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军航飞机流穿越民航航线冲突探测与解脱问题

吴明功 蒋旭瑞 温祥西 陈彬

吴明功, 蒋旭瑞, 温祥西, 等 . 军航飞机流穿越民航航线冲突探测与解脱问题[J]. 北京航空航天大学学报, 2019, 45(5): 863-872. doi: 10.13700/j.bh.1001-5965.2018.0504
引用本文: 吴明功, 蒋旭瑞, 温祥西, 等 . 军航飞机流穿越民航航线冲突探测与解脱问题[J]. 北京航空航天大学学报, 2019, 45(5): 863-872. doi: 10.13700/j.bh.1001-5965.2018.0504
WU Minggong, JIANG Xurui, WEN Xiangxi, et al. Conflict detection and resolution in scenario of military aircraft flow passing through civil aviation route[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(5): 863-872. doi: 10.13700/j.bh.1001-5965.2018.0504(in Chinese)
Citation: WU Minggong, JIANG Xurui, WEN Xiangxi, et al. Conflict detection and resolution in scenario of military aircraft flow passing through civil aviation route[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(5): 863-872. doi: 10.13700/j.bh.1001-5965.2018.0504(in Chinese)

军航飞机流穿越民航航线冲突探测与解脱问题

doi: 10.13700/j.bh.1001-5965.2018.0504
基金项目: 

国家自然科学基金 71801221

国家自然科学基金 61472441

国家自然科学基金 61503409

陕西省自然科学基础研究计划 2018JQ7004

详细信息
    作者简介:

    吴明功 男, 硕士, 教授。主要研究方向:空中交通与管理、管制指挥与安全

    蒋旭瑞 男, 硕士研究生。主要研究方向:冲突探测与解脱

    温祥西 男, 博士, 讲师。主要研究方向:冲突探测与解脱技术

    陈彬 男, 博士研究生, 讲师。主要研究方向:军民航空管联合运行

    通讯作者:

    温祥西, E-mail:wxxajy@163.com

  • 中图分类号: V328

Conflict detection and resolution in scenario of military aircraft flow passing through civil aviation route

Funds: 

National Natural Science Foundation of China 71801221

National Natural Science Foundation of China 61472441

National Natural Science Foundation of China 61503409

Natural Science Basic Research Plan in Shaanxi Province of China 2018JQ7004

More Information
  • 摘要:

    针对军航飞机穿越民航航线的飞行冲突问题,对飞机流汇聚飞行场景进行建模分析,提出了基于滑动窗口的汇聚飞行冲突探测方法和基于合作博弈的多机冲突解脱方法。当飞机流进入预先划设的汇聚控制区,通过滑动窗口判断向前看时间内飞行冲突。基于此,潜在冲突机间组成一个联盟,以解脱边界条件为安全约束,以合作博弈理论中联盟福利最优解均衡各机效益,在保证安全的前提下实现效益均衡。根据最优机动方向特点,利用免疫粒子群优化算法快速求解策略。仿真结果表明,该场景下提出的方法能有效解算出满足要求的解脱策略,并均衡军民航飞机解脱效益。

     

  • 图 1  保护区E模型

    Figure 1.  E model of safe separation zone

    图 2  冲突探测场景

    Figure 2.  Conflict detection scenario

    图 3  飞机流之间各机冲突关系

    Figure 3.  Conflict relationship within aircraft flows

    图 4  两机冲突位置关系

    Figure 4.  Position relationship between two conflicting aircraft

    图 5  两机冲突边界条件

    Figure 5.  Conflict boundary condition of two aircraft

    图 6  免疫机理示意图

    Figure 6.  Schematic of immune mechanism

    图 7  冲突探测与解脱方法设计

    Figure 7.  Conflict detection and resolution method design

    图 8  民航飞机流信息获取

    Figure 8.  Civil aircraft flow data acquisition

    图 9  初始状态

    Figure 9.  Initial state

    图 10  飞机流汇聚飞行解脱航迹

    Figure 10.  Resolution track of centering aircraft flow

    图 11  飞行状态快照

    Figure 11.  Flight status snapshot

    图 12  各飞机解脱支付代价

    Figure 12.  Resolution pay-off of each aircraft

    图 13  免疫粒子群优化算法适应度值随收敛代数的变化

    Figure 13.  Fitness value of immune particle swarm optimization algorithm changes withconvergence algebra

    图 14  粒子群优化算法适应度值随收敛代数的变化

    Figure 14.  Fitness value of particle swarm optimization algorithm changes with convergence algebra

    表  1  码表

    Table  1.   Code table

    Δθ/(°)Δv
    -30%-20%-10%010%20%30%
    -2011121314151617
    -1521222324252627
    -1031323334353637
    -541424344454647
    051525354555657
    561626364656667
    1071727374757677
    1581828384858687
    2091929394959697
    下载: 导出CSV

    表  2  最优策略组合

    Table  2.   Optimal strategy combination

    飞机联盟策略支付代价适应度值
    A1Ua10° & 30%54.665 00.014 1
    A2Ua-5° & -10%20.512 4
    B1Ua0° & 0%0
    B2Ua0° & 0%0
    A3Ub-10° & -10%39.488 40.025 3
    B3Ub0° & 0%0
    A4Uc0° & 20%37.215 00.043 1
    A5Uc-5° & 0%6.304 8
    B4Uc0° & 0%0
    A6Ud10° & 20%69.171 80.007 1
    A7Ud-5° & -10%33.579 0
    B5Ud0° & 0%0
    B6Ud0° & 0%0
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-08-30
  • 录用日期:  2018-11-30
  • 刊出日期:  2019-05-20

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