中国民航大学学报

• 民用航空 •    下一篇

离港飞机滑行路径优化与仿真

邢志伟1,徐铭怡1,罗晓2,罗谦2   

  1. (1.中国民航大学电子信息与自动化学院,天津 300300;2.中国民航局第二研究所信息技术分公司,成都 100142)
  • 收稿日期:2018-03-04 修回日期:2018-04-02 出版日期:2018-08-25 发布日期:2018-10-25
  • 作者简介:邢志伟(1970—),男,辽宁沈阳人,教授,博士,研究方向为民航装备与系统、机场交通信息与控制.
  • 基金资助:
    国家自然科学基金项目(U1533203);中央高校基本科研业务费专项(3122014P003)

Optimization and simulation of departure aircraft taxiing path

XING Zhiwei1, XU Mingyi1, LUO Xiao2, LUO Qian2   

  1. (1. College of Electronic Information and Automation, CAUC, Tianjin 300300, China;2. Information Filiale, Second Research Institute of CAAC, Chengdu 100142, China)
  • Received:2018-03-04 Revised:2018-04-02 Online:2018-08-25 Published:2018-10-25

摘要: 可变滑行时间是评估机场场面交通流特性的重要指标,其影响机场的运行效率、旅客满意度及污染物排放。以国内某大型枢纽机场为例,构建飞机离场场面交通流特性的模型。通过分析离港交通流的特性规则、飞机在离港滑行路径中的拥塞规律,根据元胞自动机原理,将机场场面滑行区域的交通流视作由节点和链路构成的机场网络拓扑结构,以飞机滑行时的规则和飞机之间可能发生的冲突作为约束控制条件。使用蒙特卡洛算法得出最优滑行路径,计算出最小滑行时间。最后,结合航班运行数据对所建模型进行仿真分析。结果表明,该模型能有效减少离港飞机的滑行等待时间,缓解机场场面交通流的拥堵情况,充分调度和合理分配机场地面资源。

关键词: 可变滑行时间, 离港交通流, 机场网络图, 元胞自动机, 蒙特卡洛算法, 运行优化

Abstract: Variable taxiing time is an important index to evaluate the characteristics of airport traffic flow, which affects airport operation efficiency, passenger satisfaction and pollutant emission. Taking a large domestic hub airport as instance, the aircraft departure traffic flow model is constructed. Through analyses of departure traffic flow characteristics and congestion rules during departure taxiing path, and according to cellular automata theory,traffic flow of airport taxiing area is regarded as airport network topology structure made of node and link, taking taxiing rule and possible conflicts between aircrafts as constrained control conditions. Monte-Carlo algorithm is employed to achieve optimal taxiing path and shortest taxiing time. Finally, model simulation is conducted based on operational flight data. Result shows that the current model can effectively reduce taxiing time of departure flights, alleviate traffic congestion, fully schedule and reasonably allocate airport ground resource.

Key words: variable taxiing time, departure traffic flow, airport network diagram, cellular automata, Monte-Carlo algorithm, operation optimization

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