Three-Dimension Collision-Free Trajectory Planning of UAVs Based on ADS-B Information in Low-Altitude Urban Airspace

The environment of low-altitude urban airspace is complex and variable due tonumerous obstacles, non-cooperative aircrafts, and birds. Unmanned aerialvehicles (UAVs) leveraging environmental information to achieve three-dimensioncollision-free trajectory planning is the prerequisite to ensure airspacesecurity. However, the timely information of surrounding situation is difficultto acquire by UAVs, which further brings security risks. As a mature technologyleveraged in traditional civil aviation, the automatic dependentsurveillance-broadcast (ADS-B) realizes continuous surveillance of theinformation of aircrafts. Consequently, we leverage ADS-B for surveillance andinformation broadcasting, and divide the aerial airspace into multiplesub-airspaces to improve flight safety in UAV trajectory planning. In detail,we propose the secure sub-airspaces planning (SSP) algorithm and particle swarmoptimization rapidly-exploring random trees (PSO-RRT) algorithm for the UAVtrajectory planning in law-altitude airspace. The performance of the proposedalgorithm is verified by simulations and the results show that SSP reduces boththe maximum number of UAVs in the sub-airspace and the length of thetrajectory, and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.