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基于SPN的近距平行跑道容量建模与分析

王洁宁a,b,徐宁霞a,姜高扬b   

  1. (taptap下载安装安卓a.空中交通管理研究基地;b.天津市空管运行规划与安全技术重点实验室,天津300300)
  • 收稿日期:2013-03-27 修回日期:2013-04-19 出版日期:2014-04-25 发布日期:2014-03-21
  • 作者简介:王洁宁(1966—),男,甘肃兰州人,教授,博士,研究方向为空管仿真、空管软件技术.
  • 基金资助:

    天津市自然科学基金项目(10JCYBJC00800);中央高校基本科研业务费专项(ZXH2012N004,3122013P008);国家自然科学基金项目(60832011);中国民用航空局科技基金项目(MHRD200913)

Capacity modeling and analysis of closely spaced parallel runways based on SPN

WANG Jie-ninga,b,XU Ning-xiaa,JIANG Gao-yangb   

  1. (a. Air Traffic Management Research Base;b. ATM Operation Planning and Safety Techniques Key Lab of Tianjin,CAUC,Tianjin 300300,China)
  • Received:2013-03-27 Revised:2013-04-19 Online:2014-04-25 Published:2014-03-21

摘要:

跑道理论容量计算是机场容量评估的一项重要内容。传统方法是针对跑道实际运行情况建立特定的数学模型进行粗略计算,本研究则采用随机Petri网(stochastic Petri net,SPN)建立通用的近距平行跑道运行模型,通过同构马尔科夫链,建立系统稳态概率表达式,进而建立跑道容量数学模型。在此基础之上,将跑道容量的影响因素映射成相应变迁的激发率,通过对激发率的调整,实现了不同条件下交替起降近距平行跑道容量的计算与分析。与传统方法相比,该方法所建模型可复用性强,参数调整更为灵活,为跑道理论容量的计算与分析提供了新的解决方案。

关键词: 随机Petri网, 跑道容量, 近距平行跑道, 马尔科夫链, 稳态概率

Abstract:

Runway capacity plays an important role in airport capacity assessment. Traditional methods focus on special rough mathematical model building according to runway operational cases. A novel assessment model for closely parallel runway capacity is proposed based on stochastic Petri net(SPN). Firstly,an SPN model is built to depict the assessment process. Secondly,the homogeneous Markov chain is induced and system steady-state probability is established in accordance with SPN model. Then a consequence representation for a given runway operation is attained to assess runway capacity in different situations. Concretely,the influencial factors of runway capacity are mapped into corresponding transition firing rates. Compared with traditional methods,this one has a high reusability in model and more flexibility in parameter adjustment,which can be seen as a new solution for runway capacity calculation and analysis.

Key words: stochastic Petri net, runway capacity, closely spaced parallel runways, Markov chain, steady-state probability

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