Data analytics for trajectory selection and preference-model extrapolation in the European airspace

Lancia, Carlo and De Giovanni, Luigi and Lulli, Guglielmo (2019) Data analytics for trajectory selection and preference-model extrapolation in the European airspace. In: Operations Research Proceedings 2018 : Selected Papers of the Annual International Conference of the German Operations Research Society (GOR), Brussels, Belgium, September 12-14, 2018. Open Research Proceedings . Springer, Cham, pp. 563-570. ISBN 9783030184995

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Representing airspace users’ preferences in Air Traffic Flow Management (ATFM) mathematical models is becoming of high relevance. ATFM models aim to reduce congestion (en-route and at both departure and destination airports) and maximize the Air Traffic Management (ATM) system efficiency by determining the best trajectory for each aircraft. In this framework, the a-priori selection of possible alternative trajectories for each flight plays a crucial role. In this work, we analyze initial trajectories queried from Eurocontrol DDR2 data source. Clustering trajectories yields groups that are homogeneous with respect to known (geometry of the trajectory, speed) and partially known or unknown factors (en-route charges, fuel consumption, weather, etc.). Associations between grouped trajectories and potential choice-determinants are successively explored and evaluated, and the predictive value of the determinants is finally validated. For a given origin-destination pair, this ultimately leads to determining a set of flight trajectories and information on related airspace users’ preferences.

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?? air traffic flow managementdata analyticsmathematical modelsairspace users’ preferences ??
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22 Feb 2019 12:00
Last Modified:
29 Nov 2023 00:49