In this paper, we focus on designing efficient 4D trajectories for the planning phase of Air Traffic Flow Management (ATFM). A key feature of the proposed approach is the inclusion of stakeholders’ preferences and priorities. In particular, we have implemented two priority mechanisms recently developed by Eurocontrol, namely the Fleet Delay Reordering and the Margins. For this purpose, we have customized a multi-objective binary program for the ATFM problem taking into account the specific assumptions required for the ATFM planning phase. To compute the Pareto frontier in a reasonable computational time, we have developed a simulated annealing algorithm. The algorithm has been tested on an instance resembling real world conditions using data extracted from the Eurocontrol data repository. This instance involves four major European airports and their air traffic in one of the busiest days of year 2016, and precisely, October 3rd. The simulated annealing algorithm has shown good computational performances and has provided a good approximation of the Pareto optimal frontier. The results have been validated using Eurocontrol tools and have demonstrated the viability of the proposed approach. Practitioners and stakeholders’ representatives have provided positive feedback on the proposed modeling approach and on the inclusion of ATM stakeholders’ preferences and priorities.

Planning efficient 4D trajectories in Air Traffic Flow Management

Veronica Dal Sasso;Guglielmo Lulli
;
2019

Abstract

In this paper, we focus on designing efficient 4D trajectories for the planning phase of Air Traffic Flow Management (ATFM). A key feature of the proposed approach is the inclusion of stakeholders’ preferences and priorities. In particular, we have implemented two priority mechanisms recently developed by Eurocontrol, namely the Fleet Delay Reordering and the Margins. For this purpose, we have customized a multi-objective binary program for the ATFM problem taking into account the specific assumptions required for the ATFM planning phase. To compute the Pareto frontier in a reasonable computational time, we have developed a simulated annealing algorithm. The algorithm has been tested on an instance resembling real world conditions using data extracted from the Eurocontrol data repository. This instance involves four major European airports and their air traffic in one of the busiest days of year 2016, and precisely, October 3rd. The simulated annealing algorithm has shown good computational performances and has provided a good approximation of the Pareto optimal frontier. The results have been validated using Eurocontrol tools and have demonstrated the viability of the proposed approach. Practitioners and stakeholders’ representatives have provided positive feedback on the proposed modeling approach and on the inclusion of ATM stakeholders’ preferences and priorities.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3288839
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