Dynamic Nexus between Air-Transportation and Economic Growth: A Systematic Literature Review

Today’s economic growth is not promising without air transport, up-to-date airports infrastructure, efficient and safe airline services and international air transport networks. According to WB [1], 40% of the world-wide tourists travel by air transport. The main aim of this study is to analyze the literatures of air transport and economic growth study. A systematic literature review (SLR) method was used in order to examine related articles from ABDC list journals which are ranked on A*, A or B, published in period 1992-2018. This study gives a summary of the trends and research themes which have been identified. Key scholars, as well as their approaches and locations and citations are also mapped. The findings of this study show that there is a growing interest in researching and publishing on Air transportation and economic growth. This study fills a deficiency in specialized literature concerning air transportation in developing countries and provides a foundation for future research in the field of air transportation.

China's Air Transport Market and Distribution of airports

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Collaboration Optimization of Flight Schedule in Beijing⁃Tianjin⁃Hebei Airport Group

The coordinated and integrated development of regional airport group system has been identified as an important research topic in the field of air traffic management in China.However,due to the clear limitation on airspace resources and severe traffic congestion,it is necessary to further study the problem of flight schedule coordination optimization for airport clusters.We take the Beijing-Tianjin-Hebei airport Group as an example and construct an optimization model of flight schedule with the minimum adjustment and delay.The design of the implementation algorithm is proposed.As demonstrated by the simulation results,the flight delay in the Beijing-Tianjin-Hebei multi-airport system is noticeably reduced by applying both the optimization model and the algorithm proposed in this paper.

A Bilevel Programming Approach for Optimization of Airport Ground Movement

This paper proposes an optimization model for the airport ground movement problem(GMP)based on bilevel programming to address taxi conflicts on the airport ground and to improve the operating safety and efficiency.To solve GMP,an iterative heuristic algorithm is designed.Instead of separately investigating each problem,this model simultaneously coordinates and optimizes the aircraft routing and scheduling.A simulation test is conducted on Nanjing Lukou International Airport(NKG)and the results show that the bilevel programming model can clearly outperform the widely used first-come-first-service(FCFS)scheduling scheme in terms of aircraft operational time under the precondition of none conflict.The research effort demonstrates that with the reduced operating cost and the improved overall efficiency,the proposed model can assist operations of the airports that are facing increasing traffic demand and working at almost maximum capacity.

Homogeneity Analysis of Multiairport System Based on Airport Attributed Network Representation Learning

The homogeneity analysis of multi-airport system can provide important decision-making support for the route layout and cooperative operation.Existing research seldom analyzes the homogeneity of multi-airport system from the perspective of route network analysis,and the attribute information of airport nodes in the airport route network is not appropriately integrated into the airport network.In order to solve this problem,a multi-airport system homogeneity analysis method based on airport attribute network representation learning is proposed.Firstly,the route network of a multi-airport system with attribute information is constructed.If there are flights between airports,an edge is added between airports,and regional attribute information is added for each airport node.Secondly,the airport attributes and the airport network vector are represented respectively.The airport attributes and the airport network vector are embedded into the unified airport representation vector space by the network representation learning method,and then the airport vector integrating the airport attributes and the airport network characteristics is obtained.By calculating the similarity of the airport vectors,it is convenient to calculate the degree of homogeneity between airports and the homogeneity of the multi-airport system.The experimental results on the Beijing-Tianjin-Hebei multi-airport system show that,compared with other existing algorithms,the homogeneity analysis method based on attributed network representation learning can get more consistent results with the current situation of Beijing-Tianjin-Hebei multi-airport system.

Effects of Accurate Weather Forecast on Air Transport in Shanghai on March 17 in 2016

From the evening on March 17 to the morning on March 18 in 2016,advection low-cloud and advection fog weather appeared in Shanghai Pudong International Airport. The forecasters on duty accurately forecast the weather process in advance on March 17,which could provide favorable references for each airline to make correct plans for flights and for related control departments to control airspace flow,avoid a large area of flight delay,alternating and returning of flights,and disorder of air traffic order,and ensure the safety and efficiency of air transport in Shanghai.

Designing Sustainable Airport Ground Access/Egress Systems Supported by Fast-Time Modeling

The problems of airport landside capacity assessment are of industry-wide interest. Evaluation of landside capacity enables airport operators and airport designers to identify passenger and baggage flow bottlenecks, identify the primary cause of bottlenecks formation and take measures mitigating the impact of bottlenecks on the airport terminal operation. Many studies dealing with the problems of airport landside capacity are focused mainly on the processing part of the airport terminal and consider the airport terminal to be an isolated system. Even the most of models of airport landside operations developed using various simulation （both generic and dedicated） software packages （e.g., PaxSim, SLAM, WITNESS, ARENA or EXTEND） are designed for simulating the passenger and baggage flows only between curb-side and apron. Although this approach provides valuable data concerning capacity, delays or processing bottlenecks, in some cases identified capacity constraints are only the symptoms of the actual problem. In order to discover the cause of the problem, it is necessary to consider the airport terminal as an integral part of much more complex regional, national or international transportation system. This article reflects the above mentioned requirements and introduces an innovative approach to passenger and baggage flow simulation based on the fact that airport terminal is considered as an integral part of air passenger door-to-door transportation process.

机场飞行区多层异质链序风险传播模型研究

为探究机场飞行区风险发生机制及风险传播特性,增强机场飞行区安全管控能力,采用复杂网络理论,依据风险致因间的因果链序关系,构建多层异质网络风险传播模型。采用多层次因果图(AcciMap)理论分析机场飞行区运行风险传播的致因链;基于风险致因特征构建3层异质风险传播网络并根据网络特征设计概率-触发传播模型、容量-阻抗传播模型、容量-负荷传播模型;利用复杂网络理论设计风险传播评价指标,对风险网络传播特征进行分析。结果表明:多层风险网络中节点风险传播能力与节点度弱相关,节点风险灵敏指数可提升风险节点排序准确性;对风险灵敏度指数排序前15%的节点进行风险控制,可有效降低风险扩散近32%;网络风险传播结构存在高连通和松散状态,对风险扩散指数排序前15%的节点进行控制,可以有效降低网络结构鲁棒性指数使风险网络结构由高连通进入到松散状态;所建模型可有效识别风险扩散过程并进行精准控制,以提升机场飞行区风险控制水平。

进港航班滑入时间预测

准确预测进港航班滑入时间对合理调配航班保障资源和提高机场场面运行效率具有重要意义,可有效克服各大机场粗放式预测航班进港时刻的不足,为此提出一种基于机器学习模型的滑入时间预测方法。以首都机场为具体研究对象,分析进港航班滑入时间的影响因素并构建特征集;将线性回归、K-最近邻、支持向量机、决策树、随机森林和梯度提升回归树6种在滑出时间预测方面得到广泛应用的机器学习模型用于进港航班滑入时间预测。研究结果表明:在误差范围±3 min内6种机器学习模型的预测精度均超过90%,表明特征集的构建和模型的选择是有效的;综合预测性能与模型拟合评估结果,梯度提升回归树模型的预测效果最好;在梯度提升回归树模型上场面流量特征的贡献度最大,新引入的跨区特征对预测模型的贡献度超过了大部分传统特征。

基于改进鲸鱼优化算法的离场航班时刻优化

面对航空客货运输服务迅速增长、各地机场离港高峰时段拥挤度激增的情况,需要对离场航班进行优化配置,降低高峰时段离场总延误时间,同时保障航空公司申请的航班时刻总偏移。考虑航班时刻唯一性、走廊口流量限制、机场容量限制等因素,建立双目标离场航班时刻优化模型,运用精英反向策略与黄金正弦算法对鲸鱼优化算法(WOA)进行改进后求解。以北京首都国际机场为例,使用AirTOp对优化后的结果进行仿真验证。结果表明:优化后航班平均延误减少77.62%。因此,改进鲸鱼优化算法可以有效降低离港高峰时段延误,增强机场运行效率,合理配置有限的时刻资源。

考虑机场、航空公司与空管需求的机场群离场航班时刻优化

随着中国航空流量的不断增加,机场群内航班延误时间长、延误架次多、机场时刻紧张等问题逐渐暴露,这些问题主要是航班时刻设置不合理所导致。为解决这些问题,需要对机场群内航班时刻进行优化。通过从机场、航空公司、空管3个角度综合考虑,分别以延误时间、航空公司航班时刻调整总方差、管制员总调整量作为优化目标,建立了机场群航班时刻优化模型,并使用权重线性递减的粒子群优化算法实现对模型的求解。以京津冀机场群为例进行分析,使用MATLAB对模型进行寻优。结果表明优化后机场群内总延误时间由77580 min减少至46260 min,航空公司航班时刻调整总方差由447.076减少至63.141,管制员总调整量由467次减少至253次,3个目标均得到了优化。可见该模型权衡了机场、航空公司与空管之间的公平性,为机场群航班时刻的优化提供了理论参考。

浦东国际机场T3航站区地下综合交通枢纽结构设计及关键问题研究

浦东国际机场四期T3航站区地下综合交通枢纽工程为濒海环境的超深超大地下工程,建筑面积约为64万m^(2)。多条地铁及捷运、排水渠、市政道路设施等穿越地下室,轨交、市政结构与航站楼地下建筑结构合建,结构复杂程度高。介绍了工程的主要结构特点、桩基础前期试验研究和选型设计、多种功能合建地下结构设计方法;阐述了超大型复建式地下结构抗震分析、地下综合枢纽结构抗震性能化设计、开敞式地下室对结构抗震设计影响、超长地下结构抗裂抗渗设计、地铁振动对结构舒适度的影响、地下通道合建转换结构抗爆分析等若干关键结构设计问题的研究和应对措施。

成渝机场群运行效率的测度与评价研究

成渝机场群是中国重要的航空交通枢纽以及连接西南地区的重要节点,探讨成渝机场群的运行效率对成渝地区经济和交通发展的重要意义。明确了成渝机场群的投入指标和产出指标,使用Kendall和Spearman相关性分析法对指标间的关系进行了分析,并利用层次分析法对数据进行了处理。运用数据包络分析法(Data Envelopment Analysis,DEA)对机场群的运行效率进行了深入研究,通过DEAP 2.1软件对三个模型进行求解,从静态、动态和Malmquist指数方面评价了成渝机场群的运行效率。研究结果显示,投入与产出指标之间存在较强的正相关性;成渝机场群整体效率偏低,特别是在货邮吞吐量方面存在严重的产出不足问题;各个机场之间的效率差距较大,存在资源利用不足的问题。

基于强模糊云的机场刚性道面易损性评价

为进一步完善民用机场飞行区道面的评价体系,在现有的道面评价管理技术规范基础上,建立新的刚性道面易损性评价体系,综合考虑结构和功能2个方面对道面做出综合易损性评价,分别选取有代表性的5个结构性指标和4个功能性指标,并通过熵权法确定各指标在子体系中的权重,借助模糊云评价模型在定性概念和定量描述之间相互转化的突出优势,在拓展云模型(ECM)的基础上提出强模糊云(SFCM)模型,建立道面综合易损性评价模型。结合中国南部某机场实际机场道面检测数据分析,得到该机场道面综合易损性评价值为2.277,道面评价结果为具有较大易损性,评价结果的置信度接近1,说明计算结果有效,同时与ECM的评价结果(2.123)一致,证明评价结果可靠。SFCM充分考虑评价指标不完全符合标准正态分布的特性,构建偏峰分布并增强区间过渡的模糊性,评价结果更符合实际。

高铁对机场城市民航客运的影响测度研究

高铁与民航间的竞合关系使得基于双方比较优势设计和优化中国航空客运网络成为必然。本文以2008—2018年间同时具备高铁站与机场的88个城市为研究对象,在分析高铁建设布局变化的基础上,分别探讨了高铁对中国民航客运的阻力效应、机场旅客吞吐量增速及机场城市的航空等级结构的影响,结果表明:中国高铁建设布局呈现从东部、中部向西部、东北部扩展的态势,且城市对距离在1200 km以下时,高铁对民航客运的阻力效应更为明显。此外,高铁线路开通后第2年对42个机场旅客吞吐量增速及21个机场城市的航空等级结构有负向抑制作用,对19个机场旅客吞吐量增速及47个机场城市的航空等级结构有正向促进作用。因此,中国航空客运市场应结合高铁竞合效应差异,针对性地设计和优化航线网络以发挥航空客运网络优势。

基于二次分解集成的机场流量短期预测

为实现准确的机场流量短期预测,本文建立了基于二次分解方法的分解集成预测模型。首先,应用局部加权回归周期趋势分解(STL,seasonal and trend decomposition procedure based on Loess)算法将原始时间序列分解为趋势项、季节项和余项3个分量,并计算其样本熵。其次,应用遗传算法(GA,genetic algorithm)优化变分模态分解(VMD,variational mode decomposition)参数,对熵值较大的分量进行二次分解。再次,使用极端梯度提升(XGBoost,extreme gradient boosting)对二次分解后的所有分量进行预测,采用加和集成得到最终的预测值。最后,采集国内典型机场实际运行数据进行实例分析。针对北京首都国际机场60 min进场、离场流量时序,本文模型预测的均等系数(EC,equal coefficient)值分别为0.9703、0.9959,相比其他常用模型均有所提高。此外,对于上海浦东、上海虹桥、广州白云3个大型国际机场,本文模型在60 min、30 min统计尺度下进场和离场流量预测的EC值均在0.9700以上,15 min统计尺度下预测的EC值均在0.9500以上。结果表明,本文建立的二次分解集成预测模型具有良好的准确性和普适性,用于机场流量短期预测是可行和有效的。

空港综合交通枢纽建筑智能化机房规划

空港综合交通枢纽建筑实质上是由多个单体构成的建筑群或园区,各单体功能性较强,且单体的智能化机房之间联系紧密,这与项目自身的管理需求直接相关。以某大型机场为例,对智能化机房的规划进行深入剖析,通过信息技术与智能系统的集成,合理设计和布局机房,以支持数据处理、网络通信和系统监控,提升机场运营效率、保障安全性与服务质量。

延误传播控制导向的机场保障效率量化与评估

为量化和评估机场保障对延误传播的控制能力,提出一种延误传播控制导向的机场保障效率量化方法。利用线性回归方法计算机场保障效率及其波动范围,同时考虑延误控制手段、机场拥挤、时间段等因素对延误传播的影响。以中国45座主要机场为例,基于2019年航班延误数据,分析不同繁忙程度、不同延误水平下的机场保障效率特征,并讨论机场保障效率与航班延误的内在关联。研究发现,高繁忙度机场的保障效率易受到延误航班判定标准的影响;部分中低繁忙机场可在航班延误传播控制中发挥延误缓冲的作用;高效机场在应对60 min以上的传播延误时具有显著优势。

城市发展对临空经济区空间异质性影响研究

临空经济区建设对推动产业结构升级、促进经济高质量增长至关重要。为探究城市发展对临空经济区的空间异质性影响,以全国51个国家级及地方临空经济区为研究对象,采用核密度分析法可视化并充分讨论了临空经济区发展的演化过程,同时构建了融合综合交通时间、航空运输业务水平等属性的复合邻近关系,在此基础上提出了基于多维距离的地理加权回归模型(MD-GWR),并以此对临空经济区发展的驱动因素进行建模,从而提出了促进各地区临空经济增长的差异化政策。研究表明:MD-GWR模型相比经典GWR模型拥有更优异的拟合精度,较经典GWR模型与OLS模型分别提升了12.52%与40.17%;城市经济体量、商业贸易、招商引资、企业规模、科技实力、产业结构对临空经济增长影响均存在显著的空间异质性,对不同地区的影响程度与方向具有较大差异;为推动临空经济区高质量发展,应进一步提升东北及西北地区城市的对外开放水平,提高东部地区城市的外商投资质量,完善东北及中西部地区城市的产业结构调整政策,加大乌鲁木齐、长春等城市的科技研发资金投入。研究结果有助于明确我国各城市临空经济区的发展规律与驱动机理,为制定具有针对性且差异化的临空经济区发展政策提供理论依据,对促进临空经济高质量增长具有重要意义。

基于深度可分离注意力网络的机场网络因果时延关系探究

探究机场网络延误传播因果关系及获取因果时延效应对于剖析机场网络延误传播机理,提出机场网络延误应对措施具有重要意义。为科学、准确地挖掘机场网络延误传播因果关系,本文运用卷积神经网络的方法,提出了一种基于注意力机制的深度学习框架。该框架主要分为两个部分:基于注意力机制的深度可分离扩张因果卷积神经网络的因果关系探究和基于置换重要性方法的因果关系验证,并提出延误传播因果时延指数的概念,用以表征机场间延误传播所需要的时间步长(本文中的1个时间步长等于1h),进而构建了机场网络延误传播因果时延效应网络图。为进一步验证所提方法的有效性,选取我国2019至2020年夏秋和冬春航季的国内离港航班运行数据进行实例分析,实验结果表明,我国机场网络中存在广泛的延误传播因果关系,且夏秋航季中的因果关系多于冬春航季。在延误传播中,机场的重要程度与其规模并不完全一致,大多数延误传播因果关系中的“因”机场主要为我国中小型机场,应重点关注该类机场的延误治理能力提升。此外,针对延误传播因果时延效应,我国夏秋(冬春)航季机场对之间延误传播的平均时延指数约为4.5(5.6)个时间步长,这表明夏秋(冬春)航季中“因”机场的延误将在4.5(5.6)小时内传播至“果”机场,“果”机场可根据时延指数及时调整机场运行管理措施以应对“因”机场带来的延误,防止大面积航班延误的发生。综上,本研究可为航司、机场、管制等部门在减少延误、提高民航运行安全与效率方面提供相应的决策支持。