交通运输系统工程与信息 ›› 2023, Vol. 23 ›› Issue (1): 284-294.DOI: 10.16097/j.cnki.1009-6744.2023.01.030

• 系统工程理论与方法 • 上一篇    下一篇

基于复杂性的多扇区移交策略优化

王红勇*,张加豪,许平   

  1. 中国民航大学,空中交通管理学院,天津 300300
  • 收稿日期:2022-10-19 修回日期:2022-12-06 接受日期:2022-12-09 出版日期:2023-02-25 发布日期:2023-02-16
  • 作者简介:王红勇(1979- ),男,山西洪洞人,副研究员,博士。
  • 基金资助:
    国家自然科学基金 (U1833103);天津市应用基础多元投入基金重点项目 (21JCZDJC00840)

Optimization of Multi-sector Transfer Strategy Based on Complexity

WANG Hong-yong*, ZHANG Jia-hao, XU Ping   

  1. College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China
  • Received:2022-10-19 Revised:2022-12-06 Accepted:2022-12-09 Online:2023-02-25 Published:2023-02-16
  • Supported by:
    National Natural Science Foundation of China (U1833103);Key Program of Tianjin Science and Technology Plan (21JCZDJC00840)

摘要: 现有多扇区移交间隔管理研究往往忽视扇区复杂性,可能出现扇区局部复杂性不均衡等问题,对空域造成一定安全隐患。本文充分考虑多个管制扇区复杂程度,提出一种新的管制移交间隔优化方法。首先,基于扇区之间复杂性的相互影响关系,建立大型区域管制中心多扇区网络模型。其次,提出航空器进入多扇区边界时刻调整,航空器进入各个扇区时刻调整以及航空器高度层重新配备等3种策略,建立以多扇区复杂性的均值、均衡程度和航空器总延误为目标的移交策略优化模型,并采用多目标遗传算法进行求解。最后,基于北京区域管制中心(ZBAAAR)的实际运行数据进行仿真分析。结果表明:3种策略可使复杂性均值分别降低2.2%,2.8%,6.0%,可使复杂性均衡程度分别提高1.76%,1.83%,1.38%,基于航空器进入时刻控制的两种策略导致航班平均延误时间分别为-295 s和-214 s,验证了模型及算法的有效性。

关键词: 航空运输, 空中交通复杂性, 多扇区复杂性, 多管制扇区, 移交策略

Abstract: The complexity of the sector is often neglected in the existing research of multi-sector transfer interval management, which may lead to some problems, such as unbalanced local sector complexity, and thereby cause security risks to airspace. This paper fully considers the complexity of multiple control sectors, and proposes a new optimization method of minute-in-trail. First, a multi-sector network model of a large regional control center is established based on the interaction of complexity between sectors. Then, three strategies are put forward, i.e., the time adjustment of aircraft entering multi-sector boundary, the time adjustment of aircraft entering each sector and the reassignment of flight level. A transfer strategy optimization model is established, which take the average of the complexity of multi-sector, the degree of equilibrium, and the aircraft delay as the objective. A multi-objective genetic algorithm is adopted to solve the model. Finally, the simulation analysis is carried out based on the actual operation data of the Beijing Regional Control Center (ZBAAAR). The results showed that: the three strategies can reduce the average complexity by 2.2% , 2.8% , and 6.0% respectively, and the complexity equilibrium is increased by 1.76% , 1.83%, and 1.38%, respectively. The two strategies based on aircraft entry time control result in an average flight delay time of -295 s and -214 s, respectively, which verifies the effectiveness of the model and algorithm.

Key words: air transportation, air traffic complexity, multi-sector complexity, multiple control sector, transfer strategy

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