进场航班空中交通流量控制优化研究
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摘要
随着空中交通流量的持续增长,我国现实行的尾随间隔流量控制策略由于缺乏对整体控制效果的综合考虑,已经无法满足实际运行的需求,为此提出了一种对交通流总量控制的流量控制策略,建立了以最小化航班总延误系数为目标的控制优化模型,研究了以区域入口点为限制点的进场航班流量优化控制问题,利用滑动窗算法对模型进行了求解。结果表明,流量控制策略能够大幅减少航班延误时间,将航班之间的延误程度控制在相对均衡的水平,验证了策略和模型的可行性。
With the continuous growth of air traffic flow,due to the lack of comprehensive consideration of the whole control effect,the miles-in-trail flow control strategy currently implements in China has been unable to meet the actual demands. A traffic control strategy based on traffic flow total quantity control was proposed and a control optimization model aimed at minimizing the total flight delay coefficient was established. The optimal control problem of the arrival flight flow was studied,which takes the regional entry point as the limit point,and the sliding window algorithm was used to solve the model. The results showed that the flow control strategy can significantly reduce flight delay time,and controlled the degree of flight delay to a relatively balanced level,which verified the feasibility of the strategy and model.
With the continuous growth of air traffic flow,due to the lack of comprehensive consideration of the whole control effect,the miles-in-trail flow control strategy currently implements in China has been unable to meet the actual demands. A traffic control strategy based on traffic flow total quantity control was proposed and a control optimization model aimed at minimizing the total flight delay coefficient was established. The optimal control problem of the arrival flight flow was studied,which takes the regional entry point as the limit point,and the sliding window algorithm was used to solve the model. The results showed that the flow control strategy can significantly reduce flight delay time,and controlled the degree of flight delay to a relatively balanced level,which verified the feasibility of the strategy and model.
引文
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[3]赵嶷飞,张雯雯.区域空中交通流量控制建模研究[J].飞行力学,2009,27(5):86-88.
[4]Sheth K,Gutierreznolasco S,Petersen J.Analysis and Modeling of Miles-in-Trail Restrictions in the National Airspace System[C].Los Angeles,USA:Aviation Technology,Integration,and Operations Conference,2013.
[5]Agogino A.Evaluating evolution and Monte Carlo for controlling air traffic Flow[C].Montreal Quebec,Canada:Conference Companion on Genetic and Evolutionary Computation Conference:Late Breaking Papers,ACM,2009:1957-1962.
[6]孙浩,胡明华,张颖.基于遗传算法的扇区边界尾随间隔管理方法的研究[J].交通运输系统工程与信息,2010,10(6):174-179.
[7]申晨.空中交通管制移交间隔管理策略研究[D].南京:南京航空航天大学,2012.
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