Three-Dimension Collision-Free Trajectory Planning of UAVs Based on ADS-B Information in Low-Altitude Urban Airspace
<|reference_start|>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 to numerous obstacles, non-cooperative aircrafts, and birds. Unmanned aerial vehicles (UAVs) leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security. However, the timely information of surrounding situation is difficult to acquire by UAVs, which further brings security risks. As a mature technology leveraged in traditional civil aviation, the automatic dependent surveillance-broadcast (ADS-B) realizes continuous surveillance of the information of aircrafts. Consequently, we leverage ADS-B for surveillance and information broadcasting, and divide the aerial airspace into multiple sub-airspaces to improve flight safety in UAV trajectory planning. In detail, we propose the secure sub-airspaces planning (SSP) algorithm and particle swarm optimization rapidly-exploring random trees (PSO-RRT) algorithm for the UAV trajectory planning in law-altitude airspace. The performance of the proposed algorithm is verified by simulations and the results show that SSP reduces both the maximum number of UAVs in the sub-airspace and the length of the trajectory, and PSO-RRT reduces the cost of UAV trajectory in the sub-airspace.<|reference_end|>
@article{dong2024three-dimension,
    title={Three-Dimension Collision-Free Trajectory Planning of UAVs Based on
  ADS-B Information in Low-Altitude Urban Airspace},
    author={Chao Dong, Yifan Zhang, Ziye Jia, Yiyang Liao, Lei Zhang, and Qihui Wu},
    journal={arXiv preprint arXiv:2404.18436},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.18436},
    primaryClass={eess.SY cs.SY}
}