MAJul 6

Dynamic Airspace Management for UAVs in Evolving Urban Environments: Collaborative Coordination and Human Safety

arXiv:2607.048254.9Has Code
Predicted impact top 84% in MA · last 90 daysOriginality Incremental advance
AI Analysis

Addresses UAV safety and human fear in low-altitude urban airspace for operators and residents.

Pharos, a collaborative multi-UAV airspace management system, reduces human fear by 52.72% and improves spatial entropy by 70.82% over Ipopt and 2.03% over A-star in urban environments.

The low-altitude economy is an emerging industry with significant development potential, in which the safety of unmanned aerial vehicle (UAV) operations is a critical challenge. Particularly within complex urban topographies and human-populated environments, UAV airspace management must prioritize collision avoidance and human safety. We propose Pharos, a collaborative multi-UAV airspace management system. Pharos lies between the distributed local perception paradigm and the centralized fine-grained control paradigm. Pharos coordinates the safe parallel execution of UAVs in shared airspace while innovatively accounting for the impact of human fear. Pharos is implemented using the MAPPO algorithm due to its faster convergence and higher rewards than other typical MARL algorithms (HAPPO and HATRPO). To evaluate Pharos, we developed a 3D simulation system using real urban data. Visualization results demonstrate its effective airspace coordination capability. Regarding performance verification, Pharos reduced human fear by 52.72% compared to the benchmark Ipopt. Moreover, we designed spatial entropy as a system evaluation metric to quantify space utilization, which improved performance by 70.82% and 2.03% compared to the benchmarks Ipopt and A-star, respectively. The source code is available at an anonymized repository: https://github.com/pharos-anonymized/source-code.git.

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