Multi-agent Based Solution for Free Flight Conflict Detection and Resolution Using Particle Swarm Optimization Algorithm

The future management of air traffic allows aircraft choosing their own velocities, altitudes and directions in real time. In aviation industry, this possibility is known as “free flight”. One of the most important issues in the free flight method is conflict detection and resolution problem. In successful free flight, conflicts while maintaining satisfactory performance must be avoided. This paper, presents a multiagent based conflict detection and resolution approach for free flight. In this paper, aircraft and ground flight path controllers are selected as agents, respectively called Aircraft Agent or “AA” and Flight Path Controller Agent or “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 advantages of our proposed system. FPCA agents map the situation of traffic in their vision domain to a flow graph using negotiation with aircraft agents. After some conversion on mapped graph, agents color the corresponding graph using Particle Swarm Optimization (PSO) algorithm. The proposed method is implemented and tested by using five well-known test cases. The experimental results show the high capability and efficiency of our approach for conflict problem. The advantages of using our proposed system includes delay reduction, passenger comfort, safety and speed increase, travel time reduction and less fuel consumption. This system not only proposed for free flight but also can use along with the current air traffic management systems without completely replaces them.