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No description available.

The international civil aviation system is currently going through a transitional phase. Deregulation and liberalization of air transport services and privatisation of certain airlines have contributed to the modification of the aviation landscape. In this context, airline alliances play a crucial role. Both the US and EC authorities have been supportive of airline alliances because they believe that alliances have the potential to increase competition and to provide the consumers with benefits. / The first part of this thesis intends to provide economic and historical background to highlight the reasons for the multiplication of alliances, as well as the political and economic circumstances under which competition authorities assess alliances. The second part of this thesis is meant to determine which legal regime is applied to transatlantic alliances, and whether alliances are assessed like agreements among companies in any other business sector. The third part focuses more specifically on the antitrust control of the Sky Team alliance which occurs in the context of the EU/US Open skies agreement.

This thesis addresses two planning problems motivated by the operations of PSOD air transportation: scheduled maintenance planning, and base location and fleet allocation. In the first part of the thesis, we study tactical planning for scheduled maintenance which determines the daily maintenance capacities for two operating conditions: a growth phase and the steady state. We model tactical maintenance capacity planning during the growth phase as an integer program and develop an optimization-based local search to solve the problem. Tactical planning of steady state maintenance capacity concerns a special case for which we determine the optimal and the long run capacities with a pseudo-polynomial time algorithm. In the second part of the thesis, we address operational planning for scheduled maintenance which is concerned with assigning itineraries to jets and determining the specific jets to be scheduled for maintenance on a daily basis given a certain maintenance capacity. We present a solution methodology that employs a look-ahead approach to consider the impact of our current decisions on the future and decomposes the problem exploiting the differences between jets with respect to the proximity to their next maintenance. We further develop an integrated framework in order to capture the interaction between operational level maintenance decisions and flight scheduling. In the third and final part of the thesis, we present the tactical level base location and fleet allocation problem. As PSOD air transportation experiences changes in travel demand and fleet size, decisions regarding where to open new bases and how to allocate the number of jets among the bases are made. We first present a solution approach in which high level information about flight scheduling is used in a traditional facility location problem. We next develop a model that works directly with transportation requests and integrates a simplified version of flight scheduling with the base location and fleet allocation decisions in order to capture more detail.

No description available.

The deregulation of the airline industry created a myriad of changes in the U.S. air transport system that has both defended and sparked debate on the wisdom of such policy change for over three decades. One of the promises of deregulation from its proponents in the 1970s was increased competition that would lead to a reduction in fares for consumers. Historic data and literature has indeed shown this to be to the case as average airfares have trended downward especially over the last twenty years. Nonetheless, the industry has become much more complex since deregulation in terms of pricing to the point that very sophisticated yield management computer models are used to achieve an optimum balance between load factors and price. Consequently, this has in turn translated into a haphazard experience for most air travelers in the United States; for instance, the cost of a ticket is sometimes lower traveling from coast to coast than within a particular region of the U.S. and paid fares for the exact same trip can deviate dramatically, often based on variation in the date of purchase. Additionally, this has also resulted in a spatial pattern where certain regions throughout the country have enjoyed lower airfares more so than others. This research seeks to identify this regional disparity using a geographically weighted regression and spatial autoregressive models in a sample of 6,200 routes between 80 primary U.S. airports. The results from the global model showed that variables which measure competition (airlines), operating cost (flights, distance) and elasticity (layover time) proved to be statistically significant and had a positive relationship with airfare The GWR results indicated that while some factors like distance, and hub size, were statistically significant almost nationwide, other factors such as frequency, presence of low cost carriers, and numbers of airlines were only statistically significant at certain airports. Finally, the spatial regressions models indicate that the spatial autocorrelation found in U.S. airfares resemble the first order properties of spatial autocorrelation (i.e. spatial heterogeneity) and not the second order properties (i.e. spatial dependence). / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2014. / FAU Electronic Theses and Dissertations Collection

The air transportation system plays a crucial role in modern society, comprising a major industrial sector as well as a key driver for adjacent economies. Moreover, it is a prime enabler of the modern way of life, characterized by access to products and services from around the world, and access to remote locations. Therefore there is a strong incentive to maintain the system and promote its growth. None the less, important challenges have plagued civil aviation, particularly the commercial aviation sector. On one hand, demand for air travel has grown dramatically and at an accelerated pace, in part due to the deregulation of airlines in 1978, providing airlines with the freedom to arrange their operational schedule freely and compete for markets. The dynamic nature of demand and its fast-paced growth contrasts with the relative rigidity of air transportation infrastructure development and the sluggish evolution of its operational architecture. The supply-demand mismatch that results has led to degradation in system efficiency, excessive delays, and substantial economic losses. This phenomenon is particularly exacerbated in the terminal area of major airports which have inevitably become operational choke points. On the other hand the environmental impact of air transportation, embodied primarily by the emissions and noise caused by aircraft operations, has also grown as a result of the increase in aviation activity, and has therefore become a major issue of public interest. Airport communities experience said environmental impact most intensely, particularly those associated with bottleneck airports, and thus represent a uniquely strong force opposing further expansion of air transportation in these areas where it is most needed. Past efforts to address these challenges have been notably stovepiped and have failed to recognize the importance of the relationship between the operational nature of the system and its environmental impact. Only recently have research efforts begun to incorporate a joint view of the operational-environmental problem that attempts to formulate solutions accordingly. However, the state of the art has yet to answer some of the most fundamental questions. First, the relationship between operational and environmental elements has not been quantified conclusively. Doing so is vital to understand the operational-environmental nature of terminal areas before any solutions can be considered. Secondly, many different types of solution alternatives have been proposed, such as the construction of new runways, redesign of operational procedures, introduction of advanced aircraft concepts, and transformation of airspace capabilities. However, a direct comparison between dissimilar alternatives that accounts for operational and environmental issues is rarely found, and yet remains crucial in the formulation of a solution portfolio. More importantly, the additive and countervailing interactions that different solutions have on each other are widely recognized but remain, for the most part, unknown. Because all solutions under consideration require an extended period of time to develop and represent very large economic commitments, the selection of a portfolio demands a careful look at the future to determine the adequate measures that should be pursued in the present. In response to this methodological need, this thesis proposes a strategic planning approach to investigate the operational-environmental nature of the air transportation system, as well as the adequacy of solution alternatives for terminal areas in the formulation of a portfolio. The state of the art currently incorporates elements of strategic planning, but has yet to address two important methodological gaps. First, the inherent systemic complexity of airport performance obfuscates its quantitative characterization, which is paramount in attaining adequate insight and understanding to support informed strategic decision-making in the selection of terminal area solutions. Second, there is significant uncertainty about the evolution of the aviation demand and its operational context, making the use of forecasts grossly inadequate for this application. A scenario-based approach is used in its place, but the current frameworks for the generation, evaluation, and selection of an adequate scenario set currently lack traceability and methodological rigor. To address the first gap, this thesis proposes the use of well established statistical analysis techniques, leveraging on recent developments in interactive data visualization capabilities, to quantitatively characterize the interactions, sensitivities, and tradeoffs prevalent in the complex behavior of airport operational and environmental performance. Within the strategic airport planning process, this approach is used in the assessment of airport performance under current/reference conditions, as well as in the evaluation of terminal area solutions under projected demand conditions. More specifically, customized designs of experiments are utilized to guide the intelligent selection and definition of modeling and simulation runs that will yield greater understanding, insight, and information about the inherent systemic complexity of a terminal area, with minimal computational expense. Regression analysis leverages the creation of response surface equations that explicitly and quantitatively capture the behavior of system metrics of interest as functions of factors or terminal area solutions. This explicit mathematical characterization enables a variety of interactive visualization schemes that allow analysts and decision makers to confirm or rectify expected patterns of behavior, and to discover the unknown and the unexpected. Said visualization schemes are also instrumental in communicating, in a very direct and succinct fashion, complex relationships, sensitivities, tradeoffs, and interactions, that would be otherwise too complex to explain or communicate transparently. More importantly, this approach provides a rigorous and formalized mathematical framework within which the statistical significance of different factors or terminal area solutions can be quantitatively and explicitly assessed, primarily by means of statistical hypotheses testing of regression parameter estimates, such as the analysis of variance, or the t-statistic test. This proposed approach does not suggest a new strategic planning process, but rather improves specific steps pertaining to performance assessments, and builds upon established practices and the recommended planning process for airports to leverage on the decades of experience supporting the existing strategic airport planning paradigm. On the other hand, the proposed approach recognizes the methodological limitations and constraints that lead to the lack of terminal area performance characterization within the strategic planning process, embodied primarily by computational constraints and unmanageable systemic complexity, and directly addresses these shortcomings by incorporating mature statistical analysis techniques into key steps of said process. In turn, the proposed approach represents a novel adaptation of the strategic airport planning process that results in greater knowledge, insight, and understanding, at a resource cost comparable to current airport planning practices. As such, this proposed approach is demonstrated using the Atlanta Hartsfield-Jackson International Airport as a representative test case, and constitutes a contribution to strategic airport planning given that it supports strategic decision making by revealing, at an acceptable analysis and computational expense, the various sensitivities, interactions, and tradeoffs of interest in operational-environmental performance that would otherwise remain implicit and obfuscated by systemic complexity. For the research documented in this thesis, a modeling and simulation environment was created featuring three primary components. First, a generator of schedules of operations, based primarily on previous work on aviation demand characterization, whereby growth factors and scheduling adjustment algorithms are applied on appropriate baseline schedules so as to generate notional operational sets representative of consistent future demand conditions. The second component pertains to the modeling and simulation of aircraft operations, defined by a schedule of operations, on the airport surface and within its terminal airspace. This component is a discrete event simulator for multiple queuing models that captures the operational architecture of the entire terminal area along with all the necessary operational logic pertaining to simulated ATC functions, rules, and standard practices. The third and final component is comprised of legacy aircraft performance, emissions and dispersion, and noise exposure modeling tools, that use the simulation history of aircraft movements to generate estimates of fuel burn, emissions, and noise. A set of designed modeling and simulation experiments were conducted to examine the interactions between exogenous and endogenous factors, as well as their main and quadratic effect, on operational metrics such as delay, and on fuel burn as the primary environmental metrics. Results show that for a gate-hold scheme used to manage surface traffic density, the departure queue threshold features a statistically significant interaction with the increasing number of operations, but that otherwise the relative percent change in the number of operations remains as the predominant exogenous factor driving operational and environmental performance. A separate design of modeling and simulation experiments was conducted to test the statistical significance of proposed geographical regional categories that could potentially be used to classify operations and capture operational demand characteristics such as fleet mix, time of day distribution, and arrival/departure route distribution. Results show that whereas the proposed categorization is statistically significant for a few metric of interest, marginally significant for others, and not statistically significant for most metrics, the proposed regional classification scheme is not appropriate for operational demand characterization. The implementation of the proposed approach for the assessment of terminal area solutions incorporates the use of discrete response surface equations, and eliminates the use of quadratic terms that have no practical significance in this context. Rather, attention is entire placed on the main effects of different terminal area solutions, namely additional airport infrastructure, operational improvements, and advanced aircraft concepts, modeled as discrete independent variables for the regression model. Results reveal that an additional runway and a new international terminal, as well as reduced aircraft separation, have a major effect on all operational metrics of interest. In particular, the additional runway has a dominant effect for departure delay metrics and gate hold periods, with moderate interactions with respect to separation reduction. On the other hand, operational metrics for arrivals are co-dependent on additional infrastructure and separation reduction, featuring marginal improvements whenever these two solutions are implemented in isolation, but featuring a dramatic compounding effect when implemented in combination. The magnitude of these main effects for departures and of the interaction between these solutions for arrivals is confirmed through appropriate statistical significance testing. Finally, the inclusion o advanced aircraft concepts is shown to be most beneficial for airborne arrival operations and to a lesser extent for arrival ground movements. More specifically, advanced aircraft concepts were found to be primarily responsible for reductions in volatile organic compounds, unburned hydrocarbons, and particulate matter in this flight regime, but featured relevant interactions with separation reduction and additional airport infrastructure. To address the second gap, pertaining to the selection of scenarios for strategic airport planning, a technique for risk-based scenario construction, evaluation, and selection is proposed, incorporating n-dimensional dependence tree probability approximations into a morphological analysis approach. This approach to scenario construction and downselection is a distinct and novel contribution to the scenario planning field as it provides a mathematically and explicitly testable definition for an H parameter, contrasting with the qualitative alternatives in the current state of the art, which can be used in morphological analysis for scenario construction and downselection. By demonstrating that dependence tree probability product approximations are an adequate aggregation function, probability can be used for scenario construction and downselection without any mathematical or methodological restriction on the resolution of the probability scale or the number of morphological alternatives that have previously plagued probabilization and scenario downselection approaches. In addition, this approach requires expert input elicitation that is comparable or less than the current state of the art practices.

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.

It is of nearly universal acceptance that one of the pillars of American economic success over the course of the 20th century was the rapid development of infrastructure. Transportation infrastructure has been of particular importance in the rise of the United States and attributed to the spread of an increasingly mobile culture. Americans undoubtedly enjoy traveling, and the ability to do so with relative ease is of immense value to many. In Texas, the majority of economic activity takes place within what is colloquially known as the “Texas Triangle”, an area bounded by the large metropolitan areas of Houston, Dallas-Ft. Worth, and San Antonio. Intensive population growth in Texas, anchored by the triangle, has led to increasing road congestion on many routes, especially along Interstates 35 and 10. This congestion, and the wasted time and money that comes with it, are of increasing concern to the future economic vitality of the state. The Texas Triangle is also served by extensive aviation links via major airports in the major metropolitan areas, as well as smaller airports in other parts of the region. These flights, operated by American Airlines, Continental Airlines, and Southwest Airlines are frequent, but emit large amounts of greenhouse gases that contribute to ground level pollution and possibly climate change. High-speed rail has been considered by many to be a superior environmental option for intercity routes with lengths inherent to the Texas Triangle. However, given the fact that Texas is the top emitter of carbon dioxide in the U.S. and relies on an energy mix that is primarily fossil fuel powered; would a potential high-speed rail in Texas outperform the current air system environmentally, given similar passenger miles traveled? This report examines the environmental emissions of high-speed rail and compares it to the environmental emissions of our current aviation system, taking into account a life-cycle perspective. / text