College of Information and Electrical Engineering, China Agricultural University, Beijing, China.
Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
PLoS One. 2021 Apr 14;16(4):e0249680. doi: 10.1371/journal.pone.0249680. eCollection 2021.
With an increasing number of unmanned aerial vehicles (UAVs), the difficulty of UAV management becomes more challenging, especially for low-altitude airspace due to complicated issues of security, privacy and flexibility. Existing management approaches to UAV flights include implementing registration of flight activity for supervision purposes, limiting the maximum flight height, setting different zones for different flight activities and prohibiting flights. In this research, we proposed a new air traffic management method for UAVs based on global subdivision theory. We designed four types of low-altitude air routes from grids, which correspond to grid sizes of 1.85 km, 128 m, 64 m and 32 m. Utilization of the subdivision grids transforms the complex spatial computation problem into a query process in the spatial database, which provides a new approach to UAV management in the fifth-generation (5G) era. We compared the number and data size of stored track records using longitude and latitude and different grid levels, computed time consumption for air route trafficability and simulated UAV flight to verify the feasibility of constructing this type of air traffic highway system. The amount of data storage and time consumption for air route trafficability can be substantially reduced by subdivision. For example, the data size using traditional expressions of latitude and longitude is approximately 1.5 times that of using a 21-level grid, and the time consumption by coordinates is approximately 1.5 times that of subdivision grids at level 21. The results of the simulated experiments indicate that in the 5G environment, gridded airspace can effectively improve the efficiency of UAV trajectory planning and reduce the size of information storage in the airspace environment. Therefore, given the increasing number of UAVs in the future, gridded highways have the potential to provide a foundation for various UAV applications.
随着无人机（UAV）数量的增加，UAV 管理的难度变得更加具有挑战性，尤其是对于低空空域而言，因为存在安全、隐私和灵活性等复杂问题。现有的 UAV 飞行管理方法包括实施飞行活动注册以进行监管、限制最大飞行高度、为不同的飞行活动设置不同的区域和禁止飞行。在本研究中，我们提出了一种基于全球细分理论的新的 UAV 空中交通管理方法。我们设计了四种从网格中生成的低空航线类型，分别对应 1.85 公里、128 米、64 米和 32 米的网格大小。细分网格的使用将复杂的空间计算问题转化为空间数据库中的查询过程，为 5G 时代的 UAV 管理提供了一种新方法。我们比较了使用经纬度和不同网格级别存储的轨迹记录的数量和数据大小，计算了航线可通行性的时间消耗，并模拟了 UAV 飞行，以验证构建这种类型的空中交通高速公路系统的可行性。通过细分，可以大大减少数据存储量和航线可通行性的时间消耗。例如，使用传统经纬度表达式的数据大小大约是使用 21 级网格的 1.5 倍，而坐标的时间消耗大约是 21 级细分网格的 1.5 倍。模拟实验的结果表明，在 5G 环境中，网格化空域可以有效地提高 UAV 轨迹规划的效率，并减少空域环境中信息存储的大小。因此，考虑到未来 UAV 的数量不断增加，网格化高速公路有可能为各种 UAV 应用提供基础。
