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A key attribute of resilience, robustness serves as a predictor of infrastructure system performance under disruptions, thus informing proactive infrastructure risk management. A literature review indicated that previous studies did not consider some key factors that can influence the robustness of Air Transportation Infrastructure Networks (ATIN) and thus their (system-level cascade) systemic risk management processes. In this respect, the current study first assesses existing and then develops a new methodology to quantify the robustness of ATIN. Specifically, based on integrating travel time and flight frequency, the study develops alternative best route and link weight approaches to assess key ATIN robustness measures and relevant operating cost losses (OCL). In order to demonstrate the practical use of the developed methodology, the robustness and the associated OCL of the Canadian Domestic Air Traffic Network are evaluated under random failures (i.e., disruptive events that occur randomly) and targeted threats (i.e., disruptive events that occur deliberately). The analysis results show that the network robustness is influenced by the utilized evaluation approach, especially after 20% of the network components become nonoperational. Overall, the methodology developed within this study is expected to provide ATIN policymakers with the means to quantify the network robustness and OCL, and thus enable ATIN resilience-guided proactive risk management in the face of natural or anthropogenic hazard realizations. / Thesis / Master of Applied Science (MASc)

The Federal Aviation Administration (FAA) has been modernizing the United States' air transportation system within a series of initiatives called the Next Generation Air Transportation System (NextGen). The goal of NextGen is to increase the safety, efficiency, capacity, predictability, and resiliency of American Air Traffic Control (ATC) by implementing satellite-based communication, and navigation systems. Because of the vast oceanic areas controlled by Oakland, New York, and Anchorage air traffic control centers, improving oceanic operations is significant for the United States. According to the FAA, oceanic flights generate 31% of passenger revenue and 40% of cargo revenue in U.S.-controlled airspace. New NextGen procedures offer the opportunity for aircraft to save fuel consumption by allowing oceanic flights to fly at more efficient routes and flight levels. This dissertation investigates three areas to improve flight operations over oceanic airspace. The first area studies the operational benefits of providing satellite-based meteorological information to aircraft operating in remote and oceanic airspace. This research effort uses two approaches as follows: 1) statistical flight analysis, and 2) simulation-based analysis. The second area provides an optimization technique to improve the current procedures for assigning flights to the Organized Track System (OTS) in the Atlantic Ocean based on the Collaborative Decision Making (CDM) concept. The third area investigates the potential savings of "In-Trail Procedure" (ITP) as one of the advanced surveillance operations in the Pacific and Atlantic oceanic airspace. To quantify the operational benefits of the proposed procedures, a fast-time simulation tool, the Global Oceanic (GO) model, is developed and employed. The GO model is a microscopic flight simulation tool that has been developing by the Air Transportation Systems Laboratory at Virginia Tech offering realistic and inexpensive evaluations of novel technologies and procedures to improve flight operations over global oceanic airspace. the results of these studies are analyzed in terms of fuel consumption, travel distance, travel time, level of service, and potential air traffic controllers' workload. / Doctor of Philosophy / The economic growth and social connectivity of nations are highly correlated to effective and efficient air transportation systems. The Federal Aviation Administration (FAA) has initiated a program to modernize America's air transportation system and make flight operations safer, and more efficient. This program is called the Next Generation Air Transportation System (NextGen) and its goal is transforming the communication and navigation technologies to satellite-based systems. Improving oceanic flights is one of the main concerns of the NextGen program since the United States controls massive oceanic areas in the Atlantic and the Pacific Ocean. The FAA needs to evaluate the benefits and costs of advanced technologies and procedures to justify the NextGen initiatives. The FAA has employed computer simulation tools to support decisions for future infrastructure investments and encourage airlines to equip their aircraft with more advanced avionics. The Global Oceanic (GO) model is a microscopic flight simulation tool developed jointly by the Air Transportation Systems Laboratory at Virginia Tech and the FAA providing quick, realistic, and inexpensive evaluations of advanced procedures to improve flight operations over oceans. This dissertation investigates the operational benefit of three advanced procedures using the GO model. The areas to improve flight operations over oceanic airspace are as follows: 1) operational benefits of providing satellite-based meteorological information to aircraft operating in remote and oceanic airspace, 2) operational benefits of an optimization technique for flight assignments to the Organized Track System (OTS) in the Atlantic Ocean, 3) operational benefits of "In-Trail Procedure" (ITP) as one of the advanced surveillance operations in the Pacific and Atlantic oceanic airspace. These studies quantify the potential savings of these procedures in terms of reducing fuel consumption, travel distance, travel time, greenhouse gas emissions, and potential air traffic controllers' workload.

This dissertation contributes to the ongoing national project concerning the \emph{Next Generation Air Transportation System} (NextGen) that endeavors, in particular, to reshape the management of air traffic in the continental United States. Our work is part of this effort and mainly concerns modeling and algorithmic enhancements to the Airspace Planning and Collaborative Decision-Making Model (APCDM). First, we augment the APCDM to study an \emph{Airspace Flow Program} (AFP) in the context of weather-related disruptions. The proposed model selects among alternative flight plans for the affected flights while simultaneously (a) integrating slot-exchange mechanisms induced by multiple Ground Delay Programs (GDPs) to permit airlines to improve flight efficiencies through a mediated bartering of assigned slots, and (b) considering issues related to sector workloads, airspace conflicts, as well as overall equity concerns among the involved airlines in regard to accepted slot trades and flight plans. More specifically, the APCDM is enhanced to include the following: a. The revised model accommodates continuing flights, where some flight cannot depart until a prerequisite flight has arrived. Such a situation arises, for example, when the same aircraft will be used for the departing flight. b. We model a slot-exchange mechanism to accommodate flights being involved in multiple trade offers, and to permit slot trades at multiple GDP airports (whence the flight connection constraints become especially relevant). We also model flight cancelations whereby, if a flight assigned to a particular slot is canceled, the corresponding vacated slot would be made available for use in the slot-exchange process. c. Alternative equity concepts are presented, which more accurately reflect the measures used by the airlines. d. A reduced variant of the APCDM, referred to as \textbf{APCDM-Light}, is also developed. This model serves as a fast-running version of APCDM to be used for quick-turn analyses, where the level of modeling detail, as well as data requirements, are reduced to focus only on certain key elements of the problem. e. As an alternative for handling large-scale instances of APCDM more effectively, we present a \emph{sequential variable fixing heuristic} (SFH). The list of flights is first partitioned into suitable subsets. For the first subset, the corresponding decision variables are constrained to be binary-valued (which is the default for these decision variables), while the other variables are allowed to vary continuously between 0 and 1. If the resulting solution to this relaxed model is integral, the algorithm terminates. Otherwise, the binary variables are fixed to their currently prescribed values and another subset of variables is designated to be binary constrained. The process repeats until an integer solution is found or the heuristic encounters infeasibility. f. We experiment with using the APCDM model in a \emph{dynamic, rolling-horizon framework}, where we apply the model on some periodic basis (e.g., hourly), and where each sequential run of the model has certain flight plan selections that are fixed (such as flights that are already airborne), while we consider the selection among alternative flight plans for other imminent flights in a look-ahead horizon (e.g., two hours). These enhancements allow us to significantly expand the functionality of the original APCDM model. We test the revised model and its variants using realistic data derived from the \emph{Enhanced Traffic Management System} (ETMS) provided by the \emph{Federal Aviation Administration} (FAA). One of the new equity methods, which is based on average delay per passenger (or weighted average delay per flight), turns out to be a particularly robust way to model equity considerations in conjunction with sector workloads, conflict resolution, and slot-exchanges. With this equity method, we were able to solve large problem instances (1,000 flights) within 30 seconds on average using a 1\% optimality tolerance. The model also produced comparable solutions within about 20 seconds on average using the Sequential Fixing Heuristic (SFH). The actual solutions obtained for these largest problem instances were well within 1\% of the best known solution. Furthermore, our computations revealed that APCDM-Light can be readily optimized to a 0.01\% tolerance within about 5 seconds on average for the 1,000 flight problems. Thus, the augmented APCDM model offers a viable tool that can be used for tactical air traffic management purposes as an airspace flow program (particularly, APCDM-Light), as well as for strategic applications to study the impact of different types of trade restrictions, collaboration policies, equity concepts, and airspace sectorizations. The modeling of slot ownership in the APCDM motivates another problem: that of generating detoured flight plans that must arrive at a particular slot time under severe convective weather conditions. This leads to a particular class of network flow problems that seeks a shortest path, if it exists, between a source node and a destination node in a connected digraph $G(N,A)$, such that we arrive at the destination at a specified time while leaving the source no earlier than a lower bounding time, and where the availability of each network link is time-dependent in the sense that it can be traversed only during specified intervals of time. We refer to this problem as the \emph{reverse time-restricted shortest path problem} (RTSP). We show that RTSP is NP-hard in general and propose a dynamic programming algorithm for finding an optimal solution in pseudo-polynomial time. Moreover, under a special regularity condition, we prove that the problem is polynomially solvable with a complexity of order $O(|N / A|)$. Computational results using real flight generation test cases as well as random simulated problems are presented to demonstrate the efficiency of the proposed solution procedures. The current airspace configuration consists of sectors that have evolved over time based on historical traffic flow patterns. \citet{kopardekar_dyn_resect_2007} note that, given the current airspace configuration, some air traffic controller resources are likely under-utilized, and they also point out that the current configuration limits flexibility. Moreover, under the free-flight concept, which advocates a relaxation of waypoint traversals in favor of wind-optimized trajectories, the current airspace configuration will not likely be compatible with future air traffic flow patterns. Accordingly, one of the goals for the \emph{NextGen Air Transportation System} includes redesigning the airspace to increase its capacity and flexibility. With this motivation, we present several methods for defining sectors within the \emph{National Airspace System} (NAS) based on a measure of sector workload. Specifically, given a convex polygon in two-dimensions and a set of weighted grid points within the region encompassed by the polygon, we present several mixed-integer-programming-based algorithms to generate a plane (or line) bisecting the region such that the total weight distribution on either side of the plane is relatively balanced. This process generates two new polygons, which are in turn bisected until some target number of regions is reached. The motivation for these algorithms is to dynamically reconfigure airspace sectors to balance predicted air-traffic controller workload. We frame the problem in the context of airspace design, and then present and compare four algorithmic variants for solving these problems. We also discuss how to accommodate monitoring, conflict resolution, and inter-sector coordination workloads to appropriately define grid point weights and to conduct the partitioning process in this context. The proposed methodology is illustrated using a basic example to assess the overall effect of each algorithm and to provide insights into their relative computational efficiency and the quality of solutions produced. A particular competitive algorithmic variant is then used to configure a region of airspace over the U.S. using realistic flight data. The development of the APCDM is part of an ongoing \emph{NextGen} research project, which envisages the sequential use of a variety of models pertaining to three tiers. The \emph{Tier 1} models are conceived to be more strategic in scope and attempt to identify potential problematic areas, e.g., areas of congestion resulting from a severe convective weather system over a given time-frame, and provide aggregate measures of sector workloads and delays. The affected flow constrained areas (FCAs) highlighted by the results from these \emph{Tier 1} models would then be analyzed by more detailed \emph{Tier 2} models, such as APCDM, which consider more specific alternative flight plan trajectories through the different sectors along with related sector workload, aircraft conflict, and airline equity issues. Finally, \emph{Tier 3} models are being developed to dynamically examine smaller-scaled, localized fast-response readjustments in air traffic flows within the time-frame of about an hour prior to departure (e.g., to take advantage of a break in the convective weather system). The APCDM is flexible, and perhaps unique, in that it can be used effectively in all three tiers. Moreover, as a strategic tool, analysts could use the APCDM to evaluate the suitability of potential airspace sectorization strategies, for example, as well as identify potential capacity shortfalls under any given sector configuration. / Ph. D.

The purpose of this research thesis was to develop a framework and methodology for the design of a graphical user interface to be used by air traffic controllers. The interface is intended to be only a part of a complete Advisory System designed to supplement the tasks of terminal area air traffic controllers. This research addresses many of the human factors issues associated with the development of the display. The research takes a user-perspective and applies the principles of rapid prototyping to develop the framework for the design of the interface. Attention is also given to the previous research that explores the implications of automating various air traffic control tasks. Finally, a prototype system was developed to fulfill one of the primary rapid prototyping steps. The prototype displays the general format for the various advisories and presents three typical scenarios where the system may be of particular use. In the future, the prototype can be used to gather additional information on the opinions and requirements of the future system users - air traffic controllers. It is anticipated that moderate benefits can be attained through the implementation of such a system, provided that the interface satisfies the user requirements. / Master of Science

Wake vortices pose a threat to a following aircraft, because they can induce a roll and compromise the safety of everyone on board. Caused by a difference in pressure between the upper and the lower part of the wings, these invisible flows of air are a major hazard and have to be avoided by separating the aircraft at considerable distances. One of the known constraints in airport capacity for both departure and arrival operations is the large headway resulting from the wake spacing separation criteria. Reducing wake vortex separations to a safe level between successive aircraft can increase capacity in the National Airspace System (NAS) with corresponding savings in delay times. One of the main goals of the Wake Encounter Model (WEM) described in this thesis is to assess the outcome from future reduced separation criteria in the NAS. The model has been used to test probable encounters in today's operations, and can also be used to test NextGen scenarios, such as Close Parallel Approaches and reduced in-trail separation flights. This thesis presents model enhancements to account for aircraft turning maneuvers, giving the wake a more realistic shape. Three major airspaces, New York, Southern California and Atlanta, were analyzed using the original and the enhanced WEM to determine if the enhanced model better represents the conditions in today's operations. Additionally, some analysis on the wake lateral travel for closely spaced runways is presented in this thesis. Finally, some extension tools for post -analysis, such as animation tool and various graphs depicting the interactions between wake pairs were developed. / Master of Science

This document provides a comprehensive historical account of the International Advisory Group - Air Navigation Services (ANSA) and shows the achievements, organizational changes, and contributions to the aviation industry. Established in 1967 by German air traffic controllers from the Rhein Control upper airspace ATC center, ANSA is a non-profit organization dedicated to improving air traffic control systems and procedures. Initially formed to support German air navigation authorities and EUROCONTROL, the group expanded its membership to include experts from over 20 countries. In 1985, ANSA moved its legal seat to Switzerland, continuing its mission to enhance flight safety and modernize ATC systems.

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