Collision Detection for UAVs Based on GeoSOT-3D Grids

Abstract

The increasing number of unmanned aerial vehicles (UAVs) has led to challenges related to solving the collision problem to ensure air traffic safety. The traditional approaches employed for collision detection suffer from two main drawbacks: first, the computational burden of a pairwise calculation increases exponentially with an increasing number of spatial entities; second, existing grid-based approaches are unsuitable for complicated scenarios with a large number of objects moving at high speeds. In the proposed model, we first identified UAVs and other spatial objects with GeoSOT-3D grids. Second, the nonrelational spatial database was initialized with a multitable strategy, and spatiotemporal data were inserted with the GeoSOT-3D grid codes as the primary key. Third, the collision detection procedure was transformed from a pairwise calculation to a multilevel query. Four simulation experiments were conducted to verify the feasibility and efficiency of the proposed collision detection model for UAVs in different environments. The results also indicated that 64 m GeoSOT-3D grids are the most suitable basic grid size, and the reduction in the time consumption compared with traditional methods reached approximately 50–80% in different scenarios.

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

“…Recent studies on DGGSs have proven their advantages in UAV applications [ 34 , 35 ]. Gridding, as a promising and important technology, was incorporated into the standardization roadmap for unmanned aircraft systems by the American National Standards Institute (ANSI) Unmanned Aircraft Systems Standardization Collaborative (UASSC) in June 2020.…”

Algorithms for Smooth, Safe and Quick Routing on Sensor-Equipped Grid Networks

“…A first group of papers presents static approaches, where, for each vehicle, nominal routes are computed on the underlying routing network, taking load-balance factors into account, to prevent collisions as far as possible [8,9], or, if the application context allows, by dividing the routing area into non-intersecting zones, each occupied by one vehicle at a time, as in regional control models [9][10][11][12]. In general, such approaches cannot guarantee collision-free nominal routes, and additional methods are required during their execution to detect and resolve collisions and, in case, deadlocks, based on, e.g., Petri Net approaches [13,14], graph-theoretic models [15], queries on geospatial reference grid systems [16] and searching the space of possible deviations from nominal routes [17]. A specialized static approach for grid networks is presented in [18], where initial routes that minimize collisions are chosen from equivalent Manhattan paths, and selected collision avoidance rules, based on preliminary collisions classification, are applied during execution.…”

General Method for Extending Discrete Global Grid Systems to Three Dimensions

“…It also makes data querying less efficient, as data at all altitudes associated with a cell must be searched to find those that correspond with the desired altitude(s). With the large amounts of 3D geospatial data being generated, such as 3D point clouds from LIDAR [33] and aircraft flight paths [34,35], there is emerging an increasing need for 3D global grids and grid systems [12].…”

“…Due to the simplicity of its construction, it has seen use in global crust modelling [36] and exploring P-wave velocity [37] among other applications. The GeoSOT3D grid is a variation of the standard 3D LLG where latitude and longitude have been extended to larger virtual spaces to improve the efficiency of grid encoding and decoding [15] and has been used to increase the efficiency of aircraft collision detection [34,35]. Despite the simplicity of a 3D LLG, due to the nature of spherical coordinates, cells at the poles and centre of the grid degenerate and are much smaller than other cells.…”

“…The first use case we examine is tracking the trajectories of aircraft and spacecraft, such as commercial and private flights, drones, satellites, and rockets. Such a system could be used to increase the efficiency of collision queries using the hierarchy of the grid system, similar to the approaches of [34,35]. The main benefit our 3D DGGS would offer over existing grids for such a system is the ability to have cells located at low and high altitudes in the same resolution have close to equal shape and size.…”