Probabilistic Conflict Detection for Air Traffic Control

Oliver Watkins (CUED)

The problem of conflict detection in air traffic control has become more prominent in recent years, as political pressure for reforms in ATC has increased. In this seminar two contributions to conflict detection are presented. Firstly, a new method of conflict probability estimation is presented, based around Monte Carlo techniques. New information on the statistical nature of wind correlation is exploited in order to give an improvement in accuracy of conflict probability estimation. The second contribution is in the area of conflict alerting; the process of passing alerts for dangerous situations to human or automated air traffic controllers. The sensitivity of the optimal alert threshold to encounter geometry is explored, and a method for ensuring an optimal alerting strategy for all encounter geometries is presented. Finally the effect of these contributions on the state of the art is assessed.