Trajectory deconfliction with constraint programming

As acknowledged by the SESAR (Single European Sky ATM (Air Traffic Management) Research) program, current Air Traffic Control (ATC) systems must be drastically improved to accommodate the predicted traffic growth in Europe. In this context, the Episode 3 project aims at assessing the performance of new ATM concepts, like 4D-trajectory planning and strategic deconfliction. One of the bottlenecks impeding ATC performances is the hourly capacity constraints defined on each en-route ATC sector to limit the rate of aircraft. Previous works were mainly focused on optimizing the current ground holding slot allocation process devised to satisfy these constraints. We propose to estimate the cost of directly solving all conflicts in the upper airspace with ground holding, provided that aircraft were able to follow their trajectories accurately. We present a Constraint Programming model of this large-scale combinatorial optimization problem and the results obtained with the FaCiLe (Functional Constraint Library). We study the effect of uncertainties on the departure time and estimate the cost of improving the robustness of our solutions with the Complete Air Traffic Simulator (CATS). Encouraging results were obtained without uncertainty but the costs of robust solutions are prohibitive. Our approach may however be improved, for example, with a prior flight level allocation and the dynamic resolution of remaining conflicts with one of CATS' modules.

[1]  Nicolas Barnier,et al.  Slot allocation with constraint programming : models and results , 2001 .

[2]  K. Guittet,et al.  Selection and Evaluation of Air Traffic Complexity Metrics , 2006, 2006 ieee/aiaa 25TH Digital Avionics Systems Conference.

[3]  Nicolas Barnier,et al.  4D-trajectory deconfliction through departure time adjustment , 2009 .

[4]  Géraud Granger.  Détection et résolution de conflits aériens : Modélisations et analyse , 2002 .

[5]  Nicolas Durand,et al.  CATS: A Complete Air Traffic Simulator , 1997, 16th DASC. AIAA/IEEE Digital Avionics Systems Conference. Reflections to the Future. Proceedings.

[6]  Jean-Marc Alliot,et al.  OPTIMAL RESOLUTION OF EN ROUTE CONFLICTS. , 1995 .

[7]  Pascal Van Hentenryck,et al.  Constraint Satisfaction Using Constraint Logic Programming , 1992, Artif. Intell..

[8]  Stephen Anderson,et al.  Evaluating the true cost to airlines of one minute of airborne or ground delay: final report , 2004 .

[9]  Mark de Berg,et al.  Computational geometry: algorithms and applications , 1997 .

[10]  Nico Roos,et al.  Fourth International Workshop on Integration of AI and OR techniques in Constraint Programming for Combinatorial Optimisation Problems , 2002 .

[11]  Philippe Baptiste,et al.  Airspace Sectorization By Constraint Programming , 2003, RIVF.

[12]  Nicolas Durand,et al.  Failures in the automation of air traffic control , 2005 .

[13]  Edward Tsang,et al.  Constraint Based Scheduling: Applying Constraint Programming to Scheduling Problems , 2003, J. Sched..

[14]  Pierre Flener,et al.  Air-Traffic Complexity Resolution in Multi-Sector Planning , 2007 .

[15]  Nicolas Barnier.  Application de la programmation par contraintes à des problèmes de gestion du trafic aérien , 2002 .