Trajectory Mathematical Distance Applied to Airspace Major Flows Extraction

Daniel Delahaye 1 Stéphane Puechmorel 1 Sameer Alam 2 Eric Féron 1, 3
1 ENAC - Ecole Nationale de l'Aviation Civile
2 Nanyang Technological University [Singapour]
3 Georgia Institute of Technology [Atlanta]
Abstract : In this paper, the problem of aircraft trajectories representation and analysis is addressed. In many operational situations, there is a need to have a value expressing how trajectories are close to each other. Some measures have been previously defined, mainly for trajectory prediction applications, all of them being based on distance computations at given positions in space and time. The approach presented here is to consider the trajectory as a whole object belonging to a functional space and to perform all computations in this space. An efficient algorithm for computing mathematical distance between trajectories is then presented and applied to the major flows extraction in the French airspace.
Keywords : Distance trajectory homotopy energy hierarchical clustering airspace major flows
Type de document :
Communication dans un congrès
EIWAC 2017 The 5th ENRI International Workshop on ATM/CNS, Nov 2017, Tokyo, Japan. Springer, Lecture Notes in Electrical Engineering, 2018, Air Traffic Management and Systems III
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Soumis le : samedi 18 novembre 2017 - 18:45:16
Dernière modification le : lundi 11 juin 2018 - 11:14:13
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Daniel Delahaye, Stéphane Puechmorel, Sameer Alam, Eric Féron. Trajectory Mathematical Distance Applied to Airspace Major Flows Extraction. EIWAC 2017 The 5th ENRI International Workshop on ATM/CNS, Nov 2017, Tokyo, Japan. Springer, Lecture Notes in Electrical Engineering, 2018, Air Traffic Management and Systems III. 〈hal-01598864〉

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