Artificial intelligence and its applications in intelligent ship navigation

Journal article, 2026

With the rapid advancement of artificial intelligence (AI), maritime autonomous surface ships (MASSs)—also referred to as autonomous vessels—have emerged as an important avenue of research in the maritime industry. Their development is primarily driven by their potential to reduce dependence on onboard personnel, enhance operational efficiency, and improve the overall intelligence of ship navigation. In particular, the application of deep learning, imitation learning, and reinforcement learning techniques provides new approaches for developing highly intelligent navigation systems. These methods enable autonomous vessels to achieve increasingly sophisticated capabilities in environmental perception, navigation decision-making, collision avoidance, and berth-to-berth motion control, with their performance approaching that of human operators. Consequently, AI-based technologies are expected to play an increasingly significant role in intelligent ship navigation and related maritime applications, unlocking the potential to support, augment, or ultimately replace certain functions traditionally performed by onboard or shore-based officers. This technological development is widely regarded as an important direction for the future evolution of autonomous vessels and intelligent transportation systems across inland waterways, coastal regions, and open oceans. This Special Issue includes 13 research articles, comprising 5 studies on ship navigation, 6 on waterway transportation, and 2 on ocean environmental issues. Most of these studies apply AI-based methods to address specific domain problems and demonstrate satisfactory performance compared with traditional approaches.