A low-altitude public air route network for UAV management constructed by global subdivision grids

Abstract

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.

Urban Traffic Monitoring and Analysis Using Unmanned Aerial Vehicles (UAVs): A Systematic Literature Review

“…The low-altitude traffic management should also be taken into account when developing systems for monitoring traffic in urban areas since the flight environment in these areas is increasingly complex with the development of UAVs. Progress has been made in this regard as well through the development of public air route networks for UAVs [107] based on aerial corridor systems [108] or airspace geofencing volumization algorithms to support unmanned aircraft management of low-altitude airspace [109]. Another solution is represented by a multilayer network of nodes and airways [110].…”

“…The main regulations are related to the controlled use of airspace, operational limitations, and administrative procedures [10]. There are three categories of the management of low-altitude UAVs: the registration of flight activity, the limitation of maximum flight height for different types of UAVs, setting the area for different flight activities [107]. As an example, the Federal Aviation Administration of USA mention that the maximum allowable altitude is 400 ft (about 122 m) above the ground [116].…”

Multi-Objective Design of UAS Air Route Network Based on a Hierarchical Location–Allocation Model

“…For instance, some major routes are popular pathways that UASs could have shared, but these resources are not fully utilized due to separate individual decisions. Hence, network-based UAS routing has recently been researched in the literature for its advantage in traffic demand consolidation and dissemination [15][16][17].…”

Possibilities of Using UAVs in Pre-Hospital Security for Medical Emergencies

“…In particular, a drone can provide detection rates of nearly 100%. Increased detection speed over large areas, and high detection rates in different types of terrain—thanks to computer vision techniques [ 57 , 58 , 59 ]. To save lives during emergencies, it is also possible to detect the human body using UAV camera image processing.…”