Quantification of UAV Flight Safety Margins in Urban Low-Altitude Environments
In complex urban low-altitude (ULA) airspace, unmanned aerial vehicles (UAVs) face several safety challenges, such as building obstacles, airspace restrictions, and environmental uncertainties. In this study, these issues are addressed by adopting a novel quantitative method for evaluating UAV flight safety margins and integrating this method into a ULA airspace grid model. This method comprehensively considers critical factors such as airspace obstacles, environmental conditions, and UAV performance to compute a quantitative safety margin. Once safety buffer grids around restricted and potential conflict grids are introduced, dynamic constraints can be imposed on the trajectory planning process. The proposed model not only achieves a balance between path cost and safety redundancy but also significantly enhances UAV flight safety and the efficiency of airspace resource utilization in complex urban environments. The experimental results validate the effectiveness of this approach for planning multi-UAV trajectories, demonstrating its feasibility and potential for broader application. This research not only extends the safety implications of low-altitude airspace grid modeling but also provides a new technical pathway and theoretical foundation for future ULA airspace safety management, multi-UAV collaborative scheduling, and refined airspace governance.
Authors
- Chuli Hu (ORCID: https://orcid.org/0000-0003-1896-4812)
- Mu Duan (ORCID: https://orcid.org/0009-0009-9315-9304)
- Shen Chen (ORCID: https://orcid.org/0009-0006-0004-5139)
- Kaihua Jiang (ORCID: https://orcid.org/0000-0001-9570-6433)
- X. X. Ding (ORCID: https://orcid.org/0000-0002-2807-2597)
- Peng Wang (ORCID: https://orcid.org/0009-0002-7748-4843)
- Yifan Chen (ORCID: https://orcid.org/0000-0002-9054-3089)
- Haoshuang Cai (ORCID: https://orcid.org/0009-0000-2485-5503)
Institutions
- China University of Geosciences (CN)
- Wuchang University of Technology (CN)
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-12-08
- DOI
- https://doi.org/10.3390/app152412942
- Primary Topic
- Air Traffic Management and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00