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Study of interactions between two consecutive layers of ATM under increased traffic.Results highlight an exponential growth in delay costs if constant network capacity.Results highlight an unmanageable controller workload if network capacity is high.We find a compromise by controlling delay costs growth with a sector capacity growth.We quantify research objectives for future work on air traffic control optimization. Air traffic in Europe is predicted to increase considerably over the next decades. In this context, we present a study of the interactions between the costs due to ground-holding regulations and the costs due to en-route air traffic control. We dulator that considers the regulation delays, aircraft trajectories, and air conflict resolution. Through intensive simulations based on traffic forecasts extrapolated from French traffic data for 2012, we compute the regulation delays and avoidance maneuvers according to two scenarios: the current regulations and no regulations. The resulting cost analysis highlights the exponential growth in regulation costs that can be expected if the procedures and the airspace capacity do not change. Compared to the delay costs, the costs of the air traffic control are negligible with or without regulation. The analysis reveals the heavy controller workloads when there are no regulations, suggesting the need for regulations that are appropriate for large traffic volumes and an improved ATC system. These observations motivate the design of a third scenario that computes the sector capacities to find a compromise between the increase in the delay costs due to ground-holding regulations and the increase in the controller workload. The results reveal the sensitivity of the delay costs to the sector capacity; this information will be useful for further research into ATM sector capacity and ATC automated tool design. Finally, because of the growing interest in the free flight paradigm, we also perform a traffic and cost analysis for aircraft following direct routes. The results obtained highlight the fuel and time savings and the spatial restrictions that companies use to avoid congested areas.

Air traffic management (ATM) under its current paradigm is reaching its structural limits considering the continuously growing demand. The need for a decrease in traffic workload opens numerous problems for optimization, from capacity balancing to conflict solving, using many different degrees of freedom, such as re-routing, flight-level changes, or ground-holding schemes. These problems are usually of a large dimension (there are 30 000 daily flights in Europe in the year 2012) and highly combinatorial, hence challenging for current problem solving technologies. We give brief tutorials on ATM and constraint programming (CP), and survey the literature on deploying CP technology for modelling and solving combinatorial problems that occur in an ATM context.

As acknowledged by the SESAR program, current ATC systems must be drastically improved to accommodate the predicted traffic growth in Europe. This study aims at assessing the performance of 4D-trajectory planning and strategic deconfliction, two of the key concepts identified to meet SESAR capacity objectives. Among the possible degrees of freedom, we focus here on the flight level (FL) optimization to avoid en-route conflicts between intersecting flights. The resulting problem can be reduced to Graph Coloring with a specific cost function minimizing the discrepancies to requested FLs. This FL allocation leads to very large combinatorial optimization problems when applied at the continental scale, especially when considering temporal uncertainties. The instances were solved with a Tabu Search algorithm in a few seconds to a few minutes, depending on size and conflict density. Our results shows that the global conflict resolution workload is alleviated by at least 20 %, while bounding the individual FL discrepancies to three levels for a small proportion of the traffic.

In the SESAR traffic growth predictions, traffic complexity will become an issue that the current Air Traffic Management organization is not able to handle. The 4D trajectory concept offers new perspectives for deconflicting the traffic by ground-holding aircraft before they take-off. This paper studies the possible complexity reduction achievable by optimizing the aircraft take-off times. Therefore a simple model is introduced to detect pairwise 3D possible conflicts and define conflicting take-off time differences. Two resolution algorithms are tested on a real traffic data sample collected in the French airspace. The first one is based on a Constraint Programming model of the problem and ensures the optimality of the maximum delay required to solve every conflict. The second one uses an evolutionary computation algorithm to minimize the mean delay among the aircraft population. A sliding window model is introduced to reduce the size of the problem and to regularly update the current situation. Experimental results performed in the French airspace with fast time simulation show that with perfect 4D trajectory, every conflict over flight level 290 can be solved by delaying less than a quarter of the traffic within a range of delays varying from 1 to 90 minutes and a mean delay of 4 minutes. The Constraint Programming approach gives better results than the evolutionary computation approach. Adding uncertainty around 4D trajectories dramatically degrades the results.