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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Bibliographic Details
Published in:Drones (Basel) Vol. 9; no. 5; p. 320
Main Authors: Feng, Ouge, Zhang, Honghai, Tang, Weibin, Wang, Fei, Feng, Dikun, Zhong, Gang
Format: Journal Article
Language:English
Published: Basel MDPI AG 22.04.2025
Subjects:
Aircraft accidents & safety
Airspace
Airspace (Law)
airspace operational capacity
Algorithms
Altitude
Aviation
Collisions
Control systems
Drone aircraft
Efficiency
Environmental aspects
Flight altitude
Geospatial data
grid
Integer programming
Logistics
Low altitude
Midair collisions
Optimization
Parallelograms
Path planning
Phase transitions
Planning
Population density
Quantitative analysis
Resource allocation
Risk assessment
Simulation
Simulation models
Sustainable development
Third party
unmanned aerial vehicle
Unmanned aerial vehicles
Urban environments
China
ISSN:2504-446X, 2504-446X
Online Access:Get full text
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Summary: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.
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ISSN:2504-446X
2504-446X
DOI:10.3390/drones9050320