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基于点融合系统的多目标进场排序与调度

张军峰 游录宝 周铭 杨春苇 康博

张军峰,游录宝,周铭,等. 基于点融合系统的多目标进场排序与调度[J]. 北京航空航天大学学报,2023,49(1):66-73 doi: 10.13700/j.bh.1001-5965.2021.0199
引用本文: 张军峰,游录宝,周铭,等. 基于点融合系统的多目标进场排序与调度[J]. 北京航空航天大学学报,2023,49(1):66-73 doi: 10.13700/j.bh.1001-5965.2021.0199
ZHANG J F,YOU L B,ZHOU M,et al. Multi-objective arrival sequencing and scheduling based on point merge system[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(1):66-73 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0199
Citation: ZHANG J F,YOU L B,ZHOU M,et al. Multi-objective arrival sequencing and scheduling based on point merge system[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(1):66-73 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0199

基于点融合系统的多目标进场排序与调度

doi: 10.13700/j.bh.1001-5965.2021.0199
基金项目: 国家自然科学基金(U1933117)
详细信息
    通讯作者:

    E-mail:zhangjunfeng@nuaa.edu.cn

  • 中图分类号: V335

Multi-objective arrival sequencing and scheduling based on point merge system

Funds: National Natural Science Foundation of China (U1933117)
More Information
  • 摘要:

    持续增长的交通需求和日趋饱和的空域资源对飞行安全和管制效率要求更高,鉴于此,研究基于点融合系统(PMS)的多目标进场排序与调度问题。分析四维航迹预测模型与方法,实现四维航迹预测功能。针对PMS的运行模式和多个利益相关方的需求,构建PMS多目标排序与调度模型,提出基于多目标帝国竞争算法(ICA)。利用长沙黄花国际机场实际运行数据与蒙特卡罗模拟数据对优化模型与算法进行验证。结果表明:所提算法有良好的实际应用效果,能为管制员提供决策支持;在应用基于PMS的多目标进场排序与调度,即使在相对保守的安全间隔下,相对于实际运行优化后的总延误时间、总飞行时间、最大飞行时间分别有70.8%、13.2%、11.8%的缩减。

     

  • 图 1  PMS结构示意图

    Figure 1.  Schematic diagram of PMS

    图 2  航迹预测与排序调度的关系

    Figure 2.  Relation between trajectory prediction and arrival sequencing

    图 3  多目标帝国竞争算法流程

    Figure 3.  Flowchart of multi-objective ICA

    图 4  预测轨迹与实际三维轨迹对比

    Figure 4.  Comparison between three dimensional predicted and actual trajectory

    图 5  预测轨迹与实际轨迹过点时间对比

    Figure 5.  Comparison of flight time at each fix between predicted and actual trajectory

    图 6  目标随序列改变趋势

    Figure 6.  Trend of objectives with different sequences

    图 7  长沙终端航班进场轨迹

    Figure 7.  Arrival trajectories within Changsha terminal area

    图 8  系统仿真界面示意图

    Figure 8.  Interface of simulation system

    图 9  PMS与实际数据时序对比

    Figure 9.  Comparison of scheduling results between PMS and actual operation

    图 10  PMS仿真轨迹与实际轨迹对比

    Figure 10.  Comparison of trajectories between PMS simulation and actual operation

    表  1  排序目标汇总

    Table  1.   Multi-objective arrival sequencing and scheduling

    关注点 目标关注方
    跑道容量最大化最小化最大着陆时间机场
    对航空公司的公平调度最小化最大飞行时间航司
    管制工作负荷;运行效益最小化总飞行时间管制;航司
    空管效率;准点出行最小化延误时间和管制;民众
    对航空器的公平调度最小化最大延误时间航司;民众
    下载: 导出CSV

    表  2  基于实际进场数据的飞行计划(部分)

    Table  2.   Flight plan based on actual operation (part)

    序号机型进港时间/s路径序号机型进港时间/s路径
    1B73783873DPR_36R11A32084614DPR_36R
    2A32084521LIG_36R12A32084784DPR_36R
    3A32084418LLC_36R13A32185278DPR_36R
    4A32184731LIG_36R14B73885588BEM_36R
    5A32184304OVT_36R15A32085456OVT_36R
    6B73884310DPR_36R16A32185512DPR_36R
    7A32184631BEM_36R17A31986105BEM_36R
    8A32084525OVT_36R18A32186008OVT_36R
    9B73885080LIG_36R19B73886211LLC_36R
    10A32084867LLC_36R20B73886397LLC_36R
    下载: 导出CSV

    表  3  仿真结果

    Table  3.   Simulation results

    尾流间隔总延误时间/s总飞行时间/s最大飞行时间/s
    实际7628282951936
    1.2倍间隔2224245591707
    1.5倍间隔5838281861921
    下载: 导出CSV

    表  4  仿真案例航空器在排序支路飞行时间

    Table  4.   Aircraft flight time on sequencing leg of simulation case

    航班支路飞行时间/s 航班支路飞行时间/s
    10 11275
    2012225
    3481362
    41641433
    51971514
    62431628
    72331739
    8160180
    92341934
    10230200
    下载: 导出CSV
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  • 被引次数: 0
出版历程
  • 收稿日期:  2021-04-19
  • 录用日期:  2021-07-04
  • 网络出版日期:  2023-01-16
  • 刊出日期:  2021-07-26

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