Ship fuel consumption prediction plays a crucial role in navigation decision-making and the intelligent evaluation of energy efficiency, particularly for future Marine Autonomous Surface Ships (MASS). This study leverages an onboard measurement and data acquisition system installed on a 28, 000 DWT bulk carrier operating on global routes. With the system, navigation-related data from 2010 to 2016 across different sea areas, loading conditions, and meteorological and sea states were collected and analyzed, including ship speed, course, sway, main engine speed, and environmental parameters. Using real-time inputs such as wave height, wave direction, speed, wind speed, pitch angle, main engine power, and main engine speed, a fuel consumption prediction model was developed based on the lightGBM algorithm. The performance of this model was compared with other machine learning approaches, including Support Vector Regression（SVR）, Long Short-term Memory （LSTM）, Gated Recurrent Unit （GRU）, Artificial Neural Network （ANN）, and Extreme Gradient Boosting （XGBootst）. Results show that the proposed model achieves superior performance, with RMSE reduced by 7.26%, MAE reduced by at least 2.62%, R² increased by 0.23%, and runtime shortened by 73.76%. Furthermore, the navigation data was divided into four subsets based on actual loading conditions to further validate the generalization capability of the lightGBM model. The results indicate that the proposed LightGBM model provides an effective solution for predicting ship fuel consumption, striking a balance between accuracy and computation efficiency. This study also provides a valuable reference for selecting optimal fuel consumption prediction methods in comparable vessel types.

The application of green ship technologies, such as hull form optimization, has been widely studied for improving energy efficiency during ship operation. However, environmental evaluations of the shipbuilding and scrapping stages remain insufficient, making it difficult to assess the lifecycle environmental impacts of these technologies holistically. To address this gap, this study selects a 150, 000-ton shuttle tanker as the research object. Experimental measurements and statistical analyses were conducted to quantify differences in energy and material consumption over the ship's lifecycle resulting from hull form optimization. Using the Life Cycle Assessment （LCA）method implemented in SimaPro V9. 6 software, an environmental impact assessment was performed to analyze the effects of hull form optimization on Global Warming Potential （GWP）and its contribution to carbon emission reduction. The results indicate firstly that the carbon reduction contribution of hull form optimization is highest in the shipbuilding stage, followed by the operation stage, and lowest in the scrapping stage. This suggests that a comprehensive evaluation of green ship technologies should account for not only the operational phase but also the construction and dismantling phases. Furthermore, while both LCA and the Energy Efficiency Design Index （EEDI）methods show broadly consistent trends in assessing the carbon reduction effect of hull form optimization during operation, the LCA results are more conservative. This discrepancy arises partly from differences in operational condition assumptions and the fact that the carbon emission factors in the Ecoinvent-3 database, commonly used in LCA, do not fully account for fuel combustion processes.

With the continued advancement of China "dual-carbon" goals and the increasingly stringent emission reduction regulations of the International Maritime Organization (IMO), the shipping industry is facing more severe emission reduction challenges and urgently needs to clarify the green transition pathways. Most of the existing research focuses on the selection of alternative fuels, while there is relatively little research on emission reduction strategies from the perspective of the fleet. To address the shortcomings of the existing research, this study identifies the key factors influencing fleet green transition decisions. Based on this, a bi-objective linear programming model jointly considering economic and environmental objectives is established, and a genetic algorithm combined with the ε-constraint method is constructed to solve the model. Finally, taking the 10, 000-11, 000 TEU container fleet of COSCO Shipping Group as a case study, this research derives the optimal green transition strategy for the fleet during the planning horizon, encompassing fuel choices and operational configurations for individual vessels. Sensitivity analysis reveals that fluctuations in fuel prices significantly affect the selection of engine types during vessel retrofitting and renewal decisions, while the stringency of emission reduction targets directly influences fleet transition costs, thereby affecting corporate proactiveness in pursuing decarbonization initiatives. Consequently, policymakers should establish appropriately calibrated emission reduction targets and incentive mechanisms to accelerate the advancement of low-carbon technologies, reduce fleet transition costs, and expedite the achievement of decarbonization objectives in the shipping industry.

Improving ship energy efficiency and reducing greenhouse gas emissions are major research priorities in the maritime industry. Accurate prediction of main engine power is fundamental to enhancing vessel energy efficiency. Using historical operational data collected from a Very Large Crude Carrier (VLCC), this study integrated and cleaned meteorological data to construct training and test datasets. Three models for main-engine power estimation are investigated and compared:a mechanistic model （SNNM), a non-mechanistic model based on Random Forest （RF), and a semi-mechanistic RF-based model. Simulation results indicate that while the mechanistic SNNM model can meet application requirements under specific engineering conditions, but R² coefficient is relatively low. In contrast, both the non-mechanistic model based on RF and the semi-mechanistic RF-based model demonstrated excellent predictive accuracy for both main engine shaft rotational speed and power, with R² values exceeding 0. 98.

This paper presents a contrast-enhancement-based dehazing algorithm to address detail loss, dim brightness, and color distortion in dehazed images of offshore tugboat sailing scenes with large sea-sky regions. First, atmospheric light estimation is optimized using quadtree segmentation to locate the light source in regions with minimal local pixel variance. Then, mean squared error contrast preserves image details, and a contrast overall cost function combined with an information loss function is used to find optimal transmission, enhancing contrast and making the sky region clearer. A fast guided filter further refines the transmission map, reducing block artifacts and maintaining real-time performance while restoring image authenticity. Finally, adaptive histogram equalization preserves contrast information in the sky, avoiding over-bright or over-dark areas. Experiments show that the image obtained using the proposed algorithm improves structural similarity, peak signal-to-noise ratio, and mean squared error by 15. 94%, 11. 46%, and 25. 82%, respectively, compared with the OCE method, while preventing color cast and halo effects, enhancing sea-sky boundary clarity, and meeting real-time requirements for restoring a realistic maritime environment.

This paper aims to introduce the fundamental content, legislative purpose, and implementation pathways of Korea's "Act on Promoting the Development and Commercialization of Autonomous Ships." It delves into an in-depth analysis of the measures taken to promote the research, development, and commercialization of autonomous surface ships, the regulatory framework and foundational systems established, as well as the intrinsic logic and practical as well as long-term significance underlying these aspects. By sharing Korea's basic practices in promoting cutting-edge maritime technological innovation through legislation and driving the development of smart shipping via commercialization, this paper seeks to provide valuable references for China's related legislative efforts, the acceleration of smart shipping development, and the advancement of its transport sector.

This article firstly reviews the relevant background and process of revising China Maritime Code which is the first comprehensive and systematic revision in over thirty years. After elucidating the new historical mission of the Law in the new era, from the perspective of providing a solid legal safeguard for high-quality development of the shipping industry, it focuses on analyzing seven key institutional developments as follows: harmonizing domestic and international carriage of goods by sea rules, establishing the legal status of electronic transport records, regarding the port operators as actual carriers, prudently increasing limitation of liability amounts, clarifying the non-typical security attribute of ship finance leasing, improving the marine insurance rule system, and introducing countermeasure clauses. Finally, it proposes directional considerations regarding the implementation of new law, formulation of supporting rules, and future legislative development.

This article focuses on the significant revisions to the time limit system in the new Maritime Code of China, systematically examining the institutional restructuring in four key areas: the one-year time limit for the carriage of goods by sea, the recourse time limitation, special causes for the interruption of maritime time limitations, and the commencement of the time limitation for marine insurance claims. The research shows that the new Code has made important progress in maintaining the internationally accepted one-year benchmark, constructing a balanced bilateral time limit structure, appropriately broadening the causes for interruption, and unifying the commencement standard for insurance claims, thereby significantly enhancing the legal system's certainty and international harmonization. However, the new Code might face challenges in local adaptation, including the absence of an agreement-based extension mechanism, limited recourse time limitation relief space, and unclear special rules for liability insurance and subrogation. By analyzing the new legal system and evaluating its effectiveness and potential limitations, this article aims to provide response strategies for the shipping industry and judicial practice, promoting the continuous optimization of China's maritime legal environment.

Autonomous berthing is a key element of intelligent navigation, yet its strong scenario dependence limits the application of theoretical research into actual implementations. Variations in ship type, propulsion configuration, and berth conditions impose distinct requirements on trajectory planning and control. At the same time, defining the completion criteria for autonomous berthing operation and establishing a comprehensive evaluation framework are essential for ensuring practicality and safety. This paper systematically reviews recent advances in trajectory planning and motion control for autonomous berthing. First, the key technical elements, including trajectory planning and motion control methods, are introduced. Second, different berthing strategies tailored to specific ship types and propulsion systems are analyzed in depth. Subsequently, berthing completion standards, performance evaluation metrics, and experimental validation approaches are discussed. Finally, the major challenges in the current research are summarized, and potential directions for future development are outlined.

The continuous increase in crisscross navigation between passenger and cargo ships poses a significant threat to navigation safety in restricted inland waters. Traditional row-by-row crossing operation methods are inadequate for ships navigating such complex environments, leading to a surge in navigational risks. This study proposes an enhanced row-by-row following ship crossing operation method, building upon traditional approaches to address the dual peak periods of passenger ship departures and tidal effects. Based on traffic conflict technology and dynamic ship domain theory, large-angle and small-angle row-by-row following ship crossing models were developed. The advantages of the proposed methods are validated using actual Automatic Identification System (AIS) data collected from the turnaround area of the busy Huangpu River. Results indicate that both the large-angle and small-angle row-by-row crossing methods effectively mitigate the safety limitations of traditional methods. Furthermore, the small-angle row-by-row crossing method improves passenger ship crossing efficiency by up to 50% compared to the large-angle method. The proposed row-by-row following vessel crossing operation method demonstrates significant potential for enhancing navigation efficiency and safety in restricted inland waterways, particularly in congested turnaround areas.