To improve the effectiveness of Unmanned Surface Vehicle (USV) path planning in complex marine environments, and to address the issue of low operational efficiency in dynamic environments, a new Dynamic Window Approach (DWA) for USV path planning has been developed. Firstly, the target water area range is determined based on the USV's initial and target positions, and the water area is modelled using a grid system. Secondly, the forces exerted on the USV by wind, waves and currents are calculated and combined with the USV's mass to produce an acceleration value, thereby forming a kinematic model of the USV under the influence of the marine environment. Thirdly, the maximum values of linear and angular acceleration of the USV are determined using the Fossen ship dynamics model, thus obtaining the actual reachable speed set of the USV. Finally, an adaptive weight adjustment algorithm is used to improve DWA and plan the USV path, considering the heading, safe distance and speed factors. Simulation experiments were conducted in the waters near the Zhoushan Islands using the USV "Zhi Kun" to verify the reliability of the model. The results show that, compared with the comparative algorithm, the proposed algorithm performs better in terms of running time, simulation step size, change in bow direction amplitude, change in speed amplitude, and length of the planned path. The improved DWA-planned path ensures the USV can reach its destination safely and quickly, providing a reference for improving the autonomous navigation performance and efficient utilisation of USVs.

Clean and low-carbon development in the transportation sector is crucial for preventing, controlling and mitigating atmospheric environmental problems that threaten sustainable human health. Based on statistical data, sustainable development reports and pollution prevention and control plans for the five modes of transport, including railways, highways, waterways, civil aviation and urban transport, released by the relevant authorities, we have introduced rail-water intermodal transport, China-Europe express trains, high-speed rail passenger transport, Electronic Toll Collection (ETC) and 12 strategies to improve the quality of vehicle fuel, including enhancing port efficiency and maritime energy efficiency. Ship fuel quality; pollution control and emission reduction at solid and liquid bulk cargo terminals; enhancing civil aviation's energy conservation and emission reduction capabilities; electric public transport; and rail transit. A calculation model for reducing air pollutants and greenhouse gas emissions was proposed based on the fuel method, transportation energy consumption, emission factors and alternative transportation volume. Twelve scenario emission reduction estimation methods based on analogy and statistical analysis were also proposed. Based on estimated reductions in fuel, air pollutants and CO₂, the effectiveness of clean and low-carbon development in comprehensive transportation has been reviewed since 2013. Prospects for the development of clean and low-carbon comprehensive transportation have been established in response to the problems and challenges we face.

To provide integrated communication-navigation means for maritime distress and safety communication, China has established the BDMSS (BeiDou Message Service System) based on the BeiDou system's regional short message capability. After five years of operation, BDMSS has been successfully recognized by the IMO (International Maritime Organization) as a GMDSS (Global Maritime Distress and Safety System) service provider. This paper outlines the evaluation and recognition procedures for mobile satellite systems used in GMDSS, as defined by the IMO and the IMSO (International Mobile Satellite Organization). It examines BDMSS's application process for IMO recognition and the technical and operational assessment conducted by IMSO. Key assessment points for BDMSS, including availability, restoration and spare satellite arrangements, priority mode, on-site demonstration scenario design, and additional considerations, are analyzed. The results enhance understanding of the international approval and evaluation criteria for potential GMDSS mobile satellite systems. Furthermore, they provide valuable references for future revisions of IMO Resolution A.1001(25) and for incorporating international maritime requirements into the design of new mobile satellite systems.

In order to study the safe deployment of tugboats under the uncontrolled situation of large LNG (Liquefied Natural Gas) ships in the dock-constrained waters, and to ensure the safety of port terminal operations, the study adopts the CFD (Computational Fluid Dynamics) analysis method, based on the wind flow interference model, and calculates the hydrodynamic parameters and determines the emergency tugboat deployment strategy by simulating the drift process of the large LNG ship under different working conditions. Taking Wenzhou Xiaomendao as a case study object, the study focuses on analyzing the ship motion process of Qmax LNG ship under the working condition of sudden loss of control, and calculates the drift distance, which is used to guide the emergency deployment of tugboats. The results of the study show that the emergency deployment strategy of tugboat under different working conditions can be clarified by CFD analysis. This study provides scientific support for the safety of large LNG vessels in port transportation and provides an effective basis for emergency decision-making for port management to ensure the safe operation of ports and shipping industries.

To improve the comprehensive evaluation system of ports and move beyond the single evaluation mode of "throughput only," this study investigates a comprehensive evaluation index system for world-class ports. Firstly, the concept and connotation of world-class ports are interpreted using the "Theme-Objective-Path-Service" analysis framework. A comprehensive evaluation index system for world-class ports is proposed, centered around weighted throughput, ship service efficiency, connectivity, economic contribution, and green and security levels. The index weights are determined using the Analytic Hierarchy Process, and a fuzzy comprehensive evaluation model for world-class ports is established. Based on this model, 34 global sample ports are selected for comprehensive evaluation. The evaluation results show that the ports of Singapore and Shanghai rank among the top two in terms of comprehensive scores, placing them in the world's leading lineup. Nine other ports, including Rotterdam, Ningbo-Zhoushan, Busan, and Qingdao, rank among the top ports globally with scores above 80. Finally, suggestions for conducting comprehensive evaluations of world-class ports are proposed, focusing on establishing world-class port evaluation standards and strengthening the application of big data from the Automatic Identification System (AIS).

To ensure the safety of navigation in the bridge area, this paper proposes a ship automatic monitoring method based on the fusion of vision and AIS (Automatic Identification System). The ship contour information in the image is extracted by the YOLOv5 (You Only Look Once version 5) target detection algorithm and the Canny algorithm. A distance, azimuth, and height measurement model of the visual target in the bridge area is constructed to achieve the three-dimensional positioning of the ship. An abnormal behavior detection model is established using the ship navigation situation data from the fusion of vision and AIS to automatically identify and monitor monitoring of dangerous ships in the bridge area. The experimental results show that: In cases of single and multiple ships, the accuracy of visual and AIS data association is 98.45% and 91.29%, respectively; The method can effectively monitor the motion state of ships in the bridge area. This paper provides an effective method for ensuring the safety of ships and bridges.

With the development of autonomous navigation for unmanned ships, identifying ship collision avoidance behavior has become a key factor in their independent decision-making. To address the inefficiency and misjudgment issues of existing ship trajectory recognition algorithms, this paper proposes a data mining model based on the steering point of a sliding window for ship collision avoidance. When the model identifies a ship's steering point, it first evaluates the change characteristics of the heading at adjacent time points in the ship's Automatic Identification System (AIS) data using a fixed sliding window. Then, the slope change of the trajectory points at adjacent moments is calculated for verification, and the earliest turning point of the heading change within the window is marked. Finally, a variable sliding window is used to maintain the heading change and error parameters during the trajectory change process, determining whether the steering point is a collision-avoidance steering point. The model is experimentally compared with the Douglas-Peucker (DP) algorithm. The results show that the model can effectively identify whether a ship's steering is collision avoidance behavior, resolve the issue of the DP algorithm misjudging steering points due to data fluctuations, and extract the earliest steering point during the ship collision avoidance process to assist in collision avoidance decision-making. This model can be applied to the research and development of intelligent collision avoidance decision-making systems, ensuring the safety of ship navigation.

In response to the IMO Preliminary Strategy for Greenhouse Gas Emission Reduction from Ships and the domestic "3060 Double Carbon Goal", carbon reduction routes applicable to the domestic fleet are proposed. Using the fleet carbon reduction analysis model, the carbon reduction amount, carbon intensity and carbon reduction cost of a domestic shipping company's fleet based on the above fuel routes are analyzed by defining the fossil fuel, methanol fuel and ammonia fuel routes. The results of the study show that the fleet based on methanol and ammonia fuel paths can meet the requirements of the "Preliminary Strategy for Ship Temperature IMO Room Gas Emission Reduction" and the domestic "3060 Double Carbon Goal", and that the fleet can be transitioned from the traditional bunker fuel type to the methanol/ammonia ready type as soon as possible in the near future, and then to methanol/ammonia powered type in the medium and long term. In the near future, we can transition from traditional fuel oil ships to methanol/ammonia fuel ready (methanol/ammonia fuel power system preset) ships as soon as possible, and in the middle and long term, we can gradually transition to methanol/ammonia fuel-powered ships; green methanol and green ammonia have their own advantages, and the number of future medium and long term commercial applications mainly depends on the differences between green methanol and green ammonia in the aspects of availability and economy.

To clarify the development stages and characteristics of China's major coastal ports since its accession to the WTO, a quantitative study is conducted based on the monthly container throughput data of seven major coastal ports from 2002 to 2023. Multivariate change point analysis is introduced to objectively reflect the stage characteristics of port development, and the Chow test is used to verify the reliability of the quantitative research results. The study shows that the major coastal ports in China can be divided into six development stages over the 22-year research period. By combining the characteristics of port container throughput growth in different stages and considering key events such as China's accession to the WTO at the end of 2001, the outbreak of the global financial crisis in 2008, and the spread of COVID-19 in 2020, the six stages are identified as: rapid growth period (2002~2005), fluctuating development period (2006~2010), recovery growth period (2011~2013), stable platform period (2014~2017), development differentiation period (2018~2020), and resilient growth period (2021~2023). Each development stage exhibits distinct characteristics, closely related to the economic and trade conditions of China and the world during the respective periods.

Existing studies indicate that the longer the queue length of vessels, the greater the channel saturation. To predict channel congestion, this study proposes a congestion prediction method that considers the maximum queue length based on the fundamental principles of traffic wave theory. The model utilizes Automatic Identification System (AIS) data to extract traffic flow characteristic parameters and, considering the differences in navigation behavior among ships in different waters, proposes a method for dividing the channel into characteristic areas. The queue length in traffic wave theory is selected as the evaluation index for congestion, and a method for predicting the maximum queue length based on Gaussian process regression is proposed to achieve the prediction of waterway congestion levels. A case study is conducted in the Yuxi River section of the Yangtze River Basin. The results show that the theoretical value of the maximum queue length in this section in July 2020 is 0.98 km, and the Adjusted R² index of the established regression model is 0.88, predicting a maximum queue length of 1.34 km with an error of 0.37 km compared to the theoretical value. The research results demonstrate that the proposed model has a high degree of interpretability and can effectively predict the maximum queue length, thereby enabling the prediction of channel congestion. This study provides a theoretical basis for improving the level of maritime supervision services.