Maritime piracy represents a significant international challenge, impacting both economic stability and political dynamics. Researchers from diverse disciplines have been drawn to this multifaceted issue, each aiming to understand and address different aspects of piracy’s impact and implications. This study offers a comprehensive overview of maritime piracy research based on bibliographic analysis. Its objective is threefold. First, to delineate the key domains of inquiry within maritime piracy research. These domains encompass a wide range of topics, including the socio-economic drivers of piracy, the legal frameworks governing maritime security, and computer science to analyse piracy acts. Second, to identify major contributions in the field, recognising seminal works, influential authors and significant findings related to maritime piracy. Lastly, to discern emerging research trends within maritime piracy, and to identify novel areas of inquiry, innovative methodologies and promising avenues for future exploration. Furthermore, the most popular datasets from these studies that include relevant information are presented in this work.

This paper studies the probability of active navigational error events for use in ship–bridge allision risk analysis. To estimate the probability of these kinds of events, accident databases, incident reports and AIS data were studied; the case studies herein cover 6 years and 15 bridges in Scandinavia. The main findings of this paper show that there is great variation in the probability of ship–bridge allision due to active navigational errors, and it is not recommended to use the currently common practice of 2% uniform distribution of the number of ship passages on all bridges. Another important finding is that the probability of a ship striking a bridge due to the error type Wrong Course at a Turning point is not uniform along the length of the bridge, but is only likely to occur in a cone formation from the last turning point.

During a regatta, the influence of wind speed on the velocity of the boat, the distance covered and the manoeuvres carried out has not been clarified to date in the 49er and 49erFX classes. Therefore, the main aim of this study was to analyse how these variables are affected by wind speed during a regatta. The sample consisted of 39 Olympic sailors from the 49erFX and 49er classes, who participated in a World Cup. Velocity, velocity made good (VMG), distance and manoeuvres were evaluated in the upwind and downwind legs using global positioning system (GPS) devices. In both classes, it was observed that mean velocity, VMG and distance travelled increased as the wind velocity increased in upwind and downwind legs. The velocity, the distance travelled and the manoeuvres carried out are conditioned by wind speed in both upwind and downwind legs in the 49er and 49erFX classes.

Maritime navigation in low visibility presents a significant challenge, jeopardising seafarers’ situational awareness and escalating collision risks. This study introduces a maritime head-up display (mHUD) to address this issue. The mHUD, a 2-m diameter aluminium ring with dual rows of LEDs, enhances visibility for autonomous ships in adverse conditions on ship bridges and remote operating centres (ROCs). Displaying various modes such as shallow waters, land, lighthouses, beacons, buoys and maritime traffic, the mHUD was evaluated in a ship bridge simulator by 12 navigation students. Results revealed that the mHUD substantially improved situational awareness, proving more efficient and effective than navigating without it in poor visibility conditions. Participants found the mHUD easy to learn and expressed willingness to use it in real-world situations. The study highlights the mHUD’s potential to enhance situational awareness on ship bridges and ROCs for autonomous ships, while suggesting potential enhancements to increase usability and user satisfaction.

Accurate typhoon track nowcasting is vital for navigation and coastal disaster prevention. This research integrates a Large Language Model (LLM) with Retrieval-Augmented Generation (RAG) technology for typhoon path prediction. Leveraging LLMs as the predictive foundation, the approach tailors forecasts to individual typhoon characteristics. The methodology involves collecting satellite imagery, standardizing data, and employing optical flow methods to track typhoons and derive path coordinates. These coordinates are preprocessed and embedded into the LLM. RAG enhances the LLM’s predictive performance, enabling effective forecasting. Increasing typhoon-specific embedded data further improves accuracy. Using the FY-4 dataset, the method achieved an average absolute error of 10.78 km in 12-hour predictions. The study demonstrates that LLM-RAG integration excels in nowcasting.

Global Navigation Satellite System (GNSS) positioning accuracy is challenged due to abnormal signals in harsh environments. This study proposes an approach for multiple and mixed abnormal measurement processing in multi-GNSS positioning and navigation based on the resilient a priori innovation and posterior residual (PR) for harsh environments. Specifically, first, both static and kinematic processing modes are considered when calculating the innovation vector (IV). Second, observations are classified and abnormal measurements are eliminated based on the different observation accuracies of different GNSS systems within the resilient IV method. Finally, the resilient PR method considers the total number of redundant observations. Compared with the traditional IV and PR method, the RIP method improves the positioning accuracy by approximately 30.2% and 58.0% in static experimental datasets No. 1 and No. 2, respectively. In the kinematic experiment, it improves the ambiguity success rate and positioning accuracy by approximately 41.5% and 86.7%, respectively.