Two-Layer Optimization Algorithm for Multi-UAV Conflict Resolution considering Individual Fairness

• Published in: International journal of aerospace engineering 2021-10, Vol.2021, p.1-21
• Main Authors: Gan, Xusheng, Zhang, Honghong, Wu, Yarong, Sun, Jingjuan, Zhao, Guhao, Lin, Fugen
• Format: Article
• Language: English
• Subjects: Aerospace engineering; Aircraft; Altitude; Aviation; Conflict resolution; Game theory; Genetic algorithms; Income distribution; Linear programming; Low altitude; Methods; Optimization; Optimization algorithms; Potential fields; Public safety; Reliability analysis; Strategy; Unmanned aerial vehicles
• ISSN: 1687-5966; 1687-5974
• DOI: 10.1155/2021/9975538

In order to solve the unfair individual payment costs problem in the low-altitude unmanned aerial vehicle (UAV) conflict resolution process, a multi-UAV conflict resolution algorithm based on the cooperative game concept “coalition complaint value” is proposed. Firstly, based on the low-altitude multi-UAV conflict scene characteristics, according to the “coalition complaint value” concept, the UAV conflict resolution payment matrix is established. Secondly, combined with the advantages of the artificial potential field (APF) method and the genetic algorithm (GA), a hybrid solution strategy for conflict resolution based on APF-GA is proposed. The final simulation results show that the APF-GA hybrid solution strategy has the best efficiency by combining the three evaluation indicators of calculation time, feasibility, and system efficiency. The reliability of the proposed algorithm is verified based on the Monte Carlo algorithm. The solution strategy based on the cooperative game “coalition complaint value” can improve individual fairness to a certain extent. At the same time, it can achieve the rapid planning goal with priority drones at the expense of a small amount of overall benefits.