Study Of Aircraft Conflict Resolution Method

With the development of air transportation, the air traffic system is facing more and more congestions. Flight conflicts have appeared frequently, putting unprecedented pressure on the current air traffic control system. Part of the anticipated solution is free flight, which allows the pilots to choose the airway and flight speeds suitable for them. Aircraft conflict detection and resolution are key problems for free flight. It is required to find out an automated and feasible conflict resolution method, which provides theoretical basis for free flight.This paper mainly focuses on the application of Artificial Field method and Ant Colony Algorithm(ACA for short) in air traffic conflicts resolution problem. Firstly, the background of the conflict detection and resolution research being undertaken worldwidely is systematically introduced. Then Artificial Field method and ACA are introduced and based on each method, two corresponding mathematic models are established. As to the application of Artificial Field method, traditional Artificial Field method is improved to resolve air traffic conflicts in 3-D space instead of 2-D space; as to the application of ACA, after using Basic Ant Colony Algorithm(BACA for short) to resolve aircraft conflict , a improved ACA is proposed by incorporating Artificial Field method into BACA. The Artificial Potential Field is introduced as the priori knowledge to initialize the solution of BACA. Compared with BACA, the proposed method incorporating these two methods notably improves the planning quality and efficiency, which is the innovative point in this paper. Finally, by the simulation of multi-aircraft centering conflicts, the algorithms are proved to be competent in resolving various air traffic conflicts by heading change,which provide theoretical basis for further air traffic automation research.