Proactive Collision Avoidance for ASVs using A Dynamic Reciprocal Velocity Obstacles Method

We propose a collision avoidance method that incorporates the interactive behavior of agents and is proactive in dealing with the uncertainty of the future behavior of obstacles. The proposed method considers interactions that will be experienced by an autonomous surface vessel (ASV) in an environment governed by the international regulations for preventing collisions at sea (COLREGs). Our approach aims at encouraging dynamic obstacles to cooperate according to COLREGs. Therefore, we propose a strategy for assessing the cooperative behavior of obstacles, and the result of the assessment is used to adapt collision avoidance decisions within the Reciprocal Velocity Obstacles (RVO) framework. Moreover, we propose a predictive approach to solving known limitations of the RVO framework, and we present computationally feasible extensions that enable the use of complex dynamic models and objectives suitable for ASVs. We demonstrate the performance and potentials of our method through a simulation study, and the results show that the proposed method leads to proactive and more predictable ASV behavior compared with both Velocity Obstacles (VO) and RVO, especially when obstacles cooperate by following COLREGs.