DEVELOPING A DECISION-MAKING MECHANISM FOR AUTONOMOUS COLLISION AVOIDANCE OF UNMANNED NAVIGATION: FUZZY APPROACH

Abstract

In the near future, unmanned vessel (UV) will become increasingly important and will act without any human intervention. This situation raises the collision risk between UVs and general ships. Research on maritime accidents have shown that ship collision accidents due to violation of the International Rules for the Prevention of Collisions at Sea, 1972 (COLREGs-72), which were developed by the International Maritime Organization (IMO), remain the leader of navigational accidents on shipping waterways. In this respect, autonomous preventing collisions is critical for unmanned navigational safety at sea. Hence, in this paper, aiming at the problem of autonomous collision avoidance in open sea area under conditions of good visibility. To this end, a fuzzy logic system to obtain autonomous collision of UVs according to the rules of COLREGs-72 proposed in this paper. The proposed Decision-Making Mechanism (DMM) based on logical schema for the implementation of the strategy that is the best in the sense of the selected optimality criterion (optimal strategy) for unmanned navigation control. The inputs to the collision avoidance fuzzy logic system are the navigational parameters (speed, course, position, etc.). The rule base of the collision avoidance fuzzy logic system consists of 17 rules to avoid collisions. The authors proposed a trapezoidal membership function which allows an analytical representation of the collision risk of an UV with a target ship, depending on the situation feature (encounter sector). Currently, various information collision avoidance systems, which have been developed, added a safety barrier to help prevent collisions at sea. However, further research and efforts of scientists from many developed countries of the world were still required. As part of further research, the authors plan to use the described method to develop an information decision-making system for a movement control of an unmanned vessel