Open AccessMETHODS OF CONFLICT PROBABILITY ESTIMATION AND DECISION MAKING FOR AIR TRAFFIC MANAGEMENT
Author(s) -
Vitalii Babak,
Volodymyr Kharchenko,
Volodymyr Vasylyev
Publication year - 2006
Publication title -
aviation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.239
H-Index - 13
eISSN - 1822-4180
pISSN - 1648-7788
DOI - 10.3846/16487788.2006.9635920
Subject(s) - air traffic control , range (aeronautics) , air traffic management , interval (graph theory) , computer science , separation (statistics) , limit (mathematics) , transformation (genetics) , boundary (topology) , trajectory , operations research , mathematical optimization , engineering , mathematics , machine learning , physics , astronomy , aerospace engineering , mathematical analysis , biochemistry , chemistry , combinatorics , gene
This research addresses the issue of conflict detection in Air Traffic Control (ATC) and in Airborne Separation Assurance System (ASAS) domains. Stochastic methods of conflict situation detection and conflict probability evaluation are presented. These methods can be used for air traffic conflict alert and avoidance systems for mid‐range monitoring of air traffic and for flight safety. The mathematical formulation of the problem and the procedure of evaluation are presented. Two methods are introduced. One is based on fast statistical simulation of predicted violations of safe separation standards, and the other gives a closed‐form analytic expression that can be applied to numerical evaluation methods. The next method proposed is a method of sequential evaluation of decision‐making time limit to prevent a dangerous approach of the aircraft for short‐range monitoring. The problem is solved by assuming that the estimation and prediction of trajectory are based on the spline‐function method. The evaluation of the boundary instants for decision‐making is achieved by solving the derived boundary equation for fixed decision‐making distance. The distinguishing feature of this method is transformation of a confidence interval of predicted distance to a confidence interval of predicted time for estimation of the decision‐making time limit.