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<p>This paper addresses the challenge of designing final approach airspace for multi-rotor UAVs operating in complex urban environments. We propose a novel airspace framework based on a multi-branch strategy that integrates obstacle avoidance, UAV safe constraints, and traffic management. The model structures airspace into concentric annular layers with hovering points, accounting for urban obstacles through three geometric intersection states (non-intersection, long-side, broad-side). Key parameters—including layer radii, hovering point distribution, and altitude—are derived computationally using safety constraints, UAV maneuvering limits, and obstacle geometries. The approach process is governed by the branch blockade principle(inspired by railway section control) and a multilevel first-come-first-served (FCFS) strategy to ensure collision-free sequencing. Simulations of Tokyo Midtown scenarios validate the model’s efficacy, demonstrating how acceleration (0.5–3&#xa0;m/s²) and speed limits (2–5&#xa0;m/s) impact landing time and processing efficiency. Results show that higher acceleration and speed ceilings reduce average landing time under high-density traffic, while strategic parameter coordination unlocks critical efficiency thresholds. This work provides a scalable solution for urban vertiport operations.</p>

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Annular layered airspace design in dense urban obstacle environments

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月31日

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  • Renjian Zhou,
  • Li Quan,
  • Yu Lei

摘要

This paper addresses the challenge of designing final approach airspace for multi-rotor UAVs operating in complex urban environments. We propose a novel airspace framework based on a multi-branch strategy that integrates obstacle avoidance, UAV safe constraints, and traffic management. The model structures airspace into concentric annular layers with hovering points, accounting for urban obstacles through three geometric intersection states (non-intersection, long-side, broad-side). Key parameters—including layer radii, hovering point distribution, and altitude—are derived computationally using safety constraints, UAV maneuvering limits, and obstacle geometries. The approach process is governed by the branch blockade principle(inspired by railway section control) and a multilevel first-come-first-served (FCFS) strategy to ensure collision-free sequencing. Simulations of Tokyo Midtown scenarios validate the model’s efficacy, demonstrating how acceleration (0.5–3 m/s²) and speed limits (2–5 m/s) impact landing time and processing efficiency. Results show that higher acceleration and speed ceilings reduce average landing time under high-density traffic, while strategic parameter coordination unlocks critical efficiency thresholds. This work provides a scalable solution for urban vertiport operations.