Stochastic Air Traffic Flow Management for Demand and Capacity Balancing Under Capacity Uncertainty

This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.

Evolution of Air Traffic Management Concept of Operations and Its Impact on the System Architecture

The air traffic management system(ATM)has the task of ensuring safe,orderly and expeditious flow of air traffic.The ATM system architecture is very much dependent on the concept of operations(ConOps).Over the years the evolution in ConOps has resulted in changes in the ATM′s physical architecture,improving its physical infrastructure,increasing the levels of automation and making operational changes to improve air traffic flow,to cope with increasing demand for air travel.However,what is less clear is the impact of such changes in ConOps on the ATM′s functional architecture.This is vital for ensuring optimality in the implementation of the physical architecture components to support the ATM functions.This paper reviews the changes in the ConOps over the years,proposes a temporally invariant ATM functional model,and discusses some of the main key technologies expected to make significant improvements to the ATM system.

SESAR:The Past,Present,and Future of European Air Traffic Management Research

The Single European Sky Air Traffic management(ATM)Research(SESAR)project is the technological pillar of the European Commission’s Single European Sky Initiative to modernize ATM.Here,we describe the process of establishing SESAR and the main parts of the project:the research and development(R&D)part,which is led by the SESAR Joint Undertaking;the deployment part,which is managed by the SESAR Deployment Manager;and the European ATM Master Plan,which collects and lays out both the R&D and deployment needs.The latest European ATM Master Plan was adopted just prior to the current pandemic.The huge loss in air traffic due to the pandemic,and the speed of the recovery of the aviation industry will require reprioritization,but the main elements that have been established-particularly those in support of the environment-remain valid.

En-route Sector Complexity Control Strategies in Air Traffic Management

Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the operational efficiency of air transport systems. Thus,objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment,and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary,we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast,the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models,we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.

Review on artificial intelligence techniques for improving representative air traffic management capability

The use of artificial intelligence(AI)has increased since the middle of the 20th century,as evidenced by its applications to a wide range of engineering and science problems.Air traffic management(ATM)is becoming increasingly automated and autonomous,making it lucrative for AI applications.This paper presents a systematic review of studies that employ AI techniques for improving ATM capability.A brief account of the history,structure,and advantages of these methods is provided,followed by the description of their applications to several representative ATM tasks,such as air traffic services(ATS),airspace management(AM),air traffic flow management(ATFM),and flight operations(FO).The major contribution of the current review is the professional survey of the AI application to ATM alongside with the description of their specific advantages:(i)these methods provide alternative approaches to conventional physical modeling techniques,(ii)these methods do not require knowing relevant internal system parameters,(iii)these methods are computationally more efficient,and(iv)these methods offer compact solutions to multivariable problems.In addition,this review offers a fresh outlook on future research.One is providing a clear rationale for the model type and structure selection for a given ATM mission.Another is to understand what makes a specific architecture or algorithm effective for a given ATM mission.These are among the most important issues that will continue to attract the attention of the AI research community and ATM work teams in the future.

Assessing Air Traffic Management Performance Interdependencies through Bayesian Networks： Preliminary Applications and Results

The performance model proposed by this study represents an innovative approach to deal with performance assessment in ATM （air traffic management）. It is based on Bayesian networks methodology, which presents several advantages but also some drawbacks as highlighted along the paper. We illustrate the main steps required for building the model and present a number of interesting results. The contribution of the paper is two-fold： （1） It presents a new methodological approach to deal with a problem which is of strategic importance for ANSPs （air navigation service providers）; （2） It provides insights on the interdependencies between factors influencing performance. Both results are considered particularly important nowadays, due to the SES （Single European Sky） performance scheme and its related target setting process.

Ontology-Based Approach for Human Competency Gap Analysis in Air Traffic Management:A Case Study of Georgia

The Global Air Navigation Plan is a flexible global engineering approach that allows all States to advance their Air Navigation capacities based on their specific operational requirements.Aviation professionals have an essential role in the transition to,and successful implementation of the GANP.The research work is focused on the creation of methodology for the partial automation of the comparison competences of Air Traffic Management(ATM)personal and synthesis of training courses and modules,using a formal,ontology-based approach as a tool to solve these problems.One of the problems in the implementation of the GANP is that,on the one hand,there are currently no unified requirements for all categories of ATM personnel,and on the other hand,the development of ATM technologies is far ahead of the pace of training of personnel of appropriate qualifications.This problem becomes even more noticeable in countries that have just started an active modernization of ATC systems and do not have enough experience in this field.The paper describes the general methodological approach based on the education ontology modelling for human competency gap analysis in ATM and for gap analysis between the university curricula outcomes and the ATM requirements.The ontology of key personnel competencies issues for the design and integration of large-scale future ATM programmes is proposed.

Human Resource Management:A Case Study of the Air Traffic Controller Strike in 1981

The article discusses several hemispheres of human resource management based on a typical case review. The study presents the main problems of the case from both employees and organizations; the issued problems involve compensations and benefits,restructuring,job design,and training. Based on the analysis of the case,two alternative solutions state that the potential routes for the organizations to avoid serious negative results. The study introduces a number of recommendations that can be used as a reference for other organizations to avoid similar risks.

A study on basic research priorities and development suggestions for the digital transformation of air traffic management

Air traffic is exhibiting the characteristics of high density,high volume,and unmanned operations.To ensure smooth,efficient,safe,and reliable operations,it is necessary to promote the digital transformation of Air Traffic Management(ATM)with digitalization,autonomy,and collaboration as its typical features.This article,based on the background of current and foreseeable future ATM needs,deeply analyzes the challenges and opportunities faced by traditional ATM.It explores and proposes to further investigate the commonalities,characteristics,and evolution of air traffic,the interaction mechanism of"human-machine-environment"in air traffic,the integrated design of airborne avionics and ATM systems,the comprehensive integration of ATM based on vulnerability analysis,airspace classification management,air traffic flow management,key technologies of"perception-collision avoidance",wake vortex monitoring and interval reduction,unmanned aerial vehicle management,and the expansion of ATM capabilities in the"high frontier".The research suggests strengthening top-level planning,building an open,mutually beneficial,and win-win digital ATM ecological framework based on multi-party collaboration,coordinating the research and application of new digital ATM technologies,accelerating the occupation of the new track of low-altitude economy,and enhancing ATM capabilities driven by the digital transformation of ATM.

Modeling of 3-D Air Traffic Complexity Based on Route Structure Constraints

It is an important issue to assess traffic situation complexity for air traffic management.There is a lack of systematic review of the existing air traffic complexity assessment methods,and there is no consideration of the role of airspace and traffic coordination mechanism.A new 3-D airspace complexity measurement method is proposed based on route structure constraints to evaluate the air traffic complexity objectively.Firstly,the model of the impact on horizontal and vertical direction for“aircraft pair”is established based on the route guidance.After that,the coupled complexity model for 3-D airspace is given according to the modification on the model in terms of flight standardization.Finally,the global model of the airspace traffic complexity is established.It is proved by the experimental data from the actual operation in airspace that the proposed model can reflect the space coupling situation and complexity of aircraft.At the same time,it can precisely describe the actual operation of civil aviation in China.

Identification of Information-Seeking Behaviors from Air Traffic Controllers′ Eye Movements

Air traffic controllers are the important parts of air traffic management system who are responsible for the safety and efficiency of the system.They make traffic management decisions based on information acquired from various sources.The understanding of their information seeking behaviors is still limited.We aim to identify controllers′ behavior through the examination of the correlations between controllers′eye movements and air traffic.Sixteen air traffic controllers were invited to participate real-time simulation experiments,during which the data of their eye ball movements and air traffic were recorded.Tweny-three air traffic complexity metrics and six eye movements metrics were calculated to examine their relationships.Two correlational methods,Pearson′s correlation and Spearman′s correlation,were tested between every eye-traffic pair of metrics.The results indicate that controllers′two kinds of information-seeking behaviors can be identified from their eye movements:Targets tracking,and confliction recognition.The study on controllers′ eye movements may contribute to the understanding of information-seeking mechanisms leading to the development of more intelligent automations in the future.

OPTIMAL FLOW CONTROL PROBLEM IN AIR TRAFFIC CONTROL:PARTⅠ

The fundamental case is considered in which flights from many destinations must be scheduled for arrival at a single congested airport having limited capacities.An air traffic control(ATC)model is developed in this case.A new and efficient algorithm for the optimal solution of ground holding strategy problem(GHSP)is put forward and verified by a numerical example.

Design and Analysis of Computer Experiments Based on a Simulation Model of Air Traffic Flow Optimization in Panama

There is a growing in number of operations in aviation all over the world.This growing is increasing the necessity of innovation and new technology to respond the increment of the demand.As a respond of this demand,FAA(Federal Aviation Administration)is working with NextGen in the United States and the EUROCONTROL is implementing the Point Merge as solution in the air traffic flow management in Europe.However,the FAA alternative and EUROCONTROL alternative are not mutually exclusive since Panama,a small country in Latin America,is trying to use a combination between the vectoring approach and the Point Merge in the air traffic flow management.In addition,the AAC(Autoridad de Aereonautica Civil)and the Tocumen(Tocumen International Airport)are working in a continuous collaboration between FAA and Panama with the mutual challenge to improve the actual system.As a result,the main airline of Panama,the Compania Panamena de Aviacion(COPA Airlines),and the Autoridad de Aeronautica Civil(AAC)constructed a simulation model to select an air traffic flow alternative that can be able to change the actual situation.In other words,COPA Airlines and AAC are pursuing the minimization of the numbers of conflicts,the number of sequence actions,the flight time,the track flight distance and the fuel burn.Furthermore,this study aims to use the final draft of this previous analysis based on a simulation methodology to conduct a Design and Analysis of Computer Experiments with the final objective to increment the statistical significance of the actual model.

基于Transformer-GRU网络的4D航迹预测

航空器的4D航迹预测作为基于航迹运行(TBO)的关键技术之一具有非常重要的意义。基于Transformer-GRU(T-GRU)网络,提出了一种新的航迹预测方法,结合Adamax优化器实现了4D航迹预测。利用Transformer网络的自注意力机制对输入序列进行建模,通过GRU网络获取时序数据的特征;对原始航迹数据进行重采样插值和中值滤波等预处理,以便消除数据缺失和异常值等对预测的影响;通过E E、E AT、E CT、E A等误差指标对实验结果进行评价,并与其他常用的航迹预测方法进行对比。研究结果表明:与传统深度学习方法相比,基于T-GRU网络的4D航迹预测模型在航迹预测中具有更高的准确性和鲁棒性。

基于OBE理念的机场管制模拟训练改革与实践

基于OBE理念,从课程目标、实践内容、实践过程和考核方法以及校企联合授课教学等方面对机场管制模拟训练进行改革。实践表明:课程目标反向设计、实践内容与训练难度分层设计、指导教师及学生动态分组、基于教考分离和自动评价的面向过程考核、校企联合教学等改革手段,能较好地解决教学存在的问题。与改革前相比较,不仅课程平均分有所提升,优秀比例也进一步提高,60~69分段比例下降明显,课程达成度提升效果显著。基于OBE理念的改革方案和实践成果为交通运输类专业的实践教学提供了应用案例。

基于结构主题模型的民航管制不安全事件主题识别

为探究民航管制运行不安全事件的发生规律及特点,采用结构主题模型捕捉报告中的词汇共现及层次结构。考虑结构主题的语义连贯性以及排他性等指标,辨识管制运行事件的最优主题数目。选取事件严重度及发生时间等协变量,构建融合多变量的主题分析,挖掘不同类型事件的严重度差异性及在时间维度上的演化趋势。最后,基于航空安全自愿报告系统2018-2022年的4346起管制事件报告进行实证分析。研究结果表明:与管制运行有关的不安全事件可分为管制移交、恶劣天气、人为因素事件、夜航航班、场面滑行、起飞离场、部门协调、雷达间隔、设备故障、进近程序、陆空对话、复杂空域环境、飞行冲突、飞行高度、冲/偏出跑道及跑道侵入15类;飞行区滑行、进近程序、飞行冲突等事件更易产生严重事故;飞行高度有关的不安全事件呈逐年上升趋势。研究结果可为提升管制运行安全风险水平提供理论支持,并为管理人员针对性施策提供参考。

机场航班时刻资源管理研究进展

繁忙机场都会面临严重的交通拥堵和航班延误问题。解决该问题的一个有效手段是对机场航班时刻资源进行优化管理。全面介绍了航班时刻资源管理相关的研究进展,系统回顾了机场公布容量设置、机场航班时刻配置的主要方法和手段。从公布容量确定、单机场、机场网络层面和机场群航班时刻配置及航班时刻配置技术复杂性等方面,得出机场航班时刻资源优化配置的关键技术问题。展望了机场航班时刻资源管理的主要方向,并对下一步研究提出建议。

基于扇区开合的管制员排班优化

为提高管制员的利用效率和工作满意度,制定出更切合实际运行的管制员排班表,从管制工作的实际需要出发,以人员需求数量最少为目标,在符合民航局各种规章要求的基础上,建立管制员排班模型。在初始模型的基础上,又考虑了人员对工作及休息时间的个性化需求,对模型进行改进。最后以某空中交通管理局区域管制室管制员数据为例进行分析,使用LINGO求解器对模型进行求解。结果表明:与手工编制的排班时间表相比,通过排班优化模型制定出的排班方案减少了执勤人数,避免了人员浪费,并能较为充分地满足管制员的个性化需求。

基于通信信号管制的城市空中交叉口设计研究

为确保城市低空空域内无人机规模化运行安全,缓解低空交通运行瓶颈,本文借鉴地面交通较为成熟的研究成果,结合城市低空及无人机运行特色,提出一种基于通信信号管制的城市空中交叉口设计模型。首先,考虑航路构型设计与航路运行主体,构建无人机运行所需的城市低空航路。其次,从进出口道、冲突响应距离2方面对空中交叉口几何结构进行设计,再从进口航道划分、通信信号管制、无人机高度调整3方面对交通组织进行设计,实现对空中交叉口的基本模型设计。最后,设置仿真实验验证该模型的可行性,并分析不同参数组合下的交叉口综合通行效率。实验结果表明:当飞行速度为18 m/s,纵向间隔为50 m,管制信号周期时长为226 s时,综合通行效率达到最佳。本研究可为未来城市空中交通航路网络精细划设与管理提供支撑,增强低空无人机交通的实践性。

基于任务优先权的军民航飞行活动协同排序模型

随着空域资源需求的不断增大,军民航间飞行矛盾日益突显。为解决此问题,本文以国务院、中央军事委员会空中交通管制委员会提出的“军民航空管联合运行”为背景,引入军民航共享空域的概念,重点研究了在此类空域中军民航飞行活动协同排序(CMFCS,civil-military aviation flight activity collaborative sequencing)问题。首先,基于军民航各自飞行任务特点与差异,对军民航飞行任务的种类进行划分,并使用层次分析法确定各类飞行任务的优先权原则;其次,以军民航飞行活动总延误时间成本最小为目标,建立CMFCS模型;最后,使用遗传算法对模型进行求解,确定军民航飞行活动批准进入共享空域的时间序列。研究结果表明,与经典的先到先服务(FCFS,first come first service)策略相比,协同排序策略得到的总延误时间成本降低了72.17%,优化效果显著且更符合实际,能够实现军民航共同使用国家空域资源,保障飞行活动安全、有序、高效地运行。