为解决局部空域内的无人机（UAV）群相撞和可能发生连锁碰撞问题，创新地以复杂网络理论为基础，将无人机群的飞行冲突解脱分为关键节点选择和避撞方向选择2个步骤实施，最大限度地保证无人机群受威胁时的安全性。通过分析无人机群的状态信息，选择最重要无人机（关键节点）进行避撞，同时遵循鲁棒性最小原则进行避撞方向选择。通过2个典型无人机飞行案例的仿真实验，验证该策略不仅可以有效解决当前无人机的冲突问题，而且可以防止连锁碰撞，实现整体的最优化。大量仿真实验验证了所提算法的可行性和可扩展性，以及与随机选择方向避撞算法进行比较，结果表明该算法能够提升无人机群的安全性。
In order to solve the problem of collision of Unmanned Aerial Vehicles (UAV) in a local airspace and the possibility of chain collision, innovatively based on the theory of complex networks, the key node selection and the sense selection are applied, maximizing the security of the threat to the UAV group. By analyzing the status information of the UAV group, the most important UAV (key nodes) is selected to avoid collisions, and at the same time, the robustness minimum principle is adopted to select the collision avoidance direction. Simulation results of the two typical UAV flight cases show that this strategy can not only effectively solve the current conflict problem of UAVs, but also prevent chain collisions and achieve overall optimization. Quantitative simulation experiments are conducted to validate the feasibility and scalability of the proposed algorithm. Compared with the random choose direction collision algorithm, the results show that this algorithm can indeed improve the safety of the UAV group.
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