利用蜂群无人机网络优化城市空中交通冲突管理
Optimized Conflict Management for Urban Air Mobility Using Swarm UAV Networks
该研究提出了一种基于边缘人工智能的分布式蜂群架构，用于优化城市空中交通中的冲突管理，显著提升了冲突解决效率和准确性。此方案对推动eVTOL行业在高密度城市环境下的安全运行具有参考价值，可支持未来空中交通管理系统的智能化发展。
Urban Air Mobility (UAM) poses unprecedented traffic coordination challenges, especially with increasing UAV densities in dense urban corridors. This paper introduces a mathematical model using a control algorithm to optimize an Edge AI-driven decentralized swarm architecture for intelligent conflict resolution, enabling real-time decision-making with low latency. Using lightweight neural networks, the system leverages edge nodes to perform distributed conflict detection and resolution. A simulation platform was developed to evaluate the scheme under various UAV densities. Results indicate that the conflict resolution time is dramatically minimized up to 3.8 times faster, and accuracy is enhanced compared to traditional centralized control models. The proposed architecture is highly promising for scalable, efficient, and safe aerial traffic management in future UAM systems.
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来源：arXiv先进空中交通研究 · arxiv.org