Affiliations: [a] Université Fédérale de Toulouse, École Nationale de l’Aviation Civile, Toulouse, France
| [b] Capgemini Technology Services, Toulouse, France
| [c] Daniel Guggenheim School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA
Abstract: Air Traffic Flow Management (ATFM) aims at structuring traffic in order to reduce congestion in airspace. Congestion being linked to aircraft located at the same position at the same time, ATFM organizes traffic in the spatial dimension (e.g. route network) and in the time dimension (e.g. sequencing and merging of aircraft flows taking off or landing at airports). The objective of this paper is to develop a methodology that allows the traffic to self-organize in the time and space dimensions when demand is high. This structure disappears when the demand diminishes. In order to reach this goal, a multi-agent system has been developed, in which aircraft cooperate to structure traffic. Multi-agent systems have several advantages, including a good resilience when confronted with disruptive events. In this system, three algorithms have been implemented, aiming at reducing traffic complexity in three different ways. The first algorithm allows aircraft agents flying on a route network to regulate speed in order to reduce the number of conflicts, a conflict occurring when two aircraft do not respect separation norms. The second algorithm allows aircraft to solve conflicts when the traffic is not structured by a route network. The third algorithm creates temporary local route networks allowing to structure traffic. The three algorithms implemented in this multi-agent system allow to decrease overall traffic complexity, which becomes easier to manage by air traffic controllers. This algorithm was applied on realistic examples and was able to structure traffic in a resilient way.
