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