Robust visual perception of Aids to Navigation (AtoN) is essential for Maritime Autonomous Surface Ships (MASS) operating in restricted navigational waters, where estuarine clutter, fog, glare, and dense traffic can severely degrade detection reliability. Existing maritime vision datasets largely emphasize open-sea targets or coarse AtoN categories, leaving a granularity gap for IALA-compliant fine-grained understanding in riv...

With the rapid growth of global shipping, accurate vessel traffic prediction is essential for waterway management and navigation safety. This study proposes the Fusion Spatio-Temporal Transformer (FSTformer) to address non-Gaussianity, non-stationarity, and spatiotemporal heterogeneity in traffic flow prediction. FSTformer incorporates a Weibull–Gaussian Transformation for distribution normalization, a hybrid Transformer encod...

In this paper, we propose a hybrid algorithm that integrates an improved artificial potential field method (IAPF), model predictive control (MPC), and an extended state observer (ESO) to address the obstacle avoidance problem in multi-unmanned surface vehicle (Multi-USV) formations, including both dynamic and static obstacles, as well as navigation through narrow waterways. Initially, the virtual structure method was applied f...

The autonomous decision-making model for ship navigation requires extensive interaction and trial-and-error in real, complex environments to ensure optimal decision-making performance and efficiency across various scenarios. However, existing approaches still encounter significant challenges in addressing the temporal features of state space and tackling complex dynamic collision avoidance tasks, primarily due to factors such...

Increasing vessel traffic in narrow, winding inland waterways has heightened the risk of accidents, driving the need for improved surveillance and management. This study addresses the challenge of real-time processing and synchronization of voluminous video and AIS data for effective waterway management. We developed a surveillance method utilizing smart buoys equipped with sensors and edge computing devices, enabling dynamic...

The safety of ships during nighttime navigation has always been a major concern. With the widespread application of technologies such as intelligent recognition, intelligent detection, and unmanned ship navigation at night, nighttime maritime light pollution has significantly affected the effectiveness of these intelligent technologies and navigation safety. Therefore, effectively eliminating nighttime maritime light pollution...

Ship trajectory prediction plays a key role in the early warning and safety of maritime traffic. It is a necessary assistant tool that can forecast a ship’s trajectory in a certain period to prevent ship collision. However, highly precise prediction of long-term ship trajectories is still a challenge. This study proposes a ship trajectory prediction model called ShipTrack-TVAE, which is based on a Variational Autoencoder (Soci...