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Full-Text Articles in Navigation, Guidance, Control and Dynamics
Air Navigation And Covid-19: Atm Efficiency In Pandemic Crisis, Fabio Lourenco Carneiro Barbosa
Air Navigation And Covid-19: Atm Efficiency In Pandemic Crisis, Fabio Lourenco Carneiro Barbosa
Graduate Student Works
The coronavirus crisis effects on aviation in 2020 are currently well-documented. Nonetheless, the widely registered low traffic due to the crisis does not necessarily lead to increased air navigation efficiency. Thus, the present work, developed to fulfill the program outcomes for the Master of Science in Aeronautics, Air Traffic Management (ATM) specialization, aimed to investigate what was the impact of the COVID-19 crisis on air navigation efficiency in Brazil. This research question was addressed through a quantitative, nonexperimental, observational approach with two parallel branches, designed to answer two sub-questions. For the first, regarding what was the impact of the crisis …
Leveraging Aircraft Transponder Signals For Measuring Aircraft Fleet Mix At Non-Towered Airports, Chuyang Yang, John Mott, Darcy M. Bullock
Leveraging Aircraft Transponder Signals For Measuring Aircraft Fleet Mix At Non-Towered Airports, Chuyang Yang, John Mott, Darcy M. Bullock
International Journal of Aviation, Aeronautics, and Aerospace
The general aviation sector has contributed significantly to the overall growth of the aviation industry. Fleet mix and operations information is important for the analysis of both the safety and the environmental and economic impact of general aviation activity. Factual data on the impact of environment and safety is particularly important, given the scarcity of airport improvement funds and the strong stakeholder engagement that often occurs when airport investments are evaluated. The research presented herein evaluates Mode S short and extended squitter data collected from three general aviation airports over a one-month period. This article demonstrates that by utilizing the …
Predictability Improvement Of Scheduled Flights Departure Time Variation Using Supervised Machine Learning, Deepudev Sahadevan, Palanisamy Ponnusamy Dr, Manjunath K. Nelli Mr, Varun P. Gopi Dr
Predictability Improvement Of Scheduled Flights Departure Time Variation Using Supervised Machine Learning, Deepudev Sahadevan, Palanisamy Ponnusamy Dr, Manjunath K. Nelli Mr, Varun P. Gopi Dr
International Journal of Aviation, Aeronautics, and Aerospace
The departure time uncertainty exacerbates the inaccuracy of arrival time estimation and demand for arrival slots, particularly for movements to capacity constrained airports. The Estimated Take-Off Time (ETOT) or Estimated Departure Time(ETD) for each individual flight is currently derived from Air Traffic Flow Management System (ATFMS), which are solely determined based on individual flight plan Estimated Off Block Time(EOBT) or subsequent delays updated by Airline. Even if normal weather conditions prevail, aircraft departure times will differ from ETOTs determined by the ATFMS due to a number of factors such as congestion, early/delayed inbound flight (linked flights), reactionary delays and air …