Cooperative collision avoidance study of Maritime Autonomous Surface Ship

Maritime Autonomous Surface Ships (MASS) with the advantage of advanced guidance, navigation, and control capabilities have attracted great attention in recent years. The MASS collect travelling information by the radar, camera, and Autonomous Identification System (AIS) with which it is equipped. Therefore, collision avoidance of MASS turns to be a cooperative and collaborative one by utilizing the interactive information efficiently and effectively. During the collision avoidance procedure of MASS, steering and deceleration are the common actions. In order to receive an efficient and reasonable steering angle and navigation time on the new course, a communication-based real time collaborative collision avoidance decision model is proposed. Firstly, a multi-level communication method is utilized to integrate dynamic information of surrounding vessels. Secondly, a real time collision risk analysis system for MASS is established based on fuzzy logic method. Finally, a collaborative collision avoidance decision system based on the PSO (Particle Swarm Optimization) algorithm is developed to find the optimal steering angle and sailing time on a new course. Comparative analysis about collision avoidance decision results are discussed in simulations. The results show that the model raised in this paper is able to provide effective collision risk awareness and collision avoidance decisions for MASS in a real-time situation.