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Monte Carlo Optimisation for Conflict Resolution in Air Traffic Control


A. Lecchini Visintini, W. Glover, J. Lygeros, Jan M. Maciejowski

Lecture Notes in Control and Information Sciences (LNCIS), vol. 337, pp. 257-276, Chapter in book: Stochastic Hybrid Systems: Theory and Safety Critical Applications. H.A.P. Blom, J. Lygeros (Eds.)

The safety of the flights, and in particular separation assurance, is one of the main tasks of Air Traffic Control. Conflict resolution refers to the process used by air traffic controllers to prevent loss of separation. Conflict resolution involves issuing instructions to aircraft to avoid loss of safe separation between them and, at the same time, direct them to their destinations. Conflict resolution requires decision making in the face of the considerable levels of uncertainty inherent in the motion of aircraft. We present a framework for conflict resolution which allows one to take into account such levels of uncertainty through the use of a stochastic simulator. The conflict resolution task is posed as the problem of optimizing an expected value criterion. Optimization of the expected value resolution criterion is carried out through an iterative procedure based on Markov Chain Monte Carlo. Simulation examples inspired by current air traffic control practice in terminal maneuvering areas and approach sectors illustrate the proposed conflict resolution strategy.


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% Autogenerated BibTeX entry
@Book { VisEtal:2006:IFA_2734,
    author={A. Lecchini Visintini and W. Glover and J. Lygeros and Jan M.
    title={{Monte Carlo Optimisation for Conflict Resolution in Air
	  Traffic Control}},
    publisher={Springer Verlag},
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