928 resultados para AIR TRANSPORT MANAGEMENT


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Mode of access: Internet.

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Mode of access: Internet.

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"11 February 1991"--Vol. 2, P. i.

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Shipping list no.: 92-0610-P.

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"R6-NR-TP-14-96."

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Complex network theory is a framework increasingly used in the study of air transport networks, thanks to its ability to describe the structures created by networks of flights, and their influence in dynamical processes such as delay propagation. While many works consider only a fraction of the network, created by major airports or airlines, for example, it is not clear if and how such sampling process bias the observed structures and processes. In this contribution, we tackle this problem by studying how some observed topological metrics depend on the way the network is reconstructed, i.e. on the rules used to sample nodes and connections. Both structural and simple dynamical properties are considered, for eight major air networks and different source datasets. Results indicate that using a subset of airports strongly distorts our perception of the network, even when just small ones are discarded; at the same time, considering a subset of airlines yields a better and more stable representation. This allows us to provide some general guidelines on the way airports and connections should be sampled.

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The anticipated growth of air traffic worldwide requires enhanced Air Traffic Management (ATM) technologies and procedures to increase the system capacity, efficiency, and resilience, while reducing environmental impact and maintaining operational safety. To deal with these challenges, new automation and information exchange capabilities are being developed through different modernisation initiatives toward a new global operational concept called Trajectory Based Operations (TBO), in which aircraft trajectory information becomes the cornerstone of advanced ATM applications. This transformation will lead to higher levels of system complexity requiring enhanced Decision Support Tools (DST) to aid humans in the decision making processes. These will rely on accurate predicted aircraft trajectories, provided by advanced Trajectory Predictors (TP). The trajectory prediction process is subject to stochastic effects that introduce uncertainty into the predictions. Regardless of the assumptions that define the aircraft motion model underpinning the TP, deviations between predicted and actual trajectories are unavoidable. This thesis proposes an innovative method to characterise the uncertainty associated with a trajectory prediction based on the mathematical theory of Polynomial Chaos Expansions (PCE). Assuming univariate PCEs of the trajectory prediction inputs, the method describes how to generate multivariate PCEs of the prediction outputs that quantify their associated uncertainty. Arbitrary PCE (aPCE) was chosen because it allows a higher degree of flexibility to model input uncertainty. The obtained polynomial description can be used in subsequent prediction sensitivity analyses thanks to the relationship between polynomial coefficients and Sobol indices. The Sobol indices enable ranking the input parameters according to their influence on trajectory prediction uncertainty. The applicability of the aPCE-based uncertainty quantification detailed herein is analysed through a study case. This study case represents a typical aircraft trajectory prediction problem in ATM, in which uncertain parameters regarding aircraft performance, aircraft intent description, weather forecast, and initial conditions are considered simultaneously. Numerical results are compared to those obtained from a Monte Carlo simulation, demonstrating the advantages of the proposed method. The thesis includes two examples of DSTs (Demand and Capacity Balancing tool, and Arrival Manager) to illustrate the potential benefits of exploiting the proposed uncertainty quantification method.

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The privatization of major Australian airports in the late 1990s unleashed an unprecedented development wave as corporate lessees implemented ambitious business plans. While planning and environmental regulations governing on-airport development were significantly enhanced, there has been national disquiet about a governance regime that remains under the auspices of the federal government and is not effectively integrated into state and local decision-making machinery. Tensions in major airport regions have been exacerbated by the building of highly conspicuous non-aeronautical developments approved with no determining input by local decision-makers as well as the growing pressures on off-airport locations for aviation-related development. This paper canvasses this context and overviews the evolving structure of planning controls for Australia’s privatized federal airports. A range of issues surfacing through the National Aviation Policy Review process in 2008–2009 is described.

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Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.

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Most airports internationally have implemented customer satisfaction programs into their operations to increase non-aeronautical revenues. In the US, taxicabs are an essential airport transport mode given the limited public transport options available. Effective airport taxicab planning can increase airport customer satisfaction levels, as well as facilitate handling increased airport passenger volumes. However, little is known on how US airports have adapted their governance practices from a traditional hierarchical to a network approach in their efforts to undertake airport taxicab planning initiatives since the deregulation of the transportation industry. Data acquired from 51 US hub airports is used to examine their existing taxicab planning practices. The findings offer how US airports can modify governance processes in their airport taxicab planning processes to better support increases in the customer satisfaction levels of airport taxicab patrons.

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In recent years, airlines have been servicing a greater variety, and increasing numbers, of disabled persons and persons with reduced mobility (PRMs), particularly associated with ageing, obesity and medical needs. With the quantity of PRMs likely to increase in the future, there will be a growing impact on the airlines' associated actual and opportunity costs, about which there is minimal literature and data. Therefore the aim of this paper is to identify standard functional key factors (FKFs) with which airlines could audit their PRMs costs, and which could be used by other interested bodies, such as governments, when considering relevant aviation policy. These FKFs are related to nine areas, namely PRMs’ transfers; mobility aids; aircraft delays/diversions costs; staff training costs; staff health, safety and welfare; aircraft fixtures and equipment costs; airport costs; transaction costs; and opportunity costs. Further research is needed to obtain the data for these FKFs.

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Contents 1.What kind of airlines? 2. Network Planning – Data – Generic / traditional – Low cost 1.What kind of airlines? 2. Network Planning – Data – Generic / traditional – Low cost