Improved Prandini Conflict Detection Algorithm Based on Trajectory Prediction

As a traditional probabilistic mid-term conflict detection algorithm, the Prandini algorithm plays an essential role in ensuring flight safety in the aircraft route area. For the issue of mutation error in the calculation results of the Prandini algorithm, this research provides an improved Prandini conflict detection algorithm. First, the integral of the standard Gaussian distribution is solved using randomization. The minimum prediction interval moment is then calculated, and the critical time points at which conflicts may exist before and after that moment are approximated separately using a bisection method. N moment values are selected uniformly within the time range formed by the two critical time points. The instantaneous conflict probabilities for these N moments are calculated and the maximum value is selected from them as a measure of the likelihood of conflict between the two aircraft over the entire route for an extreme case. Finally, a trajectory position prediction error model is built using actual ADS-B data to verify the performance of this improved algorithm for application in the no route change scenario and the multi-route scenario. The experimental results show that compared with the original Prandini algorithm, the method improves the stability of conflict detection and can meet the requirements of air traffic control (ATC) for medium-term conflict detection.