高密度机场空中交通运行特性分析
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摘要
为准确把握高密度机场空中交通运行规律,有效支撑航空运输建模、仿真、分析与实验等工作,亟需对其交通运行涉及的诸多特性进行科学分析。采用总量分析、概率统计、假设检验、包络分析、相关分析、聚类分析等理论方法,对高密度机场的交通计数分布特性、交通运行时间特性、进离场互适应特性、交通运行相关性、场面交通拥堵特性等进行了系统和全面地分析。上海浦东国际机场实例研究表明,单位时间内跑道/停机位的进场流和离场流计数服从泊松分布,滑行延误时间和无阻碍滑行时间分别服从对数正态分布和正态分布,进离场交通流之间存在明显的耦合作用关系,场面滑行时间与离场累计流量、进场累计流量、起飞队列长度、降落队列长度之间存在显著的线性相关关系。在此基础上,对机场场面拥堵等级及各关键指标临界值进行了分类识别与计算分析。所提方法对任意机场系统均具有普适性,可为机场运行管理和空中交通管理提供理论依据和建模参考。
In order to accurately analyze the laws of air traffic operations in high density traffic airports,and effectively support the modeling,simulation,analysis and experimentation of air transport,it is imperative to conduct scientific analysis on various characteristics involved in traffic operations. The methods of aggregate analysis,probability statistics,hypothesis test,envelope analysis,correlation analysis and cluster analysis were used to investigate the characteristics of traffic count,traffic operation time,interaction between arrivals and departures,correlation among traffic operation indicators,surface traffic congestion. A case study for Shanghai Pudong International Airport shows that the counts of arrival and departure traffic flow in the runway/gate system per unit time obey the Poisson distribution,and the taxiing delay time and unimpeded taxiing time obey the lognormal and the normal distribution,respectively. There is an obvious coupling relationship between arrival and departure operations,and the taxiing time significantly correlates with four indicators including cumulative departure flow indicator,cumulative arrival flow indicator,take-off queue length indicator and landing queue length indicator. Based on the above results,the classification and calculation of surface congestion levels and the corresponding threshold values of each key indicator were presented. The methods proposed are universal for any airport systems,which can provide theoretical basis and modeling references for airport operation management and air traffic management.
In order to accurately analyze the laws of air traffic operations in high density traffic airports,and effectively support the modeling,simulation,analysis and experimentation of air transport,it is imperative to conduct scientific analysis on various characteristics involved in traffic operations. The methods of aggregate analysis,probability statistics,hypothesis test,envelope analysis,correlation analysis and cluster analysis were used to investigate the characteristics of traffic count,traffic operation time,interaction between arrivals and departures,correlation among traffic operation indicators,surface traffic congestion. A case study for Shanghai Pudong International Airport shows that the counts of arrival and departure traffic flow in the runway/gate system per unit time obey the Poisson distribution,and the taxiing delay time and unimpeded taxiing time obey the lognormal and the normal distribution,respectively. There is an obvious coupling relationship between arrival and departure operations,and the taxiing time significantly correlates with four indicators including cumulative departure flow indicator,cumulative arrival flow indicator,take-off queue length indicator and landing queue length indicator. Based on the above results,the classification and calculation of surface congestion levels and the corresponding threshold values of each key indicator were presented. The methods proposed are universal for any airport systems,which can provide theoretical basis and modeling references for airport operation management and air traffic management.
引文
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12尹嘉男,胡明华,张洪海,等.多跑道协同运行模式优化方法[J].航空学报,2014,35(3):795-806Yin Jianan,Hu Minghua,Zhang Honghai,et al.Optimization approach for collaborative operating modes of multi-runway systems[J].Acta Aeronautica et Astronautica Sinica,2014,35(3):795-806
13钟育鸣.机场地面运行仿真评估系统研究[D].南京:南京航空航天大学,2009Zhong Yuming.Airfield running and capacity evaluation simulation study[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2009
14 Gupta G,Malik W,Jung Y.Effect of uncertainty on deterministic runway scheduling[C]//The Proceedings of 11th AIAA Aviation Technology,Integration,and Operations(ATIO)Conference.Virginia:AIAA,2011:1-16
15中国民用航空局.民用机场飞行区技术标准:MH 5001-2013[S].北京:中国民用航空局,2013Civil Aviation Administration of China.Aerodrome technical standards:MH 5001-2013[S].Beijing:Civil Aviation Administration of China,2013
2 The MITRE Corporation.The high density departure and arrival traffic management(HDDAM)concept:MP120146[R].Virginia:MI-TRE,2012
3 Soria M,Lordan O,Sallan J M.Heuristics of node selection criteria to assess robustness of world airport network[J].Chinese Journal of Aeronautics,2017,30(4):1473-1480
4 Voltes-Dorta A,Rodriguez-Deniz H,Suau-Sanchez P.Vulnerability of the European air transport network to major airport closures from the perspective of passenger delays:ranking the most critical airports[J].Transportation Research Part A:Policy and Practice,2017,96:119-145
5 Wilke S,Majumdar A,Ochieng W Y.The impact of airport characteristics on airport surface accidents and incidents[J].Journal of Safety Research,2015,53:63-75
6 Pyrgiotis N,Malonw K M,Odoni A.Modelling delay propagation within an airport network[J].Transportation Research Part C:Emerging Technologies,2013,27:60-75
7 Mueller E,Chatterji G.Analysis of aircraft arrival and departure delay characteristics[C]//The Proceedings of AIAA's Aircraft Technology,Integration,and Operations(ATIO).Virginia:AIAA,2002:1-14
8尹嘉男,胡明华,赵征.多跑道机场停机位分配仿真模型及算法[J].交通运输工程学报,2010,10(5):71-76Yin Jianan,Hu Minghua,Zhao Zheng.Simulation model and algorithm of multi-runway airport gate assignment[J].Journal of Traffic and Transportation Engineering,2010,10(5):71-76
9 Yin J N,Hu M H,Ma Y Y,et al.Airport taxi situation awareness with a macroscopic distribution network analysis[J].Networks&Spatial Economics,2018:1-27
10朱新平,唐志星,夏正洪.基于Petri网的A-SMGCS航空器滑行路由指派[J].信息与控制,2016,45(1):101-107Zhu Xinping,Tang Zhixing,Xia Zhenghong.Petri-net-based aircraft taxiing route assignment for A-SMGCS[J].Information and Control,2016,45(1):101-107
11 Yin J N,Hu Y X,Ma Y Y,et al.Machine learning techniques for taxi-out time prediction with a macroscopic network topology[C]//The Proceedings of 37th AIAA/IEEE Digital Avionics Systems Conference.New York:AIAA,IEEE,2018:713-720
12尹嘉男,胡明华,张洪海,等.多跑道协同运行模式优化方法[J].航空学报,2014,35(3):795-806Yin Jianan,Hu Minghua,Zhang Honghai,et al.Optimization approach for collaborative operating modes of multi-runway systems[J].Acta Aeronautica et Astronautica Sinica,2014,35(3):795-806
13钟育鸣.机场地面运行仿真评估系统研究[D].南京:南京航空航天大学,2009Zhong Yuming.Airfield running and capacity evaluation simulation study[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2009
14 Gupta G,Malik W,Jung Y.Effect of uncertainty on deterministic runway scheduling[C]//The Proceedings of 11th AIAA Aviation Technology,Integration,and Operations(ATIO)Conference.Virginia:AIAA,2011:1-16
15中国民用航空局.民用机场飞行区技术标准:MH 5001-2013[S].北京:中国民用航空局,2013Civil Aviation Administration of China.Aerodrome technical standards:MH 5001-2013[S].Beijing:Civil Aviation Administration of China,2013