverages aerial space to reduce dependence on traditional road infrastructure while addressing traffic congestion challenges in urban mobility. However, the rapid growth in aerospace transportation demand, coupled with the complexity of managing large-scale unmanned aerial vehicle (UAV) operations in 3D airspace, challenges the effectiveness of traditional traffic management systems. To address these challenges, this study proposes a hybrid framework for UAV air traffic control that integrates centralized and decentralized approaches. A 3D air traffic network is modeled in low-altitude airspace, capturing detailed 2D and 3D conflict relationships. The concept of a “virtual flight container” (VFC) is introduced to regulate UAV space–time trajectories, ensuring conflict-free, low-delay operations while minimizing real-time computational requirements, especially in high demands. The problem is addressed using a bi-level optimization approach: The upper level focuses on solving the traffic assignment problem, considering airway capacity constraints, while the lower level designs space–time trajectories to ensure conflict-free operations and enhance traffic efficiency, thereby complementing the traffic control scheme. Numerical experiments validate the proposed framework, highlighting its effectiveness in improving traffic efficiency and network throughput. Key insights are provided regarding the role of network structure, the placement of take-off and landing points, and control parameters in optimizing UAM operations.