Research Of Probabilistic Aircraft Conflict Detection Algorithms In Air Traffic Management

Conflict detection is an important part of current air traffic management system.With the increasing of traffic flow in the future, conflict detection plays anincreasingly important role. Conflict detection is the key to guarantee flight safety andefficiency. The flight airspace includes en-route area and terminal area. In the thesis,conflict detection algorithms in en-route area and terminal area were studied based ondifferent flight characteristics in the two areas.We proposed two conflict detection algorithms based on changing route onexpected time or changing route at expected waypoint for aircrafts with multi-route inen-route area. In the case of changing route on expected time, aircrafts’ routes weredivided into a sequence of route segments by the route change time. Conflictprobability was calculated based on classic aircraft position prediction model andposition space discretization algorithm. In the case of changing route at expectedwaypoint, the probability density function of arriving time at waypoint was calculated.Conflict probability at intersecting air route of two aircrafts was computed based onthe probability density function of arriving time at waypoint and the aircraft positionprediction error. Simulation results showed that the two algorithms were accurate forconflict detection and computationally efficient for engineering application.We proposed two conflict detection algorithms for aircrafts that had frequentlydynamic changes in terminal area based on stochastic differential equation positionprediction model. The two algorithms used maximum instantaneous conflictprobability and overall conflict probability to measure the possibility of conflict inprediction time. Conflict prediction time was divided into segments according to thedynamic change time of each aircraft and there were no velocity or heading changesin every segment. In the algorithm that we used maximum instantaneous conflictprobability，relative position probability density function was calculated based onstochastic differential equation position prediction model and conflict probability wascomputed using coordinate transformation and Simpson rule. In the algorithm that weused overall conflict probability，the conflict probability was equal to the probabilityof an aircraft doing stochastic motion entering another aircraft’s moving protectionzone. An approximation algorithm was given based on coordinate transformation andBachelier-Levy theorem to get the analytical expression of conflict probability.Simulation results showed that the two algorithms were accurate for conflict detection and useful for air traffic management system to detect and solve conflicts.We proposed a conflict detection algorithm for aircrafts in terminal area withintent information based on stochastic linear hybrid system position prediction modeland position space discretization algorithm. The future position of aircraft waspredicted using stochastic linear hybrid system position prediction model based oncurrent track and intent information. The predicted position of aircraft was a variableof multi-dimensional Gaussian distribution and position space discretization algorithmwas used for calculating the conflict probability. Simulation results showed theaccuracy and efficiency of the algorithm.