Cyril Allignol

Constraint programming for air traffic management : a survey

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.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.

A ground holding model for aircraft deconfliction

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.

Optimized vertical separation in Europe

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.

Integration of UAS in Terminal Control Area

In this article, we test a horizontal detect and avoid algorithm for UASs flying in Terminal Control Areas. We have used recorded commercial traffic trajectories and randomly built thousands of conflict scenarios with UASs to check the ability of such an algorithm to ensure the separation with commercial aviation. We consider two different types of UASs, flying at 80kn or 160kn, with six different missions: flying straight or turning and leveled, climbing or descending. We only focus on horizontal maneuvers at constant speed in order to not interfere with the TCASs of aircraft, nor rely on most UASs poor ability to change speed. The article investigates the influence of the various parameters on the separation achieved and the amount of maneuvers required, especially the strategy used to select the best maneuver among the allowed headings. The analysis of our results shows that, amid two basic and “extreme” strategies that favor either minimal heading changes or the robustness of the maneuvers, the combination of both, switching from the first one to the second whenever the distance between the UAS and aircraft falls under a given threshold, gives the best results with very few remaining airproxes, while keeping low the amount and amplitude of maneuvers.

Review: constraint programming for air traffic management: A survey1

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.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.

Constraint programming for air traffic management: a survey - In memory of Pascal Brisset.

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.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.