A RESEARCH ON TECHNIQUES, MODELS AND METHODS PROPOSED FOR SHIP COLLISION AVOIDANCE PATH PLANNING PROBLEM

The development of soft computing techniques in recent years has encouraged researchers to study on the path planning problem in ship collision avoidance. These techniques have widely been implemented in marine industry and technology-oriented novel solutions have been introduced. Various models, methods and techniques have been proposed to solve the mentioned path planning problem with the aim of preventing reoccurrence of the problem and thus strengthening marine safety as well as providing fuel consumption efficiency. The purpose of this study is to scrutinize the models, methods and technologies proposed to settle the path planning issue in ship collision avoidance. The study also aims to provide certain bibliometric information which develops a literature map of the related field. For this purpose, a thorough literature review has been carried out. The results of the study have pointedly showed that the artificial intelligence methods, fuzzy logic and heuristic algorithms have greatly been used by the researchers who are interested in the related field.

Mapping of Marine Safety Publications Using VOSviewer

Marine safety has promoted the non-violent transportation of goods and property through technological innovation, risk management, and regulations. Accordingly, the study of the evolution of the scientific domain in marine safety is vital. This study discusses the bibliometric review of academic publications performed in marine safety research over 58 years from 1962 till 2020. The assessment is based on the Scopus database and various bibliometric indicators, including publication output growth, citations, and author’s keywords. This study also generated graphical visualisations of bibliometric mapping through VOSviewer software. This study showed that the number of publications on marine safety research has fluctuated with a hike publication in 2020. Moreover, the results tended to indicate that marine safety research is mainly based on engineering scopes. Therefore, the bibliometric review could provide a conscientious and comprehensive view of marine safety research that could benefit marine safety practitioners, academics, and researchers interested in fostering their future exploration in this field.

Study on Visual Detection Algorithm of Sea Surface Targets Based on Improved YOLOv3

Countries around the world have paid increasing attention to the issue of marine security, and sea target detection is a key task to ensure marine safety. Therefore, it is of great significance to propose an efficient and accurate sea-surface target detection algorithm. The anchor-setting method of the traditional YOLO v3 only uses the degree of overlap between the anchor and the ground-truth box as the standard. As a result, the information of some feature maps cannot be used, and the required accuracy of target detection is hard to achieve in a complex sea environment. Therefore, two new anchor-setting methods for the visual detection of sea targets were proposed in this paper: the average method and the select-all method. In addition, cross PANet, a feature fusion structure for cross-feature maps was developed and was used to obtain a better baseline cross YOLO v3, where different anchor-setting methods were combined with a focal loss for experimental comparison in the datasets of sea buoys and existing sea ships, SeaBuoys and SeaShips, respectively. The results showed that the method proposed in this paper could significantly improve the accuracy of YOLO v3 in detecting sea-surface targets, and the highest value of mAP in the two datasets is 98.37% and 90.58%, respectively.