Flocks formation model for self-interested UAVs

Abstract

In recent years, unmanned aerial vehicles (UAVs) have been used in a wide range of domains. As the number of UAV flights increases, central flight areas may become overcrowded. This may cause delays in UAV traffic or gridlock on UAV routes. To address this challenge, we propose a flocking protocol that enables individual UAVs to optimize their flight preferences, while receiving the benefits of traveling in a group. Flocking can reduce overcrowding, and as a result, UAVs will be able to travel on less congested routes and have fewer encounters with other UAVs, thus reducing flight time and conserving energy. The protocol allows each UAV to create a flock or join an existing flock for all or part of its journey. We perform a simulation of UAV flights in an urban area and compare the average flight time of the UAVs based on various flight situations (e.g., different routes and participation in groups of UAVs). The simulation results demonstrate that the use of the flocking protocol significantly reduced the average flight time, and the flight saving rate increased with an increase in the UAV mean number. A similar effect is also observed in situations where each UAV and flock formed a dynamic A*-based path in advance to avoid collisions.