Decomposition Methods for Optimized Collision Avoidance with Multiple Threats

Aircraft collision avoidance systems assist in the resolution of collision threats from nearby aircraft by issuing avoidance maneuvers to pilots. Encounters where more than one aircraft poses a threat, though rare, can be difficult to resolve because a maneuver that might resolve a conflict with one aircraft might induce conflicts with others. Recent efforts to develop robust collision avoidance systems for single-threat encounters have involved modeling the problem as a Markov decision process, discretizing the model, and applying dynamic programming to solve for the optimal avoidance strategy. Because the direct application of this methodology does not scale well to multiple threats, this paper evaluates a variety of decomposition methods that leverage the optimal avoidance strategy for single-threat encounters.