Implementation of an Intelligent System for Identifying Vessels Exhibiting Abnormal Navigation Patterns

Abstract

The recent rise in maritime traffic volume, resulted from an increase in international marine trading volumes and the growing popularity of marine leisure activities, has increased the frequency of marine accidents. Vessels exhibiting abnormal navigation patterns (e.g., weaving in and out of courses or rotating in the same position) may have a serious impact on other vessels staying on normal courses. For this reason, ground VTS centers are keeping track of criminal vessels or damaged vessels in tandem with marine police. However, the number of available studies aimed at assisting the identification of seemingly apparent risk factors resulting from human errors has been next to nothing to date. In this respect, this study intends to implement an intelligent system that can identify vessels exhibiting abnormal navigation patterns based on fuzzy inference, in order to assist controllers and mates alike.