无人机低空飞行障碍物环境风险评估方法研究——以京津新城为例

无人机应用日益广泛,但随着城市环境建设的不断推进,无人机在城市中安全运行的问题也日益突出,因此无人机低空障碍物环境风险评估成为无人机领域研究的关键问题之一。论文按照不同类型无人机及运行高度将低空空域划分为微型、轻型和小型无人机风险评估区域,在充分考虑无人机自身形状大小、运动约束以及障碍物约束等条件的基础上,提出一种近似点扩张算法,基于障碍物原始边界生成扩张边界,并将其作为低空飞行环境中高风险与低风险之间的风险过渡区。以京津新城为例,分别提取不同风险评估区内的障碍物要素,并基于风险评估技术生成面向微型、轻型和小型无人机多高度层的低空飞行障碍物环境风险地图,按其对无人机威胁程度分为高风险区、高风险过渡区、中风险区和低风险区。实验结果表明:研究区内微型、轻型、小型无人机风险评估区内的风险过渡区分别占10.9%、7.3%、9.0%,该方法可以在考虑无人机与障碍物相互影响的基础上,计算飞行区域内无人机潜在碰撞风险区域,实现对低空障碍物环境风险的科学有效评估,为不同机型的无人机在飞行区域内的可航行性提供科学参考。

Environmental risk assessment of obstacles in low-altitude flight of unmanned aerial vehicle:Taking the Beijing-Tianjin New Town as an example

Unmanned aerial vehicle (UAV) is increasingly widely used, but with the continuous progress of urban development, the safe operation of UAV in cities is increasingly more prominent. Therefore, environmental risk assessment of obstacles has become one of the key issues in the field of low-altitude UAV research. In this study, taking the Beijing-Tianjin New Town as an example, the low-altitude airspace was divided into micro, light, and small UAV flight zones according to the low-altitude UAV types and operating heights. Based on the shape and size of UAVs, their motion constraints, and obstacle constraints, this research proposed an algorithm for approximation point expansion. The algorithm generates an expanded boundary on the basis of the original boundary of the obstacles, and this expanded boundary serves as a transitional zone between high risk and low risk areas in the low-altitude flight environment. Based on the UAV image data of 0.5 m resolution in the Beijing-Tianjin New Town in 2019, this study extracted obstacle elements in different assessment areas, and generated low-altitude flight obstacle environmental risk maps for different UAV types and different heights based on the risk assessment. The study area was divided into high-risk zone, high-risk transitional zone, medium-risk zone, and low-risk zone according to the threat posed to UAVs. The results show that: 1) The risk transitional zone in the micro, light, and small UAV control areas in the study area accounted for 10.9%, 7.3% and 9.0%, respectively, and the sharp-angle convex vertex optimization of the approximate point expansion algorithm can save about 1% of the airspace resources. 2) The proposed method can calculate the potential collision risk area of the UAVs in the flight area based on the mutual influence of the UAVs and the obstacles, and realize the effective assessment of the environmental risk of the low-altitude obstacles and provide a scientific reference for the navigability of the UAVs of different types in the flight area.