Ship Path Optimization That Accounts for Geographical Traffic Characteristics to Increase Maritime Port Safety
Hongchu Yu, Alan T. Murray, Zhixiang Fang, Jingxian Liu, Guojun Peng, Mohammad Solgi, Weilong Zhang
Abstract
Maritime ports face challenges associated with navigation safety, operational efficiency, and management. With the development of the Internet of Things, artificial intelligence simulation technologies, geographical information systems, and cloud computing technologies as well as navigation aids and decision support systems in maritime transportation, ports have the potential to better manage traffic, loading, and unloading. Recently, there has been growing attention in unmanned shipping to support the maritime industry and the military. This paper aims to extend the application of geographical theory and methodology in unmanned ship path optimization. Automatic collision avoidance concerning maneuvering capabilities of ships as well as complying with maritime traffic rules remains a challenge. This study attempts to tackle development needs associated with path optimization in maritime travel. By integrating ship movement behavior, geographical features, and the International Regulations for Avoiding Collisions at Sea, the proposed methods seek to reduce the human error associated with maritime accidents. This paper proposes economic efficiency and safety-driven unmanned ship path planning that will promote the future growth of intelligent port development.