面向航空器集群的多尺度保护区模型与改进速度障碍法OA北大核心CSTPCD

The thesis explores aircraft swarming in dense airspace.A multi-scale protected zone model,coupled with an improved velocity obstacle method,is proposed to solve this.Traditional approaches often rely on a sin-gle-aircraft protected zone model,which utilizes a velocity obstacle method characterized by complex calculations and suboptimal real-time performance.In contrast,a more advanced approach is introduced,featuring a dynamic el-lipsoidal protected zone model and a fusion protected zone model specifically designed for aircraft swarms.These models are crafted to accurately depict the aircraft's flight state and safety intervals.Moreover,the work pioneers the geometric transformation from a single-aircraft protected zone to a swarm-based protected zone.The innovative aircraft swarm protected zone model reduces the dimensional complexity while integrating critical features such as swarm safety intervals and motion characteristics.The paper further develops an improved velocity obstacle method that is grounded on the multi-scale protected zone model.This refined method incorporates a velocity obstacle boundary specifically tailored for aircraft swarms,effectively reducing the computational demands of the algorithm.The proposed models and algorithms successfully portray multiple aircraft as swarms.By establishing boundaries for real-time adjustments in speed and direction specifically for aircraft swarms,they significantly reduce computa-tional complexity.This effectively implements conflict detection and resolution trajectories for aircraft swarms.A comparison of the proposed method with conventional approaches shows a significant improvement in the conflict determination mechanism for aircraft clusters,reducing algorithm computation time by 33%.Additionally,the pro-posed method leads to a decrease in adjustment amplitude by 60.45%,enhancing its overall performance.The meth-od effectively enhances the efficiency of aircraft conflict detection and resolution under swarming phenomena.