MODELS AND SOLUTION ALGORITHMS FOR EQUITABLE RESOURCE ALLOCATION IN AIR TRAFFIC FLOW MANAGEMENT

Population growth and economic development lead to increasing demand for travel and pose mobility challenges on capacity-limited air traffic networks. The U.S. National Airspace System (NAS) has been operated near the capacity, and air traffic congestion is expected to remain as a top concern for the related system operators, passengers and airlines. This dissertation develops a number of model reformulations and efficient solution algorithms to address resource allocation problems in air traffic flow management, while explicitly accounting for equitable objectives in order to encourage further collaborations by different stakeholders. This dissertation first develops a bi-criteria optimization model to offload excess demand from different competing airlines in the congested airspace when the predicted traffic demand is higher than available capacity. Computationally efficient network flow models with side constraints are developed and extensively tested using datasets obtained from the Enhanced Traffic Management System (ETMS) database (now known as the Traffic Flow Management System). Representative Pareto-optimal tradeoff frontiers are consequently generated to allow decision-makers to identify best-compromising solutions based on relative weights and systematical considerations of both efficiency and equity. This dissertation further models and solves an integrated flight re-routing problem on an airspace network. Given a network of airspace sectors with a set of waypoint entries and a set of flights belonging to different air carriers, the optimization model aims to minimize the total flight travel time subject to a set of flight routing equity, operational and safety requirements. A time-dependent network flow programming formulation is proposed with stochastic sector capacities and rerouting equity for each air carrier as side constraints. A Lagrangian relaxation based method is used to dualize these constraints and decompose the original complex problem into a sequence of single flight rerouting/scheduling problems. Finally, within a multi-objective utility maximization framework, the dissertation proposes several practically useful heuristic algorithms for the long-term airport slot assignment problem. Alternative models are constructed to decompose the complex model into a series of hourly assignment sub-problems. A new paired assignment heuristic algorithm is developed to adapt the round robin scheduling principle for improving fairness measures across different airlines. Computational results are presented to show the strength of each proposed modeling approach

Engage D3.10 Research and innovation insights

Engage is the SESAR 2020 Knowledge Transfer Network (KTN). It is managed by a consortium of academia and industry, with the support of the SESAR Joint Undertaking. This report highlights future research opportunities for ATM. The basic framework is structured around three research pillars. Each research pillar has a dedicated section in this report. SESAR’s Strategic Research and Innovation Agenda, Digital European Sky is a focal point of comparison. Much of the work is underpinned by the building and successful launch of the Engage wiki, which comprises an interactive research map, an ATM concepts roadmap and a research repository. Extensive lessons learned are presented. Detailed proposals for future research, plus research enablers and platforms are suggested for SESAR 3

Cost-based linear holding practice and collaborative air traffic flow management under trajectory based operations

The current air transportation system is reaching the capacity limit in many countries/regions across the world. It tends to be less efficient or even incapable sometimes to deal with the enormous air traffic demand that continues growing year by year. This has been evidenced by the record-breaking flight delays reported in various places in recent years, which, have resulted in notable economical loses. To mitigate this imbalance between demand and capacity, air traffic flow management (ATFM) is usually one of the most useful options. It regulates traffic flows according to air traffic control capacity while preserving safety and efficiency of flights. ATFM initiatives can be considered well in advance of the flight execution - more than one year earlier - based on air traffic forecasts and capacity plans, and continue in effect, with information updated, to eventually the day of operation. This long effective period will inevitably allow substantial collaboration among different stakeholders, including the ATFM authority, airspace users (AUs), air navigation service providers (ANSPs), airports, etc. Under the forthcoming paradigm of trajectory based operations (TBO), the flight 4-Dimensional trajectory has been anticipated to further enhance the connection between flight planning and execution phases, thus fostering such collaboration in ATFM. Moreover, under nowadays operations, ground holding is a typical measure undertaken in many widely-used ATFM programs. Even though holding on the ground, at the origin airport, has the advantage of fuel efficiency over the air holding, it turns out that its feature of low flexibility would, in some circumstances, affect the ATFM performance. Yet, with proper flight trajectory management, it is also possible to have delay airborne at no extra fuel cost than performing ground holding. This PhD thesis firstly focuses on this trajectory management, specifically on a cost-based linear holding practice. The linear holding is realized progressively along the planned trajectory through precise speed control which can be enabled by aircraft trajectory optimization techniques. Some typical short/mid haul flights are simulated for achieving the maximum airborne delay that can be yielded using same fuel consumption as initially scheduled. Based on this, its potential applicability is demonstrated. A network ATFM model is adapted from the well-studied Bertsimas Stock-Patterson (BSP) model, incorporating different types of delay (including the linear holding) to flexibly handle the traffic flow with a set of given (yet changeable) capacities. In order that the benefits of the model can be fully realized, AUs are required to participate in the decision-making process, submitting for instance the maximum linear holding bound per flight along the planned trajectory. Next, increased AUs' participation is expected for a proposed Collaborative ATFM framework, in which not only various delay initiatives are considered, but also alternative trajectories which allow flights to route out of the identified hotspot areas. A centralized linear programming optimization model then computes for the best trajectory selections and the optimal delay distributions across all concerned flights. Finally, ANSPs' involvement is additionally considered for the framework, through dynamic airspace reconfiguration, further enhancing the collaboration between ATFM stakeholders. As such, the traffic flow regulation and sector opening scheduling are bounded into an integrated optimization model, and thus are conducted in a synchronized way. Results indicate that the performance of demand and capacity balancing can be even improved if compared with the previous ATFM models presented in this PhD thesis.El sistema de transport aeri actual està arribant al seu límit de capacitat en molts països i regions del món. Una gestió del flux de trànsit aeri (ATFM) més adequada podria mitigar aquest desequilibri entre la demanda i la capacitat. La funció de l'ATFM és regular els fluxos de trànsit aeri segons la capacitat de control del trànsit aeri, i alhora assegurar que els vols siguin segurs i eficients. Les regulacions del sistema d'ATFM es poden aplicar molt abans de l'execució del vol més d'un any abans. Un cop aplicades, aquestes regulacions continuaran evolucionant, amb informació actualitzada, fins el dia de la seva execució. El llarg període entre la planificació del vol i la seva execució permetrà una important col·laboració entre els diferents membres implicats, inclosa l'autoritat de l'ATFM, els usuaris de l'espai aeri (AUs), els proveïdors de serveis de navegació aèria (ANSP), els aeroports, etc. En les operacions d'avui en dia l'espera a terra és una de les regulacions que més aplica el sistema d'ATFM per tal d'evitar congestions als aeroports o sectors de l'espai aeri. Tot i que esperar a terra, a l'aeroport d'origen, té l'avantatge de consumir menys combustible que esperar a l'aire a l'aeroport de destí, la seva poca flexibilitat podria afectar negativament al rendiment de l'ATFM en algunes circumstàncies. Tanmateix, amb una gestió adequada de la trajectòria de vol, també és possible efectuar cert retard a l'aire sense cap cost addicional de combustible respecte al que resultaria esperant a terra. Aquesta tesi doctoral s'enfoca en primer lloc en aquesta gestió de trajectòria de vol, específicament en una pràctica d'espera tenint en compte els costos per l'aerolínia. L'espera lineal s'efectua progressivament al llarg de la trajectòria planificada mitjançant un control precís de la velocitat. Les velocitats que generen l'espera desitjada durant el vol és calculen mitjançant tècniques d'optimització. Alguns vols típics de curt i mig abast es simulen per quantificar el màxim retard a l'aire que es podria generar utilitzant el mateix consum de combustible que el previst inicialment. Basant-se en els resultats obtinguts, s'explora la seva aplicabilitat potencial. Es desenvolupa un model de la xarxa d'ATFM basat en el model de Bertsima Stock-Patterson. Com a novetat, el model desenvolupat en aquesta tesi incorpora diferents tipus de retard (incloent-hi l'espera lineal) per gestionar de forma més flexible el flux de trànsit donat un conjunt de capacitats pre-definides. Per tal d'explotar al màxim els beneficis del model proposat en aquesta tesi, les autoritats regionals estan obligades a participar en el procés de presa de decisions, declarant, per exemple, la màxima espera lineal associada a cada vol al llarg de la trajectòria planejada. Tot seguit, s'inclou la participació dels AUs en un sistema d'ATFM col·laboratiu, en el qual no només es consideren diverses tipus de retard per balancejar la capacitat i la demanda, sinó també trajectòries alternatives que permeten que els vols evitin de forma òptima els sectors de l?espai aeri congestionats. Un model d'optimització centralitzat basat en programació lineal calcula les millors seleccions de trajectòria i les distribucions òptimes de retard en tots els vols afectats per la regulació. Es demostra que incloure trajectòries alternatives pot reduir notablement la quantitat de retards. Finalment, es considera també la participació de l'ANSP en el sistema d'ATFM, a través de la configuració dinàmica de l'espai aeri, millorant encara més la col·laboració entre els membres implicats en el sistema. Com a tal, la regulació del flux de trànsit i la programació d'obertura dels diferents sectors de l'espai aeri s'inclouen en un model integrat d'optimització i, per tant, es programen de forma sincronitzada. Els resultats suggereixen que el rendiment del balanc¸ de la demanda i la capacitat es pot millorar encara m´es amb aquest sistema ATFM col·laboratiu complert. El nou model de balanc¸ de demanda i capacitat millora encara ées els resultats, si es compara amb els altres models d’ATFM presentats també en aquesta tesi doctoral.El sistema de transporte aéreo actual está llegando a su límite de capacidad en muchos países y regiones del mundo. Como consecuencia, éste tiende a ser menos eficiente e incluso en ocasiones incapaz de afrontar la enorme demanda de tráfico aéreo que incluso hoy en día crece rápidamente. Este hecho se ha visto evidenciado por los enormes retrasos registrados en diferentes lugares los últimos años, lo cual ha comportado enormes pérdidas económicas para la sociedad. Una gestión del flujo del tráfico aéreo (ATFM) más adecuada podría mitigar este desequilibrio entre la demanda y la capacidad. La función del ATFM es regular los flujos de tráfico aéreo según la capacidad de control del tráfico aéreo, siempre asegurando que los vuelos sean seguros y eficientes. Las regulaciones del sistema de ATFM se pueden aplicar mucho antes de la ejecución del vuelo –más de un año antes– en función de las previsiones de tráfico aéreo y de la capacidad esperada. Una vez aplicadas, estas regulaciones continuarán evolucionando, con información actualizada, hasta el día de su ejecución. El largo periodo entre la planificación del vuelo y su ejecución permitirá una importante colaboración entre los diferentes miembros implicados, incluida la autoridad del ATFM, los usuarios del espacio aéreo (AUs), los proveedores de servicios de navegación aérea (ANSP), los aeropuertos, etc. En el marco del futuro paradigma de las operaciones basadas en trayectorias, la introducción de vuelos con control sobre la trayectoria en las 4 dimensiones espera mejorar aún más la conexión entre las fases de planificación del vuelo y su ejecución, fomentando así la colaboración en el proceso de toma de decisiones del sistema ATFM. En las operaciones de hoy en día la espera en tierra es una de las regulaciones que más se aplica en el sistema de ATFM con el fin de evitar congestiones en los aeropuertos o en los sectores del espacio aéreo. Aun teniendo en cuenta que esperar en tierra, en el aeropuerto de origen, tiene la ventaja de consumir menos combustible que esperar en el aire en el aeropuerto de destino, su poca flexibilidad podría afectar negativamente al rendimiento del ATFM en algunas circunstancias. Aun así, con una gestión adecuada de la trayectoria de vuelo, también es posible efectuar cierto retraso en el aire sin ningún coste adicional de combustible respecto a lo que resultaría esperando en tierra. Esta tesis doctoral se centra en primer lugar en esta gestión de la trayectoria de vuelo, específicamente en una práctica de espera lineal considerando los costes para la aerolínea. La espera lineal se efectúa progresivamente a lo largo de la trayectoria planificada mediante un control preciso de la velocidad. Las velocidades que generan la espera deseada durante el vuelo se calculan mediante técnicas de optimización. Algunos vuelos típicos de corto y medio alcance se simulan para cuantificar el máximo retraso en el aire que se podría generar utilizando el mismo consumo de combustible que el previsto inicialmente. Basándose en los resultados obtenidos, se investiga su potencial aplicabilidad, como por ejemplo mejorar la planificación de programas de flujo del espacio aéreo, y ayudar a neutralizar los retrasos no deseados adicionales debidos a la incertidumbre del sistema. Se desarrolla un modelo de la red de ATFM basado en el conocido modelo Bertsimas Stock-Patterson (BSP). Como novedad, el modelo desarrollado en esta tesis incorpora diferentes tipos de retraso (incluyendo la espera lineal) para gestionar de manera más flexible el flujo de tráfico dado un conjunto de capacidades predefinidas. Con el fin de explotar al máximo los beneficios del modelo propuesto en esta tesis, se asume que las aerolíneas participaran en el proceso de toma de decisiones, declarando, por ejemplo, la máxima espera lineal asociada a cada vuelo a lo largo de la trayectoria planeada. Este concepto se ilustra con un caso de estudio, donde se demuestra una reducción significativa de los retrasos, comparado con el modelo BSP. Seguidamente, se incluye la participación de las aerolíneas en un sistema de ATFM colaborativo, en el cual no tan sólo se consideran diferentes tipos de retrasos para balancear la capacidad y la demanda, sino también trayectorias alternativas que permiten que los vuelos eviten de forma óptima los sectores del espacio aéreo congestionados. Un modelo de optimización centralizado basado en programación lineal calcula las mejores selecciones de la trayectoria y las distribuciones óptimas de retraso en todos los vuelos afectado por la regulación. Se demuestra que incluir trayectorias alternativas puede reducir notablemente la cantidad de retrasos. Finalmente, se considera también la participación de los ANSP en el sistema de ATFM, a través de la configuración dinámica del espacio aéreo, mejorando aún más la colaboración entre los miembros implicados en el sistema. Como tales, la regulación del flujo de tráfico aéreo y la programación de apertura de los diferentes sectores del espacio aéreo se incluyen en un modelo integrado de optimización y, por lo tanto, se programan de manera sincronizada. El nuevo modelo de balance de demanda y capacidad mejora aún más los resultados, si se compara con los otros modelos ATFM presentados también en esta tesis doctoralPostprint (published version

Resource-Constrained Airline Ground Operations: Optimizing Schedule Recovery under Uncertainty

Die zentrale europäische Verkehrsflusssteuerung (englisch: ATFM) und Luftverkehrsgesellschaften (englisch: Airlines) verwenden unterschiedliche Paradigmen für die Priorisierung von Flügen. Während ATFM jeden Flug als individuelle Einheit betrachtet, um die Kapazitätsauslastung aller Sektoren zu steuern, bewerten Airlines jeden Flug als Teilabschnitt eines Flugzeugumlaufes, eines Crew-Einsatzplanes bzw. einer Passagierroute. Infolgedessen sind ATFM-Zeitfenster für Flüge in Kapazitätsengpässen oft schlecht auf die Ressourcenabhängigkeiten innerhalb eines Airline-Netzwerks abgestimmt, sodass die Luftfahrzeug-Bodenabfertigung – als Verbindungselement bzw. Bruchstelle zwischen einzelnen Flügen im Netzwerk – als Hauptverursacher primärer und reaktionärer Verspätungen in Europa gilt. Diese Dissertation schließt die Lücke zwischen beiden Paradigmen, indem sie ein integriertes Optimierungsmodell für die Flugplanwiederherstellung entwickelt. Das Modell ermöglicht Airlines die Priorisierung zwischen Flügen, die von einem ATFM-Kapazitätsengpass betroffen sind, und berücksichtigt dabei die begrenzte Verfügbarkeit von Abfertigungsressourcen am Flughafen. Weiterhin werden verschiedene Methoden untersucht, um die errechneten Flugprioritäten vertraulich innerhalb von kooperativen Lösungsverfahren mit externen Stakeholdern austauschen zu können. Das integrierte Optimierungsmodell ist eine Erweiterung des Resource-Constrained Project Scheduling Problems und integriert das Bodenprozessmanagement von Luftfahrzeugen mit bestehenden Ansätzen für die Steuerung von Flugzeugumläufen, Crew-Einsatzplänen und Passagierrouten. Das Modell soll der Verkehrsleitzentrale einer Airline als taktische Entscheidungsunterstützung dienen und arbeitet dabei mit einer Vorlaufzeit von mehr als zwei Stunden bis zur nächsten planmäßigen Verkehrsspitze. Systemimmanente Unsicherheiten über Prozessabweichungen und mögliche zukünftige Störungen werden in der Optimierung in Form von stochastischen Prozesszeiten und mittels des neu-entwickelten Konzeptes stochastischer Verspätungskostenfunktionen berücksichtigt. Diese Funktionen schätzen die Kosten der Verspätungsausbreitung im Airline-Netzwerk flugspezifisch auf der Basis historischer Betriebsdaten ab, sodass knappe Abfertigungsressourcen am Drehkreuz der Airline den kritischsten Flugzeugumläufen zugeordnet werden können. Das Modell wird innerhalb einer Fallstudie angewendet, um die taktischen Kosten einer Airline in Folge von verschiedenen Flugplanstörungen zu minimieren. Die Analyseergebnisse zeigen, dass die optimale Lösung sehr sensitiv in Bezug auf die Art, den Umfang und die Intensität einer Störung reagiert und es folglich keine allgemeingültige optimale Flugplanwiederherstellung für verschiedene Störungen gibt. Umso dringender wird der Einsatz eines flexiblen und effizienten Optimierungsverfahrens empfohlen, welches die komplexen Ressourcenabhängigkeiten innerhalb eines Airline-Netzwerks berücksichtigt und kontextspezifische Lösungen generiert. Um die Effizienz eines solchen Optimierungsverfahrens zu bestimmen, sollte das damit gewonnene Steuerungspotenzial im Vergleich zu aktuell genutzten Verfahren über einen längeren Zeitraum untersucht werden. Aus den in dieser Dissertation analysierten Störungsszenarien kann geschlussfolgert werden, dass die flexible Standplatzvergabe, Passagier-Direkttransporte, beschleunigte Abfertigungsverfahren und die gezielte Verspätung von Abflügen sehr gute Steuerungsoptionen sind und während 95 Prozent der Saison Anwendung finden könnten, um geringe bis mittlere Verspätungen von Einzelflügen effizient aufzulösen. Bei Störungen, die zu hohen Verspätungen im gesamten Airline-Netzwerk führen, ist eine vollständige Integration aller in Betracht gezogenen Steuerungsoptionen erforderlich, um eine erhebliche Reduzierung der taktischen Kosten zu erreichen. Dabei ist insbesondere die Möglichkeit, Ankunfts- und Abflugzeitfenster zu tauschen, von hoher Bedeutung für eine Airline, um die ihr zugewiesenen ATFM-Verspätungen auf die Flugzeugumläufe zu verteilen, welche die geringsten Einschränkungen im weiteren Tagesverlauf aufweisen. Die Berücksichtigung von Unsicherheiten im nachgelagerten Airline-Netzwerk zeigt, dass eine Optimierung auf Basis deterministischer Verspätungskosten die taktischen Kosten für eine Airline überschätzen kann. Die optimale Flugplanwiederherstellung auf Basis stochastischer Verspätungskosten unterscheidet sich deutlich von der deterministischen Lösung und führt zu weniger Passagierumbuchungen am Drehkreuz. Darüber hinaus ist das vorgeschlagene Modell in der Lage, Flugprioritäten und Airline-interne Kostenwerte für ein zugewiesenes ATFM-Zeitfenster zu bestimmen. Die errechneten Flugprioritäten können dabei vertraulich in Form von optimalen Verspätungszeitfenstern pro Flug an das ATFM übermittelt werden, während die Definition von internen Kostenwerten für ATFM-Zeitfenster die Entwicklung von künftigen Handelsmechanismen zwischen Airlines unterstützen kann.:1 Introduction 2 Status Quo on Airline Operations Management 3 Schedule Recovery Optimization Approach with Constrained Resources 4 Implementation and Application 5 Case Study Analysis 6 ConclusionsAir Traffic Flow Management (ATFM) and airlines use different paradigms for the prioritisation of flights. While ATFM regards each flight as individual entity when it controls sector capacity utilization, airlines evaluate each flight as part of an aircraft rotation, crew pairing and passenger itinerary. As a result, ATFM slot regulations during capacity constraints are poorly coordinated with the resource interdependencies within an airline network, such that the aircraft turnaround -- as the connecting element or breaking point between individual flights in an airline schedule -- is the major contributor to primary and reactionary delays in Europe. This dissertation bridges the gap between both paradigms by developing an integrated schedule recovery model that enables airlines to define their optimal flight priorities for schedule disturbances arising from ATFM capacity constraints. These priorities consider constrained airport resources and different methods are studied how to communicate them confidentially to external stakeholders for the usage in collaborative solutions, such as the assignment of reserve resources or ATFM slot swapping. The integrated schedule recovery model is an extension of the Resource-Constrained Project Scheduling Problem and integrates aircraft turnaround operations with existing approaches for aircraft, crew and passenger recovery. The model is supposed to provide tactical decision support for airline operations controllers at look-ahead times of more than two hours prior to a scheduled hub bank. System-inherent uncertainties about process deviations and potential future disruptions are incorporated into the optimization via stochastic turnaround process times and the novel concept of stochastic delay cost functions. These functions estimate the costs of delay propagation and derive flight-specific downstream recovery capacities from historical operations data, such that scarce resources at the hub airport can be allocated to the most critical turnarounds. The model is applied to the case study of a network carrier that aims at minimizing its tactical costs from several disturbance scenarios. The case study analysis reveals that optimal recovery solutions are very sensitive to the type, scope and intensity of a disturbance, such that there is neither a general optimal solution for different types of disturbance nor for disturbances of the same kind. Thus, airlines require a flexible and efficient optimization method, which considers the complex interdependencies among their constrained resources and generates context-specific solutions. To determine the efficiency of such an optimization method, its achieved network resilience should be studied in comparison to current procedures over longer periods of operation. For the sample of analysed scenarios in this dissertation, it can be concluded that stand reallocation, ramp direct services, quick-turnaround procedures and flight retiming are very efficient recovery options when only a few flights obtain low and medium delays, i.e., 95% of the season. For disturbances which induce high delay into the entire airline network, a full integration of all considered recovery options is required to achieve a substantial reduction of tactical costs. Thereby, especially arrival and departure slot swapping are valuable options for the airline to redistribute its assigned ATFM delays onto those aircraft that have the least critical constraints in their downstream rotations. The consideration of uncertainties in the downstream airline network reveals that an optimization based on deterministic delay costs may overestimate the tactical costs for the airline. Optimal recovery solutions based on stochastic delay costs differ significantly from the deterministic approach and are observed to result in less passenger rebooking at the hub airport. Furthermore, the proposed schedule recovery model is able to define flight priorities and internal slot values for the airline. Results show that the priorities can be communicated confidentially to ATFM by using the concept of 'Flight Delay Margins', while slot values may support future inter-airline slot trading mechanisms.:1 Introduction 2 Status Quo on Airline Operations Management 3 Schedule Recovery Optimization Approach with Constrained Resources 4 Implementation and Application 5 Case Study Analysis 6 Conclusion

Optimization Models for Speed Control in Air Traffic Management

In a typical air traffic control environment, the precise landing times of en route aircraft are not set until each aircraft approaches the airspace adjacent to the destination airport. In times of congestion, it is not unusual for air traffic controllers to subject arriving aircraft to various maneuvers to create an orderly flow of flights onto an arrival runway. Typical maneuvers include flying in zig-zag patterns, flying in race track shaped patterns and tromboning. These maneuvers serve to delay the arrival time of the flight while also burning additional fuel. On the other hand, if the arrival time was established much earlier, then such delay could be realized by simply having flights fly slower while still at a higher altitude, which would incur much less fuel burn than the described maneuvers. Yet despite its potential benefit, thus far little has been done to promote the management of flights using speed control in the presence of uncertainty. This dissertation presents a set of models and prescriptions designed to use the mechanism of speed control to enhance the level of coordination used by FAA managers at the tactical and pre-tactical level to better account for the underlying uncertainty at the time of planning. Its models deal with the challenge of assigning delay to aircraft approaching a single airport, well in advance of each aircraft’s entry into the terminal airspace. In the first approach, we assume control of all airborne flights at a distance of 500 nm while assuming no control over flights originating less than 500 nm from the airport. We propose a set of integer programming models designed to issue arrival times for controlled flights in the presence of the uncertainty associated with the unmanaged flights. In the second approach, we assume control over all flights by subjecting flights to a combination of air and ground delay. Both approaches show strong potential to transfer delay from the terminal to the en route phase of flight and achieve fuel savings. Building on these ideas we then formulate an approach to incorporate speed control into Ground Delay Programs. We propose enhancements for equitably rationing airport access to carriers and develop a revised framework to allow carriers to engage in Collaborative Decision Making. We present new GDP control procedures and also new flight operator GDP planning models. While the ability to achieve all the benefits we describe will require NextGen capabilities, substantial performance improvements could be obtained even with a near-term implementation

AVIATION CONGESTION MANAGEMENT IMPROVEMENTS IN MODELING THE PREDICTION, MITIGATION, AND EVALUATION OF CONGESTION IN THE NATIONAL AIRSPACE SYSTEM

The air transportation system in the United States is one of the most complex systems in the world. Projections of increasing air traffic demand in conjunction with limited capacity, that is volatile and affected by exogenous random events, represent a major problem in aviation system management. From a management perspective, it is essential to make efficient use of the available resources and to create mechanisms that will help alleviate the problems of the imbalance between demand and capacity. Air traffic delays are always present and the more air traffic increases the more the delays will increase with very unwanted economic impacts. It is of great interest to study them further in order to be able to more effectively mitigate them. A first step would be to try to predict them under various circumstances. A second step would be to develop various mechanisms that will help in reducing delays in different settings. The scope of this dissertation is to look closer at a threefold approach to the problem of congestion in aviation. The first effort is the prediction of delays and the development of a model that will make these predictions under a wide variety of distributional assumptions. The work presented here is specifically on a continuum approximation using diffusion methods that enables efficient solutions under a wide variety of distributional assumptions. The second part of the work effort presents the design of a parsimonious language of exchange, with accompanying allocation mechanisms that allow carriers and the FAA to work together quickly, in a Collaborative Decision Making environment, to allocate scarce capacity resources and mitigate delays. Finally, because airlines proactively use longer scheduled block times to deal with unexpected delays, the third portion of this dissertation presents the assessment of the monetary benefits due to improvements in predictability as manifested through carriers' scheduled block times

Collision risk-capacity tradeoff analysis of an en-route corridor model

AbstractFlow corridors are a new class of trajectory-based airspace which derives from the next generation air transportation system concept of operations. Reducing the airspace complexity and increasing the capacity are the main purposes of the en-route corridor. This paper analyzes the collision risk-capacity tradeoff using a combined discrete–continuous simulation method. A basic two-dimensional en-route flow corridor with performance rules is designed as the operational environment. A second-order system is established by combining the point mass model and the proportional derivative controller together to simulate the self-separation operations of the aircrafts in the corridor and the operation performance parameters from the User Manual for the Base of Aircraft Data are used in this research in order to improve the reliability. Simulation results indicate that the aircrafts can self-separate from each other efficiently by adjusting their velocities, and rationally setting the values of some variables can improve the rate and stability of the corridor with low risks of loss of separation

A tractable optimization framework for Air Traffic Flow Management addressing fairness, collaboration and stochasticity

Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 151-154).We propose a tractable optimization framework for network Air Traffic Flow Management (ATFM) with an eye towards the future. The thesis addresses two issues in ATFM research: a) fairness and collaboration amongst airlines; and b) uncertainty inherent in capacity forecasts. A unifying attraction of the overall dissertation is that the Collaborative Decision-Making (CDM) paradigm, which is the current philosophy governing the design of new ATFM initiatives, is treated as the starting point in the research agenda. In the first part of the thesis, we develop an optimization framework to extend the CDM paradigm from a single-airport to a network setting by incorporating both fairness and airline collaboration. We introduce different notions of fairness emanating from a) First-Scheduled First-Served (FSFS) fairness; and b) Proportional fairness. We propose exact discrete optimization models to incorporate them. The first fairness paradigm which entails controlling number of reversals and total amount of overtaking is especially appealing in the ATFM context as it is a natural extension of Ration-By-Schedule (RBS). We allow for further airline collaboration by proposing discrete optimization models for slot reallocation. We provide empirical results of the proposed optimization models on national-scale, real world datasets that show interesting tradeoffs between fairness and efficiency. In particular, schedules close to the RBS policy (with single digit reversals) are possible for a less than 10% increase in delay costs. We utilize case studies to highlight the considerable improvements in the internal objective functions of the airlines as a result of slot exchanges. Finally, the proposed models are computationally tractable (running times of less than 30 minutes). In the second part, we address the important issue of capacity uncertainty by presenting the first application of robust and adaptive optimization in the ATFM problem. We introduce a weather-front based approach to model the uncertainty inherent in airspace capacity estimates resulting from the impact of a small number of weather fronts. We prove the equivalence of the robust problem to a modified instance of the deterministic problem; solve the LP relaxation of the adaptive problem using affine policies; and report extensive empirical results to study the inherent tradeoffs.by Shubham Gupta.Ph.D