A PERFORMANCE-BASED APPROACH TO AIRSPACE OPTIMIZATION USING WIND-OPTIMAL TRACKS NETWORK IN HO CHI MINH FIR

An Agent-Based Approach to Aircraft Conflict Resolution with Constraints

As it is defined in ATM 2000+ Strategy (Eurocontrol 2001), the mission of the Air Traffic Management (ATM) System is: “For all the phases of a flight, the ATM system should facilitate a safe, efficient, and expedite traffic flow, through the provision of adaptable ATM services that can be dimensioned in relation to the requirements of all the users and areas of the European air space. The ATM services should comply with the demand, be compatible, operate under uniform principles, respect the environment and satisfy the national security requirements.” The objective of this paper is to present a methodology designed to evaluate the status of the ATM system in terms of the relationship between the offered capacity and traffic demand, identifying weakness areas and proposing solutions. The first part of the methodology relates to the characterization and evaluation of the current system, while a second part proposes an approach to analyze the possible development limit. As part of the work, general criteria are established to define the framework in which the analysis and diagnostic methodology presented is placed. They are: the use of Air Traffic Control (ATC) sectors as analysis unit, the presence of network effects, the tactical focus, the relative character of the analysis, objectivity and a high level assessment that allows assumptions on the human and Communications, Navigation and Surveillance (CNS) elements, considered as the typical high density air traffic resources. The steps followed by the methodology start with the definition of indicators and metrics, like the nominal criticality or the nominal efficiency of a sector; scenario characterization where the necessary data is collected; network effects analysis to study the relations among the constitutive elements of the ATC system; diagnostic by means of the “System Status Diagram”; analytical study of the ATC system development limit; and finally, formulation of conclusions and proposal for improvement. This methodology was employed by Aena (Spanish Airports Manager and Air Navigation Service Provider) and INECO (Spanish Transport Engineering Company) in the analysis of the Spanish ATM System in the frame of the Spanish airspace capacity sustainability program, although it could be applied elsewhere.

The increasing demand in air transportation is pushing the current air traffic management (ATM) system to its limits in the airspace capacity and workload of air traffic controllers (ATCOs). ATCOs are in an urgent need of assistant tools to aid them in dealing with increased traffic. To address this issue, the application of artificial intelligence (AI) in supporting ATCOs is a promising approach. In this work, we build an AI system as a digital assistant to support ATCOs in resolving potential conflicts. Our system consists of two core components: an intelligent interactive conflict solver (iCS) to acquire ATCOs' preferences, and an AI agent based on reinforcement learning to suggest conflict resolutions capturing those preferences. We observe that providing the AI agent with the human resolutions, which are acquired and characterized by our intelligent interactive conflicts solver, not only improves the agent's performance but also gives it the capability to suggest more human-like resolutions, which could help increase the ATCOs' acceptance rate of the agent's suggested resolutions. Our system could be further developed as personalized digital assistants of ACTOs to maintain their workloads manageable when they have to deal with sectors with increased traffic.

The increase in civil aviation traffic and, in general, in aviation traffic going through airspace or a military terminal control area, and the increase in military operations in temporarily reserved areas bring higher requirements for airspace throughput and for the workload of military air traffic controllers. For an objective assessment of the military air traffic controllers’ workload, it is desirable to set the maximum level of workload that can be required of such personnel. This assessment is also important for planning staffing and training. In the civil air traffic control environment, the workload of air traffic controllers is clearly determined by the complexity and density of air traffic, i.e., the throughput capacity of sectors. However, this method is not suitable for measuring the workload of military air traffic controllers, because the nature of military flight activities requires solving different situations in the airspace and thus generates a different workload. One way of obtaining more objective data on the actual workload of military air traffic controllers is to accurately determine the difficulty of individual air traffic control activities, i.e., the most common activities carried out by military air traffic controllers in the course of their duty. The difficulty of a selected air traffic control activity will be represented by a weight. A method for determining this weight is presented, including the proposal of specific weights for the calculation of the military air traffic controllers’ workload during simulation training, using the functionality “Workload”.

The issue of application of Air Traffic Control (ATC) competence reference models as a mean of air navigation services provider’s charge optimization is described in the article, and this issue is interpretated as an optimization task. The data relating to the significant growth of aviation traffic, especially using the airspace of Ukraine, given by authors, and the statement of fact that Air Traffic Management (ATM) system’s technical component reliability increasement takes place on the basis of practically invariable psychophysiological abilities of aviation controller, make the substantiation of ANSP provision with the most trained ATC controllers for the work on the working places of ATC Unit actual. The ‘mechanism’ of ATC controllers competence reference model creation is defined step-by step. There is an example of candidate’s for the working place competence quantitative individual model forming as a common criteria of competence, which, in its turn, is the compressed format of all parameters of its working activity, received at the stage of control. The approach, according to which the individual parameters of graduating student’s output model’s professional characteristics, which he received after the examination of his work as Tower controller (ATM Unit of aerodrome control service), approach controller or area control service controller, are compared with the predetermined specialist’s competence reference model, relating to the special working place in ATM system, is supposed here. Notably, the conception, relating to the correspondence of the graduating student’s competence output level to the defined reference model of ATC controller, relating to the special working place of ATM Unit, is realised.

This paper presents Multi Objective Trajectory Optimization (MOTO) algorithms that were developed for integration in state-of-the-art Air Traffic Management (ATM) and Air Traffic Flow Management (ATFM) systems. The MOTO algorithms are conceived for the automation-assisted replanning of 4-Dimensional Trajectories (4DT) when unforeseen perturbations arise at strategic and tactical online operational timeframes. The MOTO algorithms take into account updated weather and neighbouring traffic data, as well as the related forecasts from selected sources. Multiple user-defined operational, economic and environmental objectives can be integrated as necessary. Two different MOTO algorithms are developed for future implementation in ATM systems: an en-route variant and a Terminal Manoeuvring Area (TMA) variant. In particular, the automated optimal 4DT replanning algorithm for en-route airspace operations is restricted to constant flight level to avoid violating the current vertical airspace structure. As such, the complexity of the generated trajectories reduces to 2 dimensions plus time (2D+T), which are optimally represented in the present 2D ATM display formats. Departing traffic operations will also significantly benefit from MOTO-4D by enabling steep/continuous climb operations with optimal throttle, reducing perceived noise and gaseous emissions.

This chapter reviews the International Civil Aviation Organization air traffic management (ATM) work programme along with ATM developments taking place around the world. It examines the various elements of the ATM system and suggests some of die research, trials and demonstrations. Airspace management is traditionally recognized mainly as involving a dynamic or tactical sharing of airspace by civil and military users. Air Traffic Services itself is comprised of several subelements, one of these being air traffic control. The increasing number of long-range interregional flights may require integration of regional Air Traffic Flow Management systems and procedures. Free Right is the guiding vision, mission and operational concept of the Federal Aviation Administration, based on Communications, Navigation, Surveillance/Air Traffic Management systems (CNS/ATM). Africa is composed of many delicate national economies separated by vast wilderness areas. The main scope of Airspace management will be toward a strategic planning function of airspace infrastructure, and flexibility of airspace use.

The exponential growth of global air travel has presented significant challenges to air traffic management systems (ATMS), including airspace congestion, flight delays, fuel inefficiency, and safety risks. Traditional ATMS are increasingly inadequate to handle these complexities. This study explores how imaging, computer vision (CV), and deep learning technologies have been employed to implement an intelligent ATMS. It aims at improving operational efficiency, safety, and scalability. AI techniques such as deep learning along with imaging and CV technologies like satellite imagery (SI), radar data, and real-time video feeds, the proposed system enhances situational awareness, predicts flight trajectories, and automates decision-making processes. The framework enables real-time monitoring, anomaly detection, and conflict resolution, addressing critical challenges such as airspace congestion, unmanned aerial vehicle (UAV) integration, and environmental concerns. Simulation-based analyses demonstrate the system's ability to improve operational efficiency, reduce fuel consumption, and enhance airspace safety, achieving high accuracy, precision, and recall rates. The findings highlight the potential of AI-driven ATMS to revolutionize air traffic management (ATM), contributing to global aviation sustainability, enhancing airspace safety, and optimizing resource utilization. Despite some limitations, such as data quality and scalability, the proposed system offers a promising solution for future air traffic control, with implications for operational efficiency, cost reduction, and societal benefits. Future research can further explore system scalability, real-world testing, and ethical considerations in AI-driven aviation management.

Air traffic management (ATM) systems and their components—planning the use of air-space and air traffic control systems—are among the most complex modern systems that cannot be introduced without a large amount of preliminary research. Tools for the simulation of the procedures of air traffic management and control used in Europe and the USA are considered. The importance of simulation is caused by the fundamental modernization of the principles and methods of control, which requires anticipatory research. The field of application of the Russian simulation tool for ATM systems called KIM OrVD is determined. This tool is used by the Russian ATM State Corporation. Examples of using this tool for working out proposals concerning the improvements in the Russian ATM system and the evaluation of the efficiency of such proposals are discussed.

The main objective of this paper is to present our vision of the role of automation in future air traffic management (ATM) system. It also includes an analysis and state of the art on ATM and automation. The content is based on HALA! position paper, that looks beyond the framework defined by SESAR and NextGen for the near future, and analyses the feasibility of higher levels of automation in ATM in the far future, taking into account the relationship between humans, organizations, and machines and scoping the allocation of functions, roles, and tasks between them. Taking into consideration the proposed SESAR&NextGen paradigm shift (trajectory-based operations; proactive, more distributed and autonomous system) and studies developed in ATM automation in the past years, the vision goes toward a more ATM automation system operation questioning even the possibility of fully automated ATM system. The understanding of higher levels of automation in ATM considers the “overall system performance” as main driver for the resulting “optimal” ATM level of automation. Implementation of above programs will change the human role in the future ATM system. In this regard, the vision considers ATM as sociotechnical system and orchestrated organization, overcoming the former consequences of automation, where some “human errors” caused from automation were found, to this new vision where human motivation for their engagement in the ATM activities, will be promoted. New roles between humans, organizations, and between them and machines will be derived by considering ATM as a complex sociotechnical multi-agent system. Under this assumption, it will be essential: to maintain a high degree of autonomy among different ATM agents and, simultaneously, an optimized level of orchestration among them. Three interdependent criteria to support the always controversial decision about where to dynamically allocate the ATM essential functions/tasks are proposed; when is the “best time” to take an operational action, where is the “best place” having the best picture to take it and, finally, who will be the “best player” to implement the associated tasks. As a result, the paper advocates for a different role of automation devoted to support a temporal, institutional, and physical distributed ATM system. It is also pointed out that research in ATM automation should always take under consideration the adequate level of automation in the far future ATM system and should always ensure the safety and reliability of a highly automated ATM system. Finally considers the need to align the research efforts into two different main activities of improvement, devoted to: aircraft trajectory hierarchal, spatial, and temporal cohesion and trajectory management.

The aviation industry faces a rapidly-emerging need for integrating Unmanned Air Systems (UAS) into the national airspace (NAS). This trend will present challenging questions for the safe operation of UAS in controlled and uncontrolled airspaces based on new Communications, Navigation and Surveillance (CNS) technologies. For example, can wireless communications data links provide the necessary capacity for accommodating ever increasing numbers of UAS worldwide? Does the communications network provide ample Internet Protocol (IP) address space to allow Air Traffic Control (ATC) to securely address each UAS? Can navigation and surveillance approaches assure safe route planning and safe separation of vehicles even in crowded skies? Under NASA contract NNA16BD84C, Boeing is developing an integrated CNS architecture to enable UAS operations in the NAS. Revolutionary and advanced CNS alternatives are needed to support UAS operations at all altitudes and in all airspaces, including both controlled and uncontrolled. These CNS alternatives must be reliable, redundant, always available, cyber-secure, and affordable for all types of vehicles including small UAS to large transport category aircraft. Our approach considers CNS requirements that address the range of UAS missions where they will be most beneficial and cost-effective. A cybersecure future UAS CNS architecture is needed to support the NASA vision for an Unmanned Air Traffic Management (UTM) system in uncontrolled airspace and a cooperative operation of manned and unmanned aircraft in the controlled global Air Traffic Management (ATM) system. The architecture must, therefore, support always-available and cyber secure operations. This paper presents UAS CNS architecture concepts for large UAS operating in the ATM system in controlled airspace. Future companion works will consider small UAS operating in the UTM system in uncontrolled airspace.

Understanding the research on air traffic controller workload and its implications for safety: A science mapping-based analysis

Air Traffic Management (ATM) systems are one of the key element of critical for flight safety infrastructure. Among ATM systems communications play a special role as a vital part in information exchange between air traffic controllers and pilots, especially in hazardous situations. In the modern ATM systems each controller has independent direct communication channel with separate radio frequency. For reliability increasing of such ATM communication channels the redundancy with common set of standby radio stations is used. Traditionally, maintenance is additional tool to increase the efficiency of radio stations operation. This paper examines the effectiveness of the ATM communication channels with the simultaneous using both of the above methods—redundancy and periodic maintenance of radio stations. Mathematical model of the channel reliability for this case is developed.

The existing Air Traffic Management (ATM) system can evolve into a Space and Air Traffic Management System (SATMS), as space operations become a more common event. An assessment tool has been developed as a catalyst for this evolution; the Dynamic Flight Path Tool was developed to utilize real time situational information to minimize the impact of space flight to operations while at the same time ensuring a level of safety acceptable to the public. This tool capitalizes on methods that rapidly compute the debris clouds within a four-dimensional space (3D space plus time). The tool has two modes of operation: 1) Pre- mission Planning and 2) Real-time Mission Mode. The Dynamic Flight Path Tool has been applied to a range of sample scenarios that demonstrate how the impact of space launch operations on air traffic can be significantly reduced. 1 . An assessment tool has been developed as a catalyst for this evolution; the Dynamic Flight Path Tool, a Research and Development prototype, was developed to utilize real time situational information to minimize the impact of space flight to operations while at the same time ensuring a level of safety acceptable to the public. This tool capitalizes on methods that rapidly compute the debris clouds within a four-dimensional space (3D space plus time). The tool has two modes of operation: 1. Pre-mission Planning. The Tool enables the planner to identify scheduled air traffic affected by a planned operation and potentially schedule a launch operation during the time of lowest air traffic density and thus, lowest overall risk and disruption. 2. Real-time Mission Mode. The Tool performs trajectory prediction to identify what air traffic will enter the operational area of interest. The Tool provides the Flight Safety Officer (FSO) and Air Traffic Control (ATC) with situational awareness information on the space and air traffic. This allows the FSO and ATC to dynamically manage the airspace as the launch operation progresses, as opposed to issuing a blanket NOTAM (Notice to Airmen) restricting a large area of airspace. The Dynamic Flight Path Tool has been applied to a range of sample scenarios that demonstrate how the impact of space launch operations on air traffic can be significantly reduced. While destruct events are very rare and the vast majority of launch operations are nominal, the dynamic understanding of the space and air traffic picture between the FSO and ATC facilitated by the Dynamic Flight Path Tool gives all users of the airspace considerably more flexibility in managing the needs of their respective airspace users while guaranteeing an acceptable level of safety. Presently the Federal Aviation Administration (FAA) considers the risk to flying and not how to respond to the real time situation that exists during a space launch. The FAA follows its strategic planning and does not formulate contingency plans - rather it relies on tactically moving aircraft - to account for the actual location of

The air transport market has a strategic character, promotes economic and social development, and has a strong correlation with the level of economic activity. The Air Traffic Management (ATM) system plays an essential role in air transportation and can be characterized as a sociotechnical system that is too complex to research through classical approaches such as systems engineering. In this sense, the application of Complex Network Theory (CNT) analysis and modeling paradigms is driven by the need to accommodate the growth of air traffic within an already saturated ATM infrastructure. The present work describes the development of a resilience evaluation model of ATM systems based on CNT, its metrics and analysis tools. The model was applied to the Brazilian ATM system, demonstrating its usefulness in identifying the air traffic control (ATC) agencies that have the greatest influence on the network. The results also showed that the Brazilian ATM network is resilient to random failures; however, it is particularly vulnerable to targeted attacks to the ATC agencies with the highest centrality. The research findings can be applied to prioritize the deployment of systems and equipment that enhance the resilience and operability of the Brazilian ATM system.