Simulation Comparison of Collision Avoidance Algorithms for Small Multi-Rotor Aircraft

This paper describes the implementation of four different collision avoidance algorithms designed for multi-rotor aircraft. The primary contribution of this paper is the evaluation of each using a common set of assumptions, simulation capabilities, and metrics. The first algorithm is an extension of the next-generation manned aircraft algorithm that will soon be deployed worldwide; it poses the collision avoidance problem as a partially observable Markov decision process and solves offline for the approximately optimal solution using dynamic programming. The second algorithm is based on receding-horizon model predictive control, and the third is based on potential field methods. The fourth algorithm is an adaptation of a tactical conflict detection and resolution algorithm that uses candidate trajectory predictions to determine a preferred resolution. A batch simulation system generates trajectories and computes aggregate metrics related to each algorithm’s performance, allowing direct comparison of the benefits and drawbacks of each approach. A second contribution of this paper is a description of the first known encounter model of hobbyist unmanned aircraft trajectories. This model is used to generate trajectories that are representative of the airspace. All algorithms have the flexibility to provide different tradeoffs between separation from an intruder and the trajectory deviation necessary to achieve that separation. The algorithm generated using dynamic programming delivers excellent maximum deviation performance with only slightly smaller separations than the model predictive control algorithm, and it does so with less than half of the required velocity change of the other algorithms.