Multi Agent Based Solution for Free Flight Conflict Detection and Resolution using Particle Swarm Optimization Algorithm

The future management of air traffic allows aircrafts choosing their own velocities, altitudes and direc-tions. In aviation industry, this possibility is known as ―free flight‖. One of the important issues in free flight method is conflict resolution. In successful free flight, conflicts while maintaining satisfactory effi-ciency must be avoided. In this paper, we proposed a multi agent based conflict detection and resolution approach in free flight method. We selected aircrafts and ground flight path controllers as agents throughout the airspace, respectively called ―AA‖ and ―FPCA‖. This type of agent selection provides a proper balance between distributed and centralized authority in order to solve air traffic conflicts and this is one of the merits of the system. FPCA Agents by negotiation with each other, map the situation of the airspace (in their vision domain) to a directed graph. After some conversion on mapped graph, agents color the corresponding graph using Particle Swarm Optimization (PSO) algorithm. There are many ben-efits to using such a system include delay reduction, passenger comfort, safety and speed increase, travel time reduction and less fuel consumption. The proposed system not only proposed for free flight method but also can be use as a tool beside the current air traffic management system without completely replac-es it. The proposed method is implemented and tested by using different common test cases. The experi-mental results show high efficiency of the system.

Keywords:

air traffic management , free flight , graph coloring problem , optimization , particle swarm optimization algorithm