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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Data analytics for trajectory selection and preference-model extrapolation in the European airspace
AU - Lancia, Carlo
AU - De Giovanni, Luigi
AU - Lulli, Guglielmo
PY - 2019/8/30
Y1 - 2019/8/30
N2 - 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 unknownfactors (en-route charges, fuel consumption, weather, etc.). Associationsbetween 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.
AB - 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 unknownfactors (en-route charges, fuel consumption, weather, etc.). Associationsbetween 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.
KW - Air traffic flow management
KW - Data analytics
KW - Mathematical models
KW - Airspace users’ preferences
U2 - 10.1007/978-3-030-18500-8_70
DO - 10.1007/978-3-030-18500-8_70
M3 - Conference contribution/Paper
SN - 9783030184995
T3 - Open Research Proceedings
SP - 563
EP - 570
BT - Operations Research Proceedings 2018
A2 - Fortz, Bernard
A2 - Labbe', Martine
PB - Springer
CY - Cham
ER -