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基于飞行冲突网络最优支配集的冲突调配策略

吴明功 毕可心 温祥西 孙继昆

吴明功,毕可心,温祥西,等. 基于飞行冲突网络最优支配集的冲突调配策略[J]. 北京航空航天大学学报,2023,49(2):242-253 doi: 10.13700/j.bh.1001-5965.2021.0233
引用本文: 吴明功,毕可心,温祥西,等. 基于飞行冲突网络最优支配集的冲突调配策略[J]. 北京航空航天大学学报,2023,49(2):242-253 doi: 10.13700/j.bh.1001-5965.2021.0233
WU M G,BI K X,WEN X X,et al. Conflict resolution strategy based on optimal dominating set of flight conflict networks[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(2):242-253 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0233
Citation: WU M G,BI K X,WEN X X,et al. Conflict resolution strategy based on optimal dominating set of flight conflict networks[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(2):242-253 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0233

基于飞行冲突网络最优支配集的冲突调配策略

doi: 10.13700/j.bh.1001-5965.2021.0233
基金项目: 国家自然科学基金(71801221); 国家社会科学基金(19BGL297)
详细信息
    作者简介:

    毕可心,等:基于飞行冲突网络最优支配集的冲突调配策略 11

    通讯作者:

    E-mail:wxxajy@163.com

  • 中图分类号: V355;O231.5

Conflict resolution strategy based on optimal dominating set of flight conflict networks

Funds: National Natural Science Foundation of China (71801221); National Social Science Fund of China (19BGL297)
More Information
  • 摘要:

    针对空中交通流量逐年上升、管制压力增大、飞行冲突难调配的问题,以航空器为节点,基于航空器之间的速度障碍关系建立飞行冲突网络。定义最优支配集的概念,通过移除飞行冲突网络的最优支配集节点,快速消解网络中的冲突,降低网络的复杂性。在使用粒子群(PSO)算法对网络最优支配集进行求解的过程中,引入免疫机制,设置节点和连边2种类型的抗原,保证对关键航空器和高风险冲突的优先调配。实验仿真表明:所提冲突调配策略相较于传统方法能够快速识别网络中的关键航空器节点,并对高风险的冲突连边具有较好的灵敏性,可为管制员和管制系统提供更加准确、可靠的信息和建议,在宏观上辅助进行飞行冲突的调配。

     

  • 图 1  位置探测区

    Figure 1.  Position detection area

    图 2  椭球形飞行保护区

    Figure 2.  Ellipsoidal flight protection zone

    图 3  速度障碍法

    Figure 3.  Velocity obstacle method

    图 4  三维速度障碍模型

    Figure 4.  3D velocity obstacle model

    图 5  飞行冲突网络示意图

    Figure 5.  Schematic of flight collision network

    图 6  最小支配集示意图

    Figure 6.  Schematic of minimum dominant set

    图 7  最优支配集

    Figure 7.  Optimal domination set

    图 8  过滤孤立节点

    Figure 8.  Filtration of isolated nodes

    图 9  冲突调配步骤

    Figure 9.  Conflict resolution process

    图 10  昆明长水国际机场空域雷达图像

    Figure 10.  Airspace radar image of Kunming Changshui International Airport

    图 11  网络对比

    Figure 11.  Network comparison

    图 12  两种网络节点度值的比较

    Figure 12.  Node degree comparison of two networks

    图 13  两种算法的对比

    Figure 13.  Comparison of two algorithms

    图 14  从网络中移除最优支配集

    Figure 14.  Removal of ODS from network

    图 15  ODS移除顺序对网络性能下降速度的影响

    Figure 15.  Effect of ODS removal order on network performance degradation rate

    图 16  不同删除方法对网络性能的影响

    Figure 16.  Impact of different deletion methods on network performance

    表  1  两种网络中节点的度值

    Table  1.   Node degrees in two networks

    序号节点度值序号节点度值
    飞行状态网络飞行冲突网络飞行状态网络飞行冲突网络
    184 2172
    262 2252
    341 23132
    470 2442
    522 25104
    632 2662
    750 2771
    841 2893
    990 29104
    1022 3051
    1162 3162
    1273 3264
    13125 3373
    1441 3474
    1550 3574
    1662 3664
    1740 3791
    1851 3874
    1962 3992
    2050 4085
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-05-07
  • 录用日期:  2021-06-11
  • 网络出版日期:  2021-07-14
  • 整期出版日期:  2023-02-28

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