Large Scale Adaptive 4D Trajectory Planning - ENAC - École nationale de l'aviation civile Accéder directement au contenu
Communication Dans Un Congrès Année :

Large Scale Adaptive 4D Trajectory Planning


Global air-traffic demand is continuously increasing. To handle such a tremendous traffic volume while maintaining at least the same level of safety, a more efficient strategic trajectory planning is necessary. Static 4D trajectory planning with constant 4D segments, where aircraft have to stay all along their flights, ensures a strong predictability of traffic and may reduce congestion in airspace. The main limitation of this approach is linked to the 4D constraint associated to aircraft. As a matter of fact, each aircraft has to comply to this 4D segment to maintain separation from other aircraft, but this induces a real control of the engine in order to stay all the time in this 4D segment. This could result in extra fuel consumption and shorter engine life. In this work, we present an adaptive 4D strategic trajectory planning methodology which aims to minimize interaction between aircraft at the European-continent scale. The main purpose of this work is to associate to each aircraft a 4D bubble which is adapted to the current traffic situation. When aircraft are located in low density areas, the size of such bubbles can extend (with a maximum range of 20 minutes) and when aircraft enter high congestion areas, such bubbles can shrink until a minimum size of 2 minutes. The size of bubbles is then optimized according to the local density of aircraft. This adaptive process, avoid to constrain aircraft in 4D all along their trajectories. The proposed methodology separates aircraft by modifying their trajectories and departure times. This route/departure-time assignment problem is modeled as a mixed-integer optimization problem. Due to the very high combinatorics involved in the continent-scale context (involving more than 30,000 flights), we develop and implement a hybrid-metaheuristic optimization algorithm. This first optimization is done with a minimum bubble size of 2 minutes. A second optimization loop uses the solution produced by the first algorithm in order to optimally extend the size of the 4D bubbles along trajectories in order to minimize the time constraint of aircraft. Index Terms-air traffic management, 4D aircraft trajectory, strategic planning, adaptive trajectory planning
Fichier principal
Vignette du fichier
dmg_dasc2018.pdf (2.3 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01887286 , version 1 (03-10-2018)


  • HAL Id : hal-01887286 , version 1


Pierre Dieumegard, Supatcha Chaimatanan, Daniel Delahaye. Large Scale Adaptive 4D Trajectory Planning. DASC 2018, 37th AIAA/IEEE Digital Avionics Systems Conference, Sep 2018, Londres, United Kingdom. ⟨hal-01887286⟩
296 Consultations
195 Téléchargements


Gmail Facebook Twitter LinkedIn More