Diverge-Merge Formation and MAC Control in Structured Airspace
2026-07-20 • Networking and Internet Architecture
Networking and Internet Architecture
AI summaryⓘ
The authors study managing groups of drones flying together in busy air highways with branches and merges. They design a system that helps drone groups split and join smoothly based on tasks and flight paths, keeping communication reliable while avoiding collisions or confusion. Their method works well even in crowded spaces and outperforms other communication protocols in simulations. This approach aims to improve drone traffic flow and safety in complex aerial corridors.
advanced air mobilityunmanned aerial vehicleformation flightcorridor-ramp branchingdiverge-merge controlclustering mechanismtime division multiple accessMAC protocoltraffic dynamicsreal-time communication
Authors
Kai Xiong, Xingyu Wu, Ba Zhang, Li Wei, Min Zeng, Supeng Leng
Abstract
The rapid scaling of advanced air mobility (AAM) makes corridor-based structured airspace a promising infrastructure for high-density unmanned aerial vehicle (UAV) traffic. Formation flight can improve corridor capacity by suppressing shockwave propagation, but rigid formations become inefficient or unsafe during ramp branching, merging, and congestion. To address this problem, this paper proposes a task-driven diverge-merge control framework for UAV formations in structured airspace. At the beginning, a corridor-ramp branching structured airspace model is established to characterize the traffic dynamics and spatial constraints. Building upon this, a fast task-driven clustering mechanism integrates spatial connectivity, flight intent, and aerial task interactions to enable real-time diverge and merge for ramp branching and traffic reshaping. To make the diverge-merge reconfigurations executable at the media access control (MAC) layer of the formation, a cluster-aware distributed time division multiple access (CAD-TDMA) protocol is further designed. It protects intra-cluster control synchronization while conservatively reusing low-risk inter-cluster slots. Simulation results show that the proposed diverge-merge algorithm maintains near-zero geometrical misclassification under severe physical overlapping and congestion. With the formation diverge-merge traces, CAD-TDMA achieves the best delay--loss--throughput tradeoff over fixed TDMA and WiFi MAC. It shows that the proposed formation control framework can jointly support real-time formation reconfiguration and reliable communication in corridor-ramp structured airspace.