Intelligent computing methods in Air Traffic Flow Management |
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| Institution: | 1. TransLab, Department of Computer Science, University of Brasilia, Brazil;2. Politec Tecnologia da Informação S.A., Brasilia, Brazil;3. Brazilian Institute of Information in Science and Technology – IBICT, Brazil;4. First Integrated Center of Air Defense and Air Traffic Control – CINDACTA I, Brasilia, Brazil;1. Civil Aviation College of Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China;2. The 28th Research Institute of China Electronic Technology Group Corporation, Nanjing, 210007, China;1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing, PR China;2. National Key Laboratory of Air Traffic Flow Management, Nanjing 210016, PR China;3. Department of Civil and Environmental Engineering, Imperial College London, SW7 2BU, UK |
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| Abstract: | This research presents the application of intelligent computing models in Air Traffic Flow Management (ATFM). Firstly, multi-agent system in grid computing environment is applied to deal with the problem of ATFM synchronization. The developed system consists of software agents, which are implemented in a Computational Grid platform for congestions identification, conflicts resolution and agreements negotiation among the participating airports. A metric criterion, called Agent’s Balancing Standard (ABS), is used as a basic index to measure the effectiveness of reducing both the amount of communication among agents and the delay of flights. Secondly, a brief discussion about the Meta-Level Control model is introduced in ATFM issues to improve the efficiency of communication among the agents. The system is developed to analyze the traffic flow information received, identify its importance and process it in the most adequate order. |
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