北京航空航天大学学报 ›› 2022, Vol. 48 ›› Issue (5): 863-871.doi: 10.13700/j.bh.1001-5965.2020.0670

• 论文 • 上一篇    下一篇

基于合作博弈的多机冲突解脱算法

张宏宏1,2,3, 甘旭升1,3, 辛建霖1, 刘一群4, 陈旭祎1   

  1. 1. 空军工程大学 空管领航学院, 西安 710051;
    2. 中国人民解放军 31664部队, 格尔木 816000;
    3. 国家空管防相撞技术重点实验室, 西安 710051;
    4. 中国人民解放军 94608部队, 南京 211500
  • 收稿日期:2020-12-01 发布日期:2022-05-30
  • 通讯作者: 甘旭升 E-mail:gxsh15934896556@qq.com
  • 基金资助:
    国家自然科学基金(61601497);空军工程大学校长基金(XZJ2020005)

Multi-aircraft conflict resolution algorithm based on cooperative game

ZHANG Honghong1,2,3, GAN Xusheng1,3, XIN Jianlin1, LIU Yiqun4, CHEN Xuyi1   

  1. 1. Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an 710051, China;
    2. Unit 31664 of the People’s Liberation Army, Golmud 816000, China;
    3. National Key Laboratory of Air Traffic Collision Prevention, Xi’an 710051, China;
    4. Unit 94608 of the People’s Liberation Army, Nanjing 211500, China
  • Received:2020-12-01 Published:2022-05-30
  • Supported by:
    National Natural Science Foundation of China (61601497);President’s Foundation of Air Force Engineering University (XZJ2020005)

摘要: 为解决低空无人机冲突解脱过程中个体支付成本不公平问题,提出了基于合作博弈“核仁解”概念的多机冲突解脱算法。针对低空多机冲突场景的特点,基于“核仁解”概念,建立无人机冲突解脱支付矩阵。结合人工势场法与蚁群算法的优点,提出基于人工势场法-蚁群算法(APF-ACO)的冲突解脱混合求解策略。仿真结果表明:综合计算时间、可行性与系统效率3个评价指标,APF-ACO混合求解策略效能最优;基于合作博弈“核仁解”的求解策略在一定程度上可提升个体公平性;同时能够在牺牲少量整体利益的前提下,拥有优先级无人机的快速规划达到目标。

关键词: 无人机, 冲突解脱, 合作博弈, 人工势场法(APF), 蚁群算法(ACO)

Abstract: In order to solve the problem of inequity of individual cost in conflict resolution of low-altitude UAV, a multi-aircraft conflict resolution algorithm based on the concept of “nucleolus solution” in cooperative game is proposed. According to the characteristics of low-altitude multi-aircraft conflict scenarios, based on the “nucleolus solution” concept, the UAV conflict resolution payment matrix is established. Combined with the advantages of artificial potential field method and ant colony optimization, a hybrid conflict resolution strategy based on artificial potential field-ant colony optimization (APF-ACO) is proposed. The simulation results show that the APF-ACO hybrid solution strategy has the best performance by integrating the three evaluation indexes of calculation time, feasibility and system efficiency. The solution strategy based on cooperative game “nucleolus solution” can improve individual fairness to a certain extent. At the same time, the priority UAV can be quickly planned to achieve the goal at the expense of a small amount of overall benefits.

Key words: UAV, conflict resolution, cooperative game, artificial potential field (APF), ant colony optimization (ACO)

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