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Two-Layer Optimization Algorithm for Multi-UAV Conflict Resolution considering Individual Fairness
Author(s) -
Xusheng Gan,
Honghong Zhang,
Yarong Wu,
Jingjuan Sun,
Guhao Zhao,
Fugen Lin
Publication year - 2021
Publication title -
international journal of aerospace engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.361
H-Index - 22
eISSN - 1687-5974
pISSN - 1687-5966
DOI - 10.1155/2021/9975538
Subject(s) - computer science , genetic algorithm , conflict resolution , complaint , reliability (semiconductor) , mathematical optimization , payment , algorithm , machine learning , mathematics , power (physics) , physics , quantum mechanics , world wide web , political science , law
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.

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