Increasing Air Traffic: What is the Problem?

An Agent-Based Approach to Aircraft Conflict Resolution with Constraints

This paper describes a simulation tool developed to aid the analysis of air traffic management domains and potential air traffic control strategies. The simulation represents aircraft and automated air traffic control support tool functionality based on a computational model of aircraft flight management system trajectories. It simulates the effects of environmental disturbances and air traffic controller intervention on air traffic in fast time. The paper outlines a methodology that leverages these capabilities to help with tool design and evaluation, and discusses the results of preliminary simulations aimed toward using the proposed methodology for characterizing the effectiveness of particular strategy-tool combinations for supporting more efficient terminal-area air traffic management. This research is supported by NASA's Vehicle Systems Program Quiet Aircraft Technology project and Airspace Systems Program Advanced Air Transportation Technology project.

Decision support system in tactical air traffic flow management for air traffic flow controllers

This paper/chapter deals with the key drivers for adopting and developing an Occupational Health and Safety System (OHS) with a special focus on air traffic management and traffic controller’s workplace. A such system includes regulation and legal compliance procedures, actions and monitoring for ensuring workplace safety, incentives and motivation for the air traffic controller and associate personnel health and wellbeing. By a systemic approach, the key characteristics of OHS towards air traffic management are presented, highlighting the key aspects for implementing a quality management system in air traffic control, which is the cornerstone of airport operation efficiency and productivity on one hand; and the nature of job and the intensive working environment is well recognised. Based on air traffic providers functional analysis the key occupational aspects for air traffic control are taken into consideration, providing the benefits for implementing quality management systems (QMS) and OHS is real business. Conventional wisdom is to highlight the importance for establishing and incorporating a modern custom-made OHS system in accordance with the requirements addressed by OHSAS 18001 to develop and implement a QMS for air traffic services. Contribution of this paper is to highlight the key priorities for managers and decision makers in field of air traffic services providers, depicting ways and recommendation for adopting an efficient path for implementing OHS in a QMS environment.

The paper deals with the diagnosis and development of core skills of air traffic (AT) controllers based on a professiogram analysis of their work. The aim was to assess how professional skills are related to experience and to explore the opportunities of purposeful training of these skills. The study was conducted with the participation of air traffic (AT) controllers who were graduates of an ATC school aged 22–25 years and had no experience and eleven first-class operators aged 31–37 years with eight to ten years of experience. The professiogram analysis of work was carried out using a specially crafted skill tests battery followed by training (ten sessions during ten school days) for inexperienced air traffic controllers, which was tied up to regular refresher training. The study pinpointed the core skills that were improved significantly by the special training and proved the possibility of their development using a training cycle during planned teaching.

Застосування адаптивних навчальних систем є напрямом вдосконалення навчальної діяльності диспетчерів управління повітряним рухом, зокрема на тренажерах. Доведено, що адаптивне навчання, яке включає штучний інтелект та гнучкі механізми формування індивідуально-адаптованих вправ, підвищує ефективність навчання порівняно з традиційним навчанням. Крім того, застосування адаптивного навчання дозволяє заощадити на витратах на професійну підготовку авіадиспетчерів за рахунок скорочення часу її проведення без зниження її ефективності. Процес адаптації складається з трьох етапів: вилучення інформації про користувача, обробка інформації для ініціалізації та оновлення моделі користувача і використання моделі користувача для забезпечення адаптації. Однією з головних проблем існуючих досліджень в сфері інтелектуальних навчальних систем є те, що в них не в повній мірі досліджено питання формування індивідуальних стратегій діяльності авіадиспетчерів на рівні моделей і алгоритмів для забезпечення ефективного зворотного зв’язку на протязі всіх етапів їх професійної підготовки. В існуючих тренажерних системах обслуговування повітряного руху не реалізовано завдання корекції навчальної діяльності. У статті розглянуті можливості формування адаптивного характеру і напрямку навчання в вигляді індивідуальних стратегій діяльності за допомогою структурованої множини режимів навчання, типових помилок за відповідними критеріями оцінки та окремих дій. Подальшими напрямами дослідження можна вважати визначення вагових коефіцієнтів важливості кожної помилки за відповідним критерієм оцінки та вагові коефіцієнти складності окремих дій. Розробка механізмів спостереження та аналізу сукупності помилок та їх причин.

Предметом вивчення в статті є методи, що дозволяють вирішити проблему невизначеності в процесі побудови систем підтримки прийняття рішень авіадиспетчера при виникненні особливих випадків в польоті. Метою є аналіз і обґрунтування вибору математичного апарату для побудови СППР авіадиспетчера. Завдання: аналіз ряду відомих методів інтелектуального аналізу даних, а саме: еволюційних алгоритмів, нейронних мереж, нечіткої логіки та байєсівських мереж з точки зору доцільності їх застосування при побудови систем підтримки прийняття рішень авіадиспетчера управління повітряним рухом при виникненні особливих випадків в польоті. Використовуваними методами є: методи аналізу і синтезу складних інформаційних систем, методи імітаційно-статистичного моделювання. Отримано такі результати. В результаті проведеного аналізу було встановлено, для побудови моделі СППР авіадиспетчера найбільш ефективним є використання апарату байєсівських мереж, який представляє собою перспективний ймовірнісний інструментарій, що дозволяє моделювати складні ієрархічні статичні та динамічні системи. Це обумовлено тим, що на відміну від популярних на даний час моделей "чорних скриньок" байєсівська мережа дозволяє отримати зрозуміле пояснення одержаних висновків, має їх логічну інтерпретацію, надає можливість врахування невизначеностей параметричного, статичного і структурного характеру і, що є особливо важливим, ґрунтується на фундаментальних положеннях теорії ймовірностей, яка розроблялась не одне сторіччя. Висновки. Напрямком подальших досліджень є побудова системи підтримки прийняття рішень авіадиспетчера з використанням байєсівських мереж і технології ймовірнісного програмування

Based on a long-term prediction by the International Civil Aviation Organization indicating steady increases in air traffic demand throughout the world, the workloads of air traffic controllers are expected to continuously increase. Air traffic control and management (ATC/M) includes the processing of various unstructured composite data along with the real-time visualization of aircraft data. To prepare for future air traffic, research and development intended to effectively present various complex navigation data to air traffic controllers is necessary. This paper presents a mixed reality-based air traffic control system for the improvement of and support for air traffic controllers’ workflow using mixed reality technology that is effective for the delivery of information such as complex navigation data. The existing control systems involve difficulties in information access and interpretation. Therefore, taking notice of the necessity for the integration of air traffic control systems, this study presents the mixed reality (MR) system, which is a new approach, that enables the control of air traffic in interactive environments. This system is provided in a form usable in actual operational environments with a head-mounted see-through display installed with a controller to enable more structured work support. In addition, since this system can be controlled first-hand by air traffic controllers, it provides a new experience through improved work efficiency and productivity.

An Eulerian network model for air traffic flow in the National Airspace System is developed and used to design flow control schemes which could be used by Air Traffic Controllers to optimize traffic flow. The model relies on a modified version of the Lighthill-Whitham-Richards (LWR) partial differential equation (PDE), which contains a velocity control term inside the divergence operator. This PDE can be related to aircraft count, which is a key metric in air traffic control. An analytical solution to the LWR PDE is constructed for a benchmark problem, to assess the gridsize required to compute a numerical solution at a prescribed accuracy. The Jameson-Schmidt-Turkel (JST) scheme is selected among other numerical schemes to perform simulations, and evidence of numerical convergence is assessed against this analytical solution. Linear numerical schemes are discarded because of their poor performance. The model is validated against actual air traffic data (ETMS data), by showing that the Eulerian description enables good aircraft count predictions, provided a good choice of numerical parameters is made. This model is then embedded as the key constraint in an optimization problem, that of maximizing the throughput at a destination airport while maintaining aircraft density below a legal threshold in a set of sectors of the airspace. The optimization problem is solved by constructing the adjoint problem of the linearized network control problem, which provides an explicit formula for the gradient. Constraints are enforced using a logarithmic barrier. Simulations of actual air traffic data and control scenarios involving several airports between Chicago and the U.S. East Coast demonstrate the feasibility of the method.

Adapting a Human – Automation Trust Scale to an Air Traffic Management Environment

The National Aeronautics and Space Administration (NASA) is conducting far-term research into a proposed concept for gate-to-gate national airspace system (NAS) operations called Distributed Air/Ground Traffic Management (DAG-TM) in which flight deck crews, air traffic service providers and aeronautical operational control facilities use distributed decision-making. In this study we estimate the benefits of En Route Free Maneuvering and En Route Trajectory Negotiation in off-nominal conditions using empirical data. Specifically, the benefits we measure are the avoided disruption costs under inclement weather conditions due to the implementation of the two en route concept elements. The random nature of inclement weather makes the measurement of its impact on aviation a challenge. Since June 2003, the Department of Transportation's Airline Service Quality Performance (ASQP) data reports the major airlines' schedule/operation disruptions, in terms of flight cancellations, delays, and diversions, allocated to five cause categories, including extreme weather and non-extreme weather conditions. We extract the inclement weather- caused disruptions from the one-year period of July 2003 through June 2004 from the ASQP data. In developing the benefits pool, we recognize that these two concept elements' functionalities and capabilities could not eliminate all disruptions caused by weather conditions. We estimate the percentage of weather caused disruptions that can be helped by the two concept elements based on expert opinion. We estimate the NAS-wide benefits for year 2004 by extending the ASQP results to the non-ASQP carriers via linear extrapolation. We also extrapolate current NAS benefits to the projected benefits in year 2015, the target year of DAG-TM deployment, by developing and applying forecast parameters to year 2004 benefits based on the traffic forecast. Finally, we translate the operational performance benefits of reduced delay and avoided diversions/cancellations into economic benefits using FAA and other published cost factors. I. Introduction HE National Aeronautics and Space Administration (NASA) is conducting far-term research into a proposed concept for gate-to-gate national airspace system (NAS) operations called Distributed Air/Ground Traffic Management (DAG-TM). DAG-TM is based on distributed decision making between flight deck crews, air traffic service providers (ATSP) and aeronautical operational control (AOC) personnel. The goal of DAG-TM is to increase system capacity/throughput, enable user preferences, and provide greater flexibility and efficiency, while meeting air traffic management (ATM) requirements and maintaining system safety and user accessibility to the NAS. DAG-TM will be accomplished with a human-centered operational paradigm enabled by procedural and technological innovations. These innovations include automation aids, information sharing and Communication, Navigation, and Surveillance (CNS) / ATM technologies. The total DAG-TM concept is intended to address all user classes (commercial carriers, general aviation, etc.) with an emphasis towards ensuring access to airspace resources

This study focuses on improving the air traffic control and management of local airspace in China. We develop five modules to establish a decision-support system, which constitutes the analysis and strategy layer of a local airspace digital twin. This integrated solution utilizes multi-source multimodal data, ranging from flight status, weather, to real-time air traffic control strategies. Specifically, the first module reviews the operational performance of the airspace and assesses the maximum capacity of an airspace under particular weather scenarios. The second module forecasts the departure times of all incoming flights to inform potential congestion. The third module is the core module simulating the local airspace operation under given weather conditions and control strategies. In the fourth module, we compare the simulation results with the assessed capacities, and suggest adjustments to control strategies proposed by air traffic controllers. The fifth module applies mixed integer programming to obtain the optimal air traffic control strategies.

Facing flight centred air traffic control (ATC) and more monitoring tasks at future controller working positions (CWP), it becomes even more important that air traffic controllers (ATCo) always focus their attention at the relevant spots on their human machine interface (HMI). This paper outlines relevant literature about attention and attention guidance (AG) in different domains, explains the concept for an AG prototype for sectorless air traffic management (ATM) and the plan for its validation in the course of Single European Sky ATM Research (PJ.16-04-03, SESAR2020). The AG prototype considers three aspects. First, the desired area of attention: An assistance system calculates where the ATCo should look at depending on input data like radar and flight plan data. Second, an external system relying on eye tracking and user inputs determines where the current ATCo focus is. Third, if the desired and the actual area of attention are not the same, mechanisms to guide the ATCo’s attention will be triggered taking a strategy of escalating visual cues into account. The latter comprises an intelligent display of action indicators with respect to time, position and appearance as well as pre-tactical inattention indicators. The AG prototype aims to increase controller productivity, improve situation awareness as well as reduce workload and stress level in a future flight centred ATC environment.

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 light signals play a vital role in the management of traffic systems. They are the key component of traffic control systems, which properly channelize the traffic flow. Therefore, the area of air traffic control (ATC) signals also becomes critical concerning the movement of airplanes because a failure in ATC light signal could cause the loss of human life and financial disasters. The air traffic control is a safety critical system and failure in such systems is not affordable. In this paper we have developed the formal model of ATC light signals where different light signals of the model are formally specified using Z-notation. Our proposed model ensures the correspondence between the functional behavior of the light signal communication system and its functional requirements. Moreover, the system also becomes important due to its uniqueness since it has an extra number of control signal combinations as compared to ordinary signal systems.