Trajectory Mathematical Distance Applied to Airspace Major Flows Extraction

Daniel Delahaye 1 Stéphane Puechmorel 1 Sameer Alam 2 Eric Féron 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 : airspace major flows hierarchical clustering energy Distance homotopy trajectory
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Conference papers
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Daniel Delahaye, Stéphane Puechmorel, Sameer Alam, Eric Féron. Trajectory Mathematical Distance Applied to Airspace Major Flows Extraction. EIWAC 2017, 5th ENRI International Workshop on ATM/CNS, ENRI, Nov 2017, Tokyo, Japan. pp. 51-66., ⟨10.1007/978-981-13-7086-1_4⟩. ⟨hal-01598864⟩

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