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A New Representation of Air Traffic Data Adapted to Complexity Assessment

Authors :
Georges Mykoniatis
Florence Nicol
Stéphane Puechmorel
Ecole Nationale de l'Aviation Civile ( ENAC )
Ecole Nationale de l'Aviation Civile (ENAC)
Nicol, Florence
Source :
ALLDATA 2018, The Fourth International Conference on Big Data, Small Data, Linked Data and Open Data, ALLDATA 2018, The Fourth International Conference on Big Data, Small Data, Linked Data and Open Data, Apr 2018, Athenes, Greece. pp. 28-33/ISBN: 978-1-61208-631-6, 2018, ALLDATA 2018 Proceedings, ALLDATA 2018, The Fourth International Conference on Big Data, Small Data, Linked Data and Open Data, Apr 2018, Athenes, Greece. pp. 28-33/ISBN: 978-1-61208-631-6, HAL
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

Abstract

International audience; Air traffic is generally characterized by simple indicators like the number of aircraft flying over a given area or the total distance flown during a time window. As an example, these values may be used for estimating a rough number of air traffic controllers needed in a given control center or for performing economic studies. However, this approach is not adapted to more complex situations such as those encountered in airspace comparison or air traffic controllers training. An innovative representation of the traffic data, relying on a sound theoretical framework, is introduced in this work. It will pave the way to a number of tools dedicated to traffic analysis. Based on an extraction of local covariance, a grid with values in the space of symmetric positive definite matrices is obtained. It can serve as a basis of comparison or be subject to filtering and selection to obtain a digest of a traffic situation suitable for efficient complexity assessment.

Details

Language :
English
ISBN :
978-1-61208-631-6
ISBNs :
9781612086316
Database :
OpenAIRE
Journal :
ALLDATA 2018, The Fourth International Conference on Big Data, Small Data, Linked Data and Open Data, ALLDATA 2018, The Fourth International Conference on Big Data, Small Data, Linked Data and Open Data, Apr 2018, Athenes, Greece. pp. 28-33/ISBN: 978-1-61208-631-6, 2018, ALLDATA 2018 Proceedings, ALLDATA 2018, The Fourth International Conference on Big Data, Small Data, Linked Data and Open Data, Apr 2018, Athenes, Greece. pp. 28-33/ISBN: 978-1-61208-631-6, HAL
Accession number :
edsair.dedup.wf.001..8ff699c092000bd12f76ca7d6c82feb1