A probabilistic approach to aircraft conflict detection

In this paper, we concentrate primarily on the detection component of conflict detection and resolution schemes operating at the mid-range and short range level of the air traffic management process. Probabilistic models for mid-term and short term prediction are introduced. Based on the mid-term prediction model, the maximum instantaneous probability of conflict is proposed as criticality measure of a two aircraft encounter situation. The computational issues involved in its estimate are solved by resorting to randomized methods which provide also quantitative bounds on the level of approximation introduced. As for short range detection, closed-form analytical expressions though approximations for the probability of conflict are obtained by using the short term prediction model. Based on these expressions, an algorithm for decentralized conflict detection and resolution that generalizes potential fields ideas to path planning in a probabilistic dynamic environment is suggested. The proposed approaches are shown to be promising using Monte Carlo simulations.