Dynamic optimization of airspace sector grouping

The current airspace configuration is highly structured, fixed and is less responsive to changes causing the overall system to lack the flexibility, adaptability, and responsibility needed to handle the increasing air traffic demands in the near future. The work presented in this thesis aims at improving the flexibility and adaptability of today's airspace management in Europe in a pretactical context. We focus on the development of a method to support a process of automatic generation of a sequence of sector configurations composed of predefined sectors. Airspace configurations should be dynamically adjusted to provide maximum efficiency and flexibility in response to demand fluctuations. We dynamically build configurations by combining existing elementary sectors. In this step, any sector combination which forms controllable airspace blocks is eligible and may be used during the day of operation. In this work, we developed efficient methods to solve DAC problem. We formulated and study the sectorization problem from an algorithmic point of view. We proposed methods based on a mathematical modeling and heuristic optimization techniques. We also introduced here an approach to evaluate the workload inside sectors

Existing and Required Modeling Capabilities for Evaluating ATM Systems and Concepts

ATM systems throughout the world are entering a period of major transition and change. The combination of important technological developments and of the globalization of the air transportation industry has necessitated a reexamination of some of the fundamental premises of existing Air Traffic Management (ATM) concepts. New ATM concepts have to be examined, concepts that may place more emphasis on: strategic traffic management; planning and control; partial decentralization of decision-making; and added reliance on the aircraft to carry out strategic ATM plans, with ground controllers confined primarily to a monitoring and supervisory role. 'Free Flight' is a case in point. In order to study, evaluate and validate such new concepts, the ATM community will have to rely heavily on models and computer-based tools/utilities, covering a wide range of issues and metrics related to safety, capacity and efficiency. The state of the art in such modeling support is adequate in some respects, but clearly deficient in others. It is the objective of this study to assist in: (1) assessing the strengths and weaknesses of existing fast-time models and tools for the study of ATM systems and concepts and (2) identifying and prioritizing the requirements for the development of additional modeling capabilities in the near future. A three-stage process has been followed to this purpose: 1. Through the analysis of two case studies involving future ATM system scenarios, as well as through expert assessment, modeling capabilities and supporting tools needed for testing and validating future ATM systems and concepts were identified and described. 2. Existing fast-time ATM models and support tools were reviewed and assessed with regard to the degree to which they offer the capabilities identified under Step 1. 3 . The findings of 1 and 2 were combined to draw conclusions about (1) the best capabilities currently existing, (2) the types of concept testing and validation that can be carried out reliably with such existing capabilities and (3) the currently unavailable modeling capabilities that should receive high priority for near-term research and development. It should be emphasized that the study is concerned only with the class of 'fast time' analytical and simulation models. 'Real time' models, that typically involve humans-in-the-loop, comprise another extensive class which is not addressed in this report. However, the relationship between some of the fast-time models reviewed and a few well-known real-time models is identified in several parts of this report and the potential benefits from the combined use of these two classes of models-a very important subject-are discussed in chapters 4 and 7

Enhanced air traffic flow and capacity management under trajectory based operations considering traffic complexity

Tesi amb menció internacional.(English) The Air Traffic Flow and Capacity Management (ATFCM) aims at maintaining the forecast traffic demand below the estimated capacity in airports and airspace sectors. The purpose is to maintain the workload of the air traffic controllers under safe limits and avoid overloaded situations. At present, the demand and the capacity management initiatives are deployed separately. Given a forecast traffic demand, the different air navigation service providers allocate their air traffic control resources providing the airspace sectorisations. Then, the network manager addresses the remaining overloads by allocating delay using the CASA algorithm based on a ration-by-schedule principle. It should be noted that some ad-hoc flights might be re-rerouted or limited in cruise altitude in order to avoid congested airspace by submitting a new flight plan. Hence, the previously chosen sectorisations may be not optimum once the demand management initiatives are deployed. Moreover, the flexibility of the airspace users is limited since they cannot express their preferences. Furthermore, the demand and the capacity are currently measured using entry counts as proxy of the air traffic control workload, which is rather easy to measure or estimate. Yet, this metric cannot evaluate the difficulty to handle different traffic patterns inside the sectors leading to the use of capacity buffers. This PhD focuses on overcoming the limitations of the current ATFCM system outlined before by the introduction of complexity metrics (instead of entry counts) in order to measure the traffic load, the better consideration of the airspace users preferences allowing the possibility of submitting alternative trajectories to avoid congested airspace, and the holistic integration of the demand and capacity management into the same optimisation problem. First, the integration of two capacity management initiatives, i.e. Dynamic Airspace Configuration (DAC) and Flight Centric ATC (FCA), is studied proving some benefits when such integration is dynamic. Next, a new concept of operation is proposed where the airspace users have the option of submitting alternative trajectories and the network manager is the responsible for the demand management (delay allocation and choice of the used trajectory) and the capacity management (selection of the airspace sectorisation), considering a network-wide optimisation. This concept of operations is mathematically modelled with two Demand and Capacity Balancing (DCB) models addressing only demand management and three holistic DCB models where the demand and the capacity management measures are considered together in the same optimisation problem. A first model aims at choosing the best trajectory and delay allocation per flight while analysing the traffic load with entry counts at traffic volume level. It is solved in a realistic case study using the historical regulations providing a 76.84% of reduction in the arrival delay if compared to the current system.(Català) La gestió dels fluxos de trànsit i de la capacitat (ATFCM) té com a objectiu mantenir la demanda de trànsit prevista per sota de la capacitat estimada dels aeroports i els sectors de l’espai aeri. Actualment, les iniciatives de gestió de la demanda i de gestió de la capacitat es duen a terme separadament. Donada una previsió de trànsit, els diferents proveïdors de serveis de navegació aèria assignen els seus recursos proporcionant les sectoritzacions de l’espai aeri. Després l’administrador de la xarxa tracta les sobrecàrregues restants mitjançant l’assignació de retards utilitzant l'algoritme CASA, basat en l'ordenació per ordre d’arribada. A alguns vols també se’ls pot canviar la ruta o se’ls pot restringit l’altitud del creuer per tal d’evitar zones congestionades requerint la presentació d’un nou pla de vol. Així doncs, les sectoritzacions prèviament escollides poden ser no òptimes una vegada s’implementin les iniciatives de gestió de la demanda. A més, la flexibilitat dels usuaris de l’espai aeri és limitada ja que no poden expressar les seves preferències. Altrament, la demanda i la capacitat es mesuren actualment comptant el nombre d’arribades com a proxy de la càrrega de treball del control del trànsit aeri. No obstant això, aquesta mètrica no pot evaluar la dificultat de gestionar diferents patrons de trànsit dins els sectors, la qual cosa condueix a la utilització de marges de capacitat. Aquest PhD es centra en superar les limitacions de l’actual sistema d’ATFCM indicades anteriorment mitjançant la introducció de mètrics de complexitat (en lloc del número d’arribades) per a mesurar el trànsit, la millor consideració de les preferències dels usuaris de l’espai aeri permetent la possibilitat d’utilitzar trajectories alternatives per a evitar la congestió de l’espai aeri, i la integració holística de la gestió de la demanda i de la capacitat en el mateix problema d’optimització. Primer, s’estudia la integració de dues iniciatives de gestió de la capacitat: DAC i FCA. S’obtenen beneficis quan la integració és dinàmica. Després, es proposa un nou concepte operacional on els usuaris de l’espai aeri tenen l'opció de proposar trajectories alternatives i l’administrador de la xarxa és el responsable de la gestió de la demanda (assignació de retards i elecció de la trajectòria utilitzada) i de la capacitat (selecció de la sectorització de l’espai aeri) considerant l’optimització de tota la xarxa. Aquest concepte operacional es formula amb dos models de DCB que aborden només la gestió de la demanda i tres models holístics on la gestió de la demanda i de la capacitat es consideren conjuntament en el mateix problema d’optimització. Un primer model es centra en escollir la millor trajectòria i assignació de retard per vol, mentre que el trànsit s'avalua mitjançant el número d’arribades als volums de trànsit. Es resol un cas d’estudi realista on s’utilitzen les regulacions històriques aconseguint un 76.84% menys de retard a l'arribada si es compara amb els sistema actual. Un dels tres models holístics de s’estudia en detall, en concret el que utilitza mètriques de complexitat i optimitza les sectoritzacions de l’espai aeri escollint entre un seguit de configuracions disponibles. Aquest model es tracta amb un nou mètode híbrid presentat en aquest PhD i que combina la simulació del recuit i la programació dinàmica. En un primer cas d'estudi, aquest nou mètode es compara amb el mètode exacte resolt amb Gurobi proporcionant un millor rendiment principalment quan la dificultat del problema augmenta. En un segon cas d’estudi es realitza un estudi de sensibilitat del paràmetre que modela una penalització per a diferents configuracions consecutives. Finalment, es resol un escenari a gran escala amb el mètode híbrid proporcionant un 74.01% menys de retard a l'arribada i un 28.47% menys en el cost de la sectorització resultant en comparació amb un escenari de referència que representa les millors condicions del sistema actual.(Español) La gestión de los flujos de tráfico y de la capacidad (ATFCM) pretende mantener la demanda de tráfico prevista por debajo de la capacidad estimada de los aeropuertos y los sectores del espacio aéreo. Actualmente, las iniciativas de gestión de la demanda y de la capacidad se implementan por separado. Ante una previsión de tráfico, los diferentes proveedores de servicios de navegación aérea asignan sus recursos proporcionando las sectorizaciones del espacio aéreo. Después, el administrador de la red trata las sobrecargas restantes mediante la asignación de retrasos utilizando el algoritmo CASA basado en un principio de ordenación por orden de llegada. A algunos vuelos también se les puede cambiar de ruta o limitar la altitud de crucero para evitar la congestión del espacio aéreo requiriendo de un nuevo plan de vuelo. Así pues, las sectorizaciones elegidas anteriormente pueden no ser óptimas una vez que se implementen las iniciativas de gestión de la demanda. Adicionalmente, la flexibilidad de los usuarios del espacio aéreo es limitada ya que no pueden expresar sus preferencias. Además, la demanda y la capacidad se miden actualmente contando el número de llegadas como proxy de la carga de trabajo del control del tráfico aéreo. Sin embargo, esta métrica no puede evaluar la dificultad de controlar diferentes patrones de tráfico dentro de los sectores lo que conduce al uso de márgenes de capacidad. Este PhD se centra en superar las limitaciones del sistema de ATFCM actual descritas anteriormente mediante la introducción de métricas de complejidad (en lugar del número de llegadas) para medir la carga de tráfico, la mejor consideración de las preferencias de los usuarios del espacio aéreo permitiendo la posibilidad de la presentación de trayectorias alternativas para evitar la congestión, y la integración holística de la gestión de la demanda y de la capacidad en un mismo problema de optimización. Primero, se estudia la integración de dos iniciativas de gestión de la capacidad, DAC y FCA, demostrando beneficios cuando dicha integración es dinámica. A continuación, se propone un nuevo concepto operacional donde los usuarios del espacio aéreo tienen la opción de presentar trayectorias alternativas y el administrador de la red es el responsable de la gestión de la demanda (asignación de retrasos y elección de la trayectoria utilizada) y la gestión de la capacidad (selección de la sectorización), considerando una optimización de toda la red. Este concepto operacional se modela con dos modelos de DCB que abordan sólo la gestión de la demanda y tres modelos holísticos donde las medidas de gestión de la demanda y de la capacidad se consideran conjuntamente en el mismo problema de optimización. Un primer modelo pretende elegir la mejor asignación de trayectoria y retraso por vuelo mientras se analiza la carga de tráfico con el número de llegadas a nivel de volumen de tráfico. Se resuelve un caso de estudio utilizando las regulaciones históricas proporcionando un 76.84% de reducción en el retraso en la llegada si se compara con el sistema actual. El model holístico que utiliza métricas de complejidad y optimiza las sectorizaciones del espacio aéreo escogiendo entre un conjunto de configuraciones disponibles se estudia en detalle. Este modelo se trata con un nuevo método híbrido basado en el recocido simulado y la programación dinámica. En un primer caso de estudio, se compara este nuevo método con el método exacto resuelto con Gurobi proporcionando un mejor rendimiento cuando aumenta la dificultad del problema. En un segundo caso de estudio se realiza un estudio de sensibilidad del parámetro que modela una penalización para diferentes configuraciones consecutivas. Finalmente, se resuelve un escenario a gran escala con el método Híbrido proporcionando menores valores de retraso en llegada y menores costes en la sectorización resultante en comparación con un escenario de referencia que representa las mejores condiciones del sistema actual.Postprint (published version

Risk Assessment in Air Traffic Management

One of the most complex challenges for the future of aviation is to ensure a safe integration of the expected air traffic demand. Air traffic is expected to almost double its current value in 20 years, which cannot be managed without the development and implementation of a safe air traffic management (ATM) system. In ATM, risk assessment is a crucial cornerstone to validate the operation of air traffic flows, airport processes, or navigation accuracy. This book tries to be a focal point and motivate further research by encompassing crosswise and widespread knowledge about this critical and exciting issue by bringing to light the different purposes and methods developed for risk assessment in ATM

Full Automation of Air Traffic Management in High Complexity Airspace

The thesis is that automation of en-route Air Traffic Management in high complexity airspace can be achieved with a combination of automated tactic planning in a look-ahead time horizon of up to two hours complemented with automated tactic conflict resolution functions. The literature review reveals that no significant results have yet been obtained and that full automation could be approached with a complementary integration of automated tactic resolutions AND planning. The focus shifts to ‘planning for capacity’ and ‘planning for resolution’ and also – but not only – for ‘resolution’. The work encompasses a theoretical part on planning, and several small scale studies of empirical, mathematical or simulated nature. The theoretical part of the thesis on planning under uncertainties attempts to conceive a theoretical model which abstracts specificities of planning in Air Traffic Management into a generic planning model. The resulting abstract model treats entities like the planner, the strategy, the plan and the actions, always considering the impact of uncertainties. The work innovates in specifying many links from the theory to the application in planning of air traffic management, and especially the new fields of tactical capacity management. The second main part of the thesis comprises smaller self-containing works on different aspects of the concept grouped into a section on complexity, another on tactic planning actions, and the last on planners. The produced studies are about empirical measures of conflicts and conflict densities to get a better understanding of the complexity of air traffic; studies on traffic organisation using tactical manoeuvres like speed control, lateral offset and tactical direct using fast time simulation; and studies on airspace design like sector optimisation, dynamic sectorisation and its optimisation using optimisation techniques. In conclusion it is believed that this work will contribute to further automation attempts especially by its innovative focus which is on planning, base on a theory of planning, and its findings already influence newer developments

Analysis of Airspace Traffic Structure and Air Traffic Control Techniques

Air traffic controller cognitive processes are a limiting factor in providing safe and efficient flow of traffic. Therefore, there has been work in understanding the factors that drive controllers decision-making processes. Prior work has identified that the airspace structure, defined by the reference elements, procedural elements and pattern elements of the traffic, is important for abstraction and management of the traffic. This work explores in more detail this relationship between airspace structure and air traffic controller management techniques. This work looks at the current National Airspace System (NAS) and identifies different types of high altitude sectors, based on metrics that are likely to correlate with tasks that controllers have to perform. Variations of structural patterns, such as flows and critical points were also observed. These patterns were then related to groupings by origins and destinations of the traffic. Deeper pilot-controller voice communication analysis indicated that groupings by flight plan received consistent and repeatable sequences of commands, which were identified as techniques. These repeated modifications generated patterns in the traffic, which were naturally associated with the standard flight plan groupings and their techniques. The identified relationship between flight plan groupings and management techniques helps to validate the grouping structure-base abstraction introduced by Histon and Hansman (2008). This motivates the adoption of a grouping-focused analysis of traffic structures on the investigation of how new technologies, procedures and concepts of operations will impact the way controllers manage the traffic. Consideration of such mutual effects between structure and controllers' cognitive processes should provide a better foundation for training and for engineering decisions that include a human-centered perspective.This work was financially supported by FAA grant 06-G-006 and NASA Cooperative Agreement NN06CN23A. Anton Koros and Eddie Sierra were the technical sponsors and provided valuable feedback and assistance

Optimization for Decision Making II

In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner

On the generation of environmentally efficient flight trajectories

To achieve a sustainable future for air transport, the International Civil Aviation Organization has proposed goals for reductions in community noise impact, local air quality and climate impacting emissions. The goals are intended to be achieved through advances in engine design, aircraft design and through improvements in aircraft operational procedures. This thesis focuses on operational procedures, and considers how trajectory generation methods can be used to support flight and airspace planners in the planning and delivery of environmentally efficient flight operations. The problem of planning environmentally efficient trajectories is treated as an optimal control problem that is solved through the application of a direct method of trajectory optimisation combined with a stochastic Non Linear Programming (NLP) solver. Solving the problem in this manner allows decision makers to explore the relationships between how aircraft are operated and the consequent environmental impacts of the flights. In particular, this thesis describes a multi-objective optimisation methodology intended to support the planning of environmentally efficient climb and descent procedures. The method combines environmental, trajectory and NLP methods to generate Pareto fronts between several competing objectives. It is shown how Pareto front information can then be used to allow decision makers to make informed decisions about potential tradeoffs between different environmental goals. The method is demonstrated through its application to a number of real world, many objective procedure optimisation studies. The method is shown to support in depth analysis of the case study problems and was used to identify best balance procedure characteristics and procedures in an objective, data driven approach not achievable through existing methods. Driven by operator specific goals to reduce CO2 emissions, work in this thesis also looks at trajectory based flight planning of CO2 efficient trajectories. The results are used to better understand the impacts of ATM constraints and recommended procedures on both the energy management and fuel efficiency of flights. Further to this, it is shown how trajectory optimisation methods can be applied to the analysis of conventional assumptions on fuel efficient aircraft operations. While the work within is intended to be directly relevant to the current air traffic management system, both consideration and discussion is given over to the evolution and continued relevance of the work to the Single European Sky trajectory based concept of operation

CONFLICT RESOLUTION AND TRAFFIC COMPLEXITY OF MULTIPLE INTERSECTING FLOWS OF AIRCRAFT

This paper proposes a general framework to study conflict resolution for multiple intersecting flows of aircraft in a planar airspace.The conflict resolution problem is decomposed into a sequence of sub-problems each involving only two intersecting flows of aircraft.The strategy for achieving the decomposition is to displace the aircraft flows so that they intersect in pairs, instead of all at once, and so that the resulting conflict zones have no overlap.A conflict zone is defined as a circular area centered at the intersection of a pair of flows which allows aircraft approaching the intersection to resolve conflict completely within the conflict zone, without straying outside.An optimization problem is then formulated to displace the aircraft flows in a way that keeps airspace demand as low as possible.Although this optimization problem is difficult to solve in general due to its non-convex nature, a closed-form solution can be obtained for three intersecting flows.The metric used for the airspace demand is the radius of the smallest circular region (control space) encompassing all of the non-overlapping conflict zones.This radius can also be used as an indication of traffic complexity for multiple intersecting flows of aircraft.It is shown that the growth of the demand for control-space radius is of the fourth order against the number of intersecting flows of aircraft in a symmetric configuration

Analysis of airspace traffic structure and air traffic control techniques

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 157-163).Air traffic controller cognitive processes are a limiting factor in providing safe and efficient flow of traffic. Therefore, there has been work in understanding the factors that drive controllers decision-making processes. Prior work has identified that the airspace structure, defined by the reference elements, procedural elements and pattern elements of the traffic, is important for abstraction and management of the traffic. This work explores in more detail this relationship between airspace structure and air traffic controller management techniques. This work looks at the current National Airspace System (NAS) and identifies different types of high altitude sectors, based on metrics that are likely to correlate with tasks that controllers have to perform. Variations of structural patterns, such as flows and critical points were also observed. These patterns were then related to groupings by origins and destinations of the traffic. Deeper pilot-controller voice communication analysis indicated that groupings by flight plan received consistent and repeatable sequences of commands, which were identified as techniques. These repeated modifications generated patterns in the traffic, which were naturally associated with the standard flight plan groupings and their techniques. The identified relationship between flight plan groupings and management techniques helps to validate the grouping structure-base abstraction introduced by Histon and Hansman (2008). This motivates the adoption of a grouping-focused analysis of traffic structures on the investigation of how new technologies, procedures and concepts of operations will impact the way controllers manage the traffic. Consideration of such mutual effects between structure and controllers' cognitive processes should provide a better foundation for training and for engineering decisions that include a human-centered perspective.by Emilio Alverne Falcão de Albuquerque Filho.S.M