METHODS OF CONFLICT PROBABILITY ESTIMATION AND DECISION MAKING FOR AIR TRAFFIC MANAGEMENT

Author:

Babak Vitaly1,Kharchenko Volodymyr1,Vasylyev Volodymyr1

Affiliation:

1. National Aviation University, 1 Kosmonavta Komarova Ave., 03058, Kiev, Ukraine

Abstract

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.

Publisher

Vilnius Gediminas Technical University

Subject

Aerospace Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Cooperative Decision Making Under Air Traffic Conflicts Detection and Resolution;Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries;2020

2. A Heuristic Approach for the Robust Flight Level Assignment Problem;Belief Functions: Theory and Applications;2018

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