Entropy minimizing curves with application to flight path design and clustering *

Abstract : Air traffic management (ATM) aims at providing companies with a safe and ideally optimal aircraft trajectory planning. Air traffic controllers act on flight paths in such a way that no pair of aircraft come closer than the regulatory separation norms. With the increase of traffic, it is expected that the system will reach its limits in a near future: a paradigm change in ATM is planned with the introduction of trajectory based operations. In this context, sets of well separated flight paths are computed in advance, tremendously reducing the number of unsafe situations that must be dealt with by controllers. Unfortunately, automated tools used to generate such plannings generally issue trajectories not complying with operational practices or even flight dynamics. In this paper, a mean of producing realistic air routes from the output of an automated trajectory design tool is investigated. For that purpose, the entropy of a system of curves is first defined and a mean of iteratively minimizing it is presented.The resulting curves form a route network that is suitable for use in a semi-automated ATM system with human in the loop. The tool introduced in this work is quite versatile and may be applied also to unsupervised classification of curves: an example is given for the french traffic.
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Stéphane Puechmorel, Florence Nicol. Entropy minimizing curves with application to flight path design and clustering *. Entropy, MDPI, 2016, Special Issue Differential Geometrical Theory of Statistics, 18 (9), pp.337. ⟨10.3390/e18090337⟩. ⟨hal-01349675⟩

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