Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments
This paper proposes a digital low-altitude airspace unmanned aerial vehicle (UAV) path planning method tailored for urban risk environments and conducts an operational capacity assessment of the airspace. The study employs a vertical–horizontal grid partitioning technique to achieve airspace grid-ba...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/5/320 |
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| author | Ouge Feng Honghai Zhang Weibin Tang Fei Wang Dikun Feng Gang Zhong |
| author_facet | Ouge Feng Honghai Zhang Weibin Tang Fei Wang Dikun Feng Gang Zhong |
| author_sort | Ouge Feng |
| collection | DOAJ |
| description | This paper proposes a digital low-altitude airspace unmanned aerial vehicle (UAV) path planning method tailored for urban risk environments and conducts an operational capacity assessment of the airspace. The study employs a vertical–horizontal grid partitioning technique to achieve airspace grid-based modeling, classifying and configuring “management-operation” grids. By integrating multi-source heterogeneous data, including building structures, population density, and sheltering factor, a grid-based discrete risk quantification model is established to evaluate comprehensive mid-air collision risk, ground impact risk, third-party risk, and UAV turning risk. A path planning method considering the optimization of the turning points of parallelograms was proposed, and the Parallel-A* algorithm was adopted for its solution. Finally, an airspace operational capacity assessment model and a conflict simulation model for urban risk environments are developed to quantify the operational capacity of urban low-altitude airspace. Using Liuhe District in Nanjing as the experimental area, the study reveals that the environmental airspace risk decreases significantly with increasing flight altitude and eventually stabilizes. In the implementation of path planning, compared with the A* and Weight-A* algorithms, the Parallel-A* algorithm demonstrates clear advantages in terms of lower average comprehensive risk and fewer turning points. In the operational capacity assessment experiments, the airspace capacity across different altitude layers increases with flight altitude and stabilizes after comprehensive risk is reduced. This research provides a theoretical foundation for the scientific management and optimal resource allocation of urban low-altitude airspace, facilitating the safe application and sustainable development of UAVs in urban environments. |
| format | Article |
| id | doaj-art-1b0aa619b74645f8aa059022f3167b25 |
| institution | OA Journals |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-1b0aa619b74645f8aa059022f3167b252025-08-20T02:33:48ZengMDPI AGDrones2504-446X2025-04-019532010.3390/drones9050320Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk EnvironmentsOuge Feng0Honghai Zhang1Weibin Tang2Fei Wang3Dikun Feng4Gang Zhong5College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaThis paper proposes a digital low-altitude airspace unmanned aerial vehicle (UAV) path planning method tailored for urban risk environments and conducts an operational capacity assessment of the airspace. The study employs a vertical–horizontal grid partitioning technique to achieve airspace grid-based modeling, classifying and configuring “management-operation” grids. By integrating multi-source heterogeneous data, including building structures, population density, and sheltering factor, a grid-based discrete risk quantification model is established to evaluate comprehensive mid-air collision risk, ground impact risk, third-party risk, and UAV turning risk. A path planning method considering the optimization of the turning points of parallelograms was proposed, and the Parallel-A* algorithm was adopted for its solution. Finally, an airspace operational capacity assessment model and a conflict simulation model for urban risk environments are developed to quantify the operational capacity of urban low-altitude airspace. Using Liuhe District in Nanjing as the experimental area, the study reveals that the environmental airspace risk decreases significantly with increasing flight altitude and eventually stabilizes. In the implementation of path planning, compared with the A* and Weight-A* algorithms, the Parallel-A* algorithm demonstrates clear advantages in terms of lower average comprehensive risk and fewer turning points. In the operational capacity assessment experiments, the airspace capacity across different altitude layers increases with flight altitude and stabilizes after comprehensive risk is reduced. This research provides a theoretical foundation for the scientific management and optimal resource allocation of urban low-altitude airspace, facilitating the safe application and sustainable development of UAVs in urban environments.https://www.mdpi.com/2504-446X/9/5/320unmanned aerial vehiclerisk assessmentgridpath planningairspace operational capacity |
| spellingShingle | Ouge Feng Honghai Zhang Weibin Tang Fei Wang Dikun Feng Gang Zhong Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments Drones unmanned aerial vehicle risk assessment grid path planning airspace operational capacity |
| title | Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments |
| title_full | Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments |
| title_fullStr | Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments |
| title_full_unstemmed | Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments |
| title_short | Digital Low-Altitude Airspace Unmanned Aerial Vehicle Path Planning and Operational Capacity Assessment in Urban Risk Environments |
| title_sort | digital low altitude airspace unmanned aerial vehicle path planning and operational capacity assessment in urban risk environments |
| topic | unmanned aerial vehicle risk assessment grid path planning airspace operational capacity |
| url | https://www.mdpi.com/2504-446X/9/5/320 |
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