As air traffic congestion grows, air traffic flow management (ATFM) is becoming a great concern. ATFM deals with air traffic and the efficient utilization of the airport and airspace. Air traffic efficiency is heavily influenced by unanticipated factors, or uncertainties, which can come from several sources such as mechanical breakdown; however, weather is the main unavoidable cause of uncertainty. Because weather is unpredictable, it poses a critical challenge for ATFM in current airport and airspace operations. Convective weather results in congestion at airports as well as in airspace sectors. During times of congestion, the decision as how and when to send aircraft toward an airspace sector in the presence of weather is difficult. To approach this problem, we first propose a two-stage stochastic integer program by emphasizing a given single sector. By considering ground delay, cancellation, and cruise speed for each flight on the ground in the first stage, as well as air holding and diversion recourse actions for each flight in the air in the second stage, our model determines how aircraft are sent toward a sector under the uncertainty of weather. However, due to the large number of weather scenarios, the model is intractable in practice. To overcome the intractability, we suggest a rolling horizon method to solve the problem to near optimal. Lagrangian relaxation and subgradient method are used to justify the rolling horizon method. Since the rolling horizon method can be solved in real time, we can apply it to actual aircraft schedules to reduce the costs incurred on the ground as well as in airspace. We then extend our two-stage model to a multistage stochastic program, which increases the number of possible weather realizations and results a more efficient schedule in terms of costs. The rolling horizon method as well as Lagrangian relaxation and subgradient method are applied to this multistage model. An overall comparison among the previously described methodologies are presented.

Increased efficiency at airports is necessary to reduce delays and fuel consumption. Many of the busiest airports in the nation have at least one pair of closely spaced parallel runways (CSPRs), defined by a separation of less than 2500 ft, with one runway dedicated to arrivals and the other to departures. CSPRs experience a large decrease in capacity under instrument conditions because they can no longer operate independently. In order to mitigate this decrease in capacity and to increase efficiency, proposed herein is a departure regulator for runways so configured, along with a plan of study to investigate the effects of this regulator. The proposed departure regulator makes use of data from precision tracking systems such as ADS-B to issue automated or semi-automated departure clearances. Assuming sequential departure separations are sufficient for clearance, the regulator will automatically issue, or advise the controller to issue, the departure clearance as soon as the arrival on the adjacent runway has descended below its decision height. By issuing the departure clearance earlier, the departure regulator reduces the gap between a pair of arrivals that is required to clear a departure. By decreasing the gap, the regulator increases the number of opportunities where a departure clearance can be issued, given a particular arrival stream. A simulation models the effects of the regulator and quantifies the resulting increases in capacity. The simulation results indicate that all forms of the regulator would provide significant gains of between 14% and 23% in capacity over the current operating paradigm. The results also indicate that the capacity gains are greatest at high arrival rates. Therefore, implementation of the departure regulator could significantly decrease the congestion at many major airports during inclement weather.

In ongoing efforts to balance air traffic demand and airspace capacity, airspace complexity stands as a fundamental research problem. Taking a more analytic approach, this thesis proposes that airspace complexity can be described in terms of how the airspace (together with the traffic inside it and the traffic control algorithm) responds to disturbances. The response of the airspace to a disturbance is captured by the degree of control activity required to accommodate such disturbance. Furthermore, since the response of the airspace depends on the disturbance, this thesis introduces a complexity map which shows how an airspace responses to a set of different disturbances. Among the many possible types of disturbances, this thesis considers an aircraft entering into the airspace, and the proposed method of describing airspace complexity is illustrated with examples. The time evolution of a complexity map is investigated using a statistical approach. In addition, the proposed method is illustrated in relation to current and future traffic flow management concepts. It is also shown that the proposed method can be applied to airspace design problems.

The air transportation demand at large hubs in the U.S. is anticipated to double in the near future. Current runway construction plans at selected airports can relieve some capacity and delay problems, but many are doubtful that this solution is sufficient to accommodate the anticipated demand growth in the National Airspace System (NAS). With the worsening congestion problem, it is imperative to seek alternative solutions other than costly runway constructions. In this respect, many researchers and organizations have been building models and performing analyses of the NAS. However, the complexity and size of the problem results in an overwhelming task for transportation system modelers. This research seeks to compose an active design algorithm for an evolutionary airline network model so as to include network specific control properties. An airline network designer, referred to as a network architect, can use this tool to assess the possibilities of gaining more capacity by changing the network configuration. Since the Airline Deregulation Act of 1978, the airline service network has evolved from a point-to-point into a distinct hub-and-spoke network. Enplanement demand on the H&S network is the sum of Origin-Destination (O-D) demand and transfer demand. Even though the flight or enplanement demand is a function of O-D demand and passenger routings on the airline network, the distinction between enplanement and O-D demand is not often made. Instead, many demand forecast practices in current days are based on scale-ups from the enplanements, which include the demand to and from transferring network hubs. Based on this research, it was found that the current demand prediction practice can be improved by dissecting enplanements further into smaller pieces of information. As a result, enplanement demand is decomposed into intrinsic and variable parts. The proposed intrinsic demand model is based on the concept of 'true' origin-destination demand which includes the direction of each round trip travel. The result from using true O-D concept reveals the socioeconomic functional roles of airports on the network. Linear trends are observed for both the produced and attracted demand from the data. Therefore, this approach is expected to provide more accurate prediction capability. With the intrinsic demand model in place, the variable part of the demand is modeled on an air transportation network model, which is built with accelerated evolution scheme. The accelerated evolution scheme was introduced to view the air transportation network as an evolutionary one instead of a parametric one. The network model takes in intrinsic demand data before undergoing an evolution path to generate a target network. The results from the network model suggests that air transportation networks can be modeled using evolutionary structure and it was possible to generate the emulated NAS. A dehubbing scenario study of Lambert-St. Louis International Airport demonstrated the prediction capability of the proposed network model. The overall process from intrinsic demand modeling and evolutionary network modeling is a unique and it is highly beneficial for simulating active control of the transportation networks.

With an increasing population of super heavy aircraft operating in the National Airspace System and with the introduction of NextGen technologies, the wake vortex problem has become more important for airport capacity and the en-route air traffic operations. The vortices generated by heavy and super heavy aircraft can generate potential hazards to other aircraft on nearby flight paths. Moreover, the design of new airport procedures needs to consider the interactions between aircraft in closer paths. New methods and models are required to examine these effects before new operations are conducted in the National Airspace System (NAS). Reducing wake vortex separations to safe levels between successive aircraft is essential for NextGen operations. One approach taken recently by ICAO and the FAA is to introduce a re-categorization (ReCat) of wake vortex separations to six groups from the existing five groups employed by the FAA in the United States. Reduced aircraft separations can increase capacity in the NAS with corresponding savings in delay times at busy airports. Future NextGen operations are likely to introduce smaller aircraft separations in the en-route and in the terminal area. Such operations would require better methods to identify potential wake hazards from reduced separation operations. This dissertation describes a model to identify potential wake encounters in the future NAS. The goal of the dissertation is to describe the Enhanced Wake Encounter Model (EWEM), a model that employs a detailed NASA-developed wake model to generate wake zones for different aircraft categories under different flight conditions that can be used with aircraft flight path data to identify potential wake encounters. The main contribution of this model is to gain an understanding of potential wake encounters under future NAS operations. / Ph. D.

Abstract: This thesis addresses the problem of graceful degradation for air traffic management systems (ATMS). The graceful degradation is the process by which the safety of the airspace is ensured in the event of failures or operational degradation in the system. After listing the main areas where failures and degradation can affect the ATMS, an ontology of the ATMS is proposed. The ontology allows to introduce failures at different levels, track their propagation throughout the system, and measure their operational impact. Then, two operational degradations are studied: The first degradation studied is a reduction in the landing capacity at San Francisco International Airport. The aircraft queueing process for terminal area is modeled and optimized to ensure a graceful degradation. The second degradation encompasses Communication, Navigation and Surveillance systems failures. The graceful degradation is ensured by increasing the spacing distance between aircraft, using novel algorithms of avoidance under uncertainties. Those algorithm also serve as probes to compare the degradation capabilities of different traffic configurations such as Miles-In-Trail and Free-Flight arrivals. Finally, this thesis focuses on monitoring the airspace for potential degradation. The ability and the difficulty of en-route traffic configuration are evaluated using degradation maps. Those maps can be used controller to rapidly and efficiently steer traffic from nominal mode of operations to mode of operations under abnormal conditions. Finally, a monitoring tool for terminal area is presented: the conformance of current flight to pre-identified typical operations is determined in real time. As the number of non-conforming aircraft increases, the complexity seen by air traffic controllers increases, and can become a threat for the airspace safety.

In response to the unparalleled growth of demand for air traffic during the past few decades, the Federal Aviation Administration (FAA) launched the Next Generation Air Transportation (NextGen) program to restructure the National Airspace System (NAS). Among the research is the focus on direct, wind optimal routing using geodesic routes and flight operations that do not depend solely on ground based navigation aids (NAVAID) and a fixed airspace structure. While technologies, such as the Global Positioning System (GPS), exist to locate an aircraft at higher degrees of resolution with a larger coverage, the way in which this information is conveyed is long and cumbersome. Therefore, new ways to describe the airspace is desired. The thesis presents the results of an experimental investigation into three alternatives to fix/route and GPS methods. The first method is the Navigation Reference System (NRS) using an absolute grid based strategy that has been recently implemented in limited portions of the United States airspace. The second method, the Military Grid Reference System (MGRS), is also a grid based system, and it is used by NATO, but it has not been applied to the air traffic control context. The third alternative is Point Relation Navigation (PRN), which uses a single point of reference within each Air Route Traffic Center (ARTCC) airspace and acts as a hybrid of coordinate and radial fixes. 21 airline dispatchers from a single major U.S air carrier participated in an online assessment of the five methods above through specific tasks. Results indicate that most participants prefer the fix/route system over the others, followed closely by the PRN method. However, there were varying results across all of the methods in terms of speed and accuracy of completing the tasks. This study incites further interest in strategies to describe aircraft routes operating in a more flexible airspace.

From 2010 to 2030, the number of instrument flight rules aircraft operations handled by Federal Aviation Administration en route traffic centers is predicted to increase from approximately 39 million flights to 64 million flights. The projected growth in air transportation demand is likely to result in traffic levels that exceed the abilities of the unaided air traffic controller in managing, separating, and providing services to aircraft. Consequently, the Federal Aviation Administration, and other air navigation service providers around the world, are making several efforts to improve the capacity and throughput of existing airspaces. Ultimately, the stated goal of the Federal Aviation Administration is to triple the available capacity of the National Airspace System by 2025. In an effort to satisfy air traffic demand through the increase of airspace capacity, air navigation service providers are considering the inclusion of advisory conflict-detection and resolution systems. In a human-in-the-loop framework, advisory conflict-detection and resolution decision-support tools identify potential conflicts and propose resolution commands for the air traffic controller to verify and issue to aircraft. A number of researchers and air navigation service providers hypothesize that the inclusion of combined conflict-detection and resolution tools into air traffic control systems will reduce or transform controller workload and enable the required increases in airspace capacity. In an effort to understand the potential workload implications of introducing advisory conflict-detection and resolution tools, this thesis provides a detailed study of the conflict event process and the implementation of conflict-detection and resolution algorithms. Specifically, the research presented here examines a metric of controller taskload: how many resolution commands an air traffic controller issues under the guidance of a conflict-detection and resolution decision-support tool. The goal of the research is to understand how the formulation, capabilities, and implementation of conflict-detection and resolution tools affect the controller taskload (system demands) associated with the conflict-resolution process, and implicitly the controller workload (physical and psychological demands). Furthermore this thesis seeks to establish best practices for the design of future conflict-detection and resolution systems. To generalize conclusions on the conflict-resolution taskload and best design practices of conflict-detection and resolution systems, this thesis focuses on abstracting and parameterizing the behaviors and capabilities of the advisory tools. Ideally, this abstraction of advisory decision-support tools serves as an alternative to exhaustively designing tools, implementing them in high-fidelity simulations, and analyzing their conflict-resolution taskload. Such an approach of simulating specific conflict-detection and resolution systems limits the type of conclusions that can be drawn concerning the design of more generic algorithms. In the process of understanding conflict-detection and resolution systems, evidence in the thesis reveals that the most effective approach to reducing conflict-resolution taskload is to improve conflict-detection systems. Furthermore, studies in the this thesis indicate that there is significant flexibility in the design of conflict-resolution algorithms.

<p>Pre obavljanja levog manevra, sa prioritetnog prilaza TWSC nesignalisane raskrsnice, vozač procenjuje interval koji se javlja u konfliktnom toku i bira onaj interval koji mu je najviše prihvatljiv. Vreme koje je potrebno za procenu prihvatljivog intervala je predstavljeno u vidu vremena čekanja u opsluzi vozila na raskrsnici. Sa pojavom prihvatljivog intervala, vreme čekanja u opsluzi vozila se završava, i tada počinje vreme za izvođenje manevra levog skretanja. Odluka o momentu početka izvođenja manevra levog skretanja je subjektivna i zasniva se na proceni vozača. Ispravna subjektivna procena uvek rezerviše bezbednosno vreme. U ovoj disertaciji je predstavljen razvoj detaljnog matematičkog postupka za proračun bezbednosnog vremena. Merenja na nesignalisanim raskrsnicama su dokazala primenjivost predloženog modela, mogućnost proračuna subjektivnog bezbednosnog vremena i visoko učešće bezbednosnog vremena u kritičnom intervalu (oko jedne trećine). Dobijeni rezultati su visoko saglasni sa HCM.</p> / <p>Before the left turn manoeuvre, from priority approach at TWSC unsignalized intersection, the driver estimates the interval occurring in the conflict flow and chooses the one which is most acceptable for him. The time required for evaluation of acceptable interval is presented by the service waiting time of vehicles at an intersection. With the appearance of an acceptable interval, service waiting time for vehicle ends, and then starts a time for performance of left turn manoeuvre. A decision about the moment of starting left turn manoeuvre is subjective and based on a driver&rsquo;s estimate. Correct subjective evaluation always reserves the safety time. This dissertation presents development of a detailed mathematical procedure for calculation form of safety time. Measurements at unsignalized intersections are proven applicability of the proposed model, possibility of calculation subjective safety time and high participation of safety time in critical gap (about one-third). The obtained results are highly consistent with HCM.</p>