Sampling-based collision avoidance for commercial airliners with intruder aircraft and terrain

This paper presents a robust, sampling-based path-planning algorithm for commercial airliners that simultaneously performs collision avoidance both with intruder aircraft and terrain. The current resolution systems implemented on commercial airliners are effective and efficient, but have certain limitations; the algorithm proposed in this paper attempts to rectify some of these. Recent advances in automatic dependent surveillance-broadcast (ADS-B) and GPS technology provides the information required to resolve complex conflict scenarios that simultaneously involve multiple intruder aircraft and terrain. The proposed algorithm applies an incremental sampling-based technique to determine a safe path quickly and reliably. As the number of samples increases, the algorithm strives towards an optimal solution; this results in a safe, near-optimal path that avoids the conflict region. Simulation results show that the proposed algorithm is able to successfully resolve various conflict scenarios, including the generic two aircraft scenario, terrain only scenario and a two aircraft with terrain scenario. A statistical analysis of the simulation results shows that the algorithm finds near-optimal paths quickly and reliably.