Civil & Environmental Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/2221
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Item Extracting capacity metrics for General Aviation airports from ADS-B data(2021) Mitkas, Danae Zoe; Lovell, David J; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)General Aviation airports play a pivotal role in the aviation system of the US, with over 5000 small airports existing and operating across the country. Serving almost exclusively small aircraft, these airports have a unique activity profile, compared to larger commercial airports. Like their larger cousins, they occasionally see the need to apply for federal funding for capacity enhancement projects, a process that requires rigorous documentation of the demand and capacity situation at the airport. Existing models for capacity estimation have been calibrated to reflect the much larger scale features that dominate large airports. The main challenge is to develop a method to provide precise data for small airports that operate mainly with small single or multi-engine aircraft. These airports are typically not towered and, hence, do not benefit from traditional automated data collection technologies. This research addresses the issues of a) collecting aircraft data at local airport environments from aircraft equipped with Automated Dependent Surveillance – Broadcast (ADS-B) technology, b) processing the data to determine and classify flights, and c) assessing elements of the operational performance of these aircraft. The thesis proposes a method to extract aircraft approach speeds and runway occupancy times, which are important contributors to capacity estimation. We applied and validated our method in three small airports.Item Mechanisms for Trajectory Options Allocation in Collaborative Air Traffic Flow Management(2018) Mohanavelu Umamagesh, Prithiv Raj; Lovell, David J; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Flight delays are primarily due to traffic imbalances caused by the demand for airspace resource exceeding its capacity. The capacity restriction might be due to inclement weather, an overloaded air traffic sector, or an airspace restriction. The Federal Aviation Administration (FAA), the organization responsible for air traffic control and management in the USA, has developed several tools known as Traffic Management Initiatives (TMI) to bring the demand into compliance with the capacity constraints. Collaborative Trajectory Option Program (CTOP) is one such tool that has been developed by the FAA to mitigate the delay experienced by flights. Operating under a Collaborative Decision Making (CDM) environment, CTOP is considered as the next step into the future of air traffic management by the FAA. The advantages of CTOP over the traditional the TMIs are unequivocal. The concerns about the allocation scheme used in the CTOP and treatment of flights from the flight operators/airlines have limited its usage. This research was motivated by the high ground delays that were experienced by flights and how the rerouting decisions were made in the current allocation method used in a CTOP. We have proposed four alternative approaches in this thesis, which incorporated priority of flights by the respective flight operator, aimed at not merely reducing an individual flight operator’s delay but also the total delay incurred to the system. We developed a test case scenario to compare the performances of the four proposed allocation methods against one another and with the present allocation mechanism of CTOP.Item AVIATION CONGESTION MANAGEMENT IMPROVEMENTS IN MODELING THE PREDICTION, MITIGATION, AND EVALUATION OF CONGESTION IN THE NATIONAL AIRSPACE SYSTEM(2014) Vlachou, Kleoniki; Lovell, David J.; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)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.