Issue №39

The increase in the number, size, and speed of ships, the introduction of new information technologies in navigation, the development of autonomous ships, and the growing presence of these ships on waterways alongside conventional ships have led to changes in ship control and necessitated the reflection of these changes in the International Regulations for Preventing Collisions at Sea (COLREGS). The first part of the article highlights the differences between the tasks of interpreting the Rules and bringing them up to date. The section “Interpretation of the COLREGs” presents a proposed method for determining the values of parameters for circular and semi-elliptical and semi-circular danger domains appropriate for navigation conditions, based on the available results of statistical analysis of the values of maneuvering parameters used on ships. A new method for determining the stage of timely actions by ships has been developed. The section “Update of COLREGS” presents the results of a critical analysis of the Rules for Steering and Sailing in Part B of COLREGS, notes a number of shortcomings in these Rules, and justifies and presents proposals for amending and supplementing the provisions of COLREGS. Attention is drawn to the need to adhere to the principles of classification when dividing situations involving the approach of two vessels into separate types. The section “Taking into account the features of MASS” presents the issues discussed in connection with the development of additions to COLREGS to address this task.

Keywords: collision avoidance, collision risk, vessel approach situations, autonomous vessels, interpretation of COLREGS, updating of rules.

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The study investigates how the accuracy of vessel position determination depends on the method used to estimate coordinates from measured navigation parameters. While the conventional approach assumes that random measurement errors follow a normal distribution and therefore justifies the use of the least squares method, recent statistical evidence indicates that navigation measurement errors often deviate from normality. In response, the study substantiates the applicability of mixed distributions of the first and second types for describing such errors. These distributions are theoretically justified by the structure of random error sample formation and are analytically convenient because their density and distribution functions can be expressed in elementary form. The hypothesis was tested through field observations collected during a six-month voyage. The results show that bearing and distance measurement errors observed over short time intervals of up to 8 hours are adequately described by the normal distribution. However, for longer observation intervals of one day or more, these errors follow mixed distribution laws, and the degree of deviation from normality increases with the duration of the measurement interval. To assess the effectiveness of vessel position estimates derived from redundant position lines and processed by the least squares method, simulation-based computer modeling was carried out for cases in which position line errors obeyed mixed distributions of the first and second types. The results demonstrated close agreement between theoretical and simulated efficiency estimates for all values of the essential parameter, confirming that the accuracy of vessel position determination depends on the selected coordinate estimation method.

Keywords: navigational safety, efficiency of the coordinates, lines of position, normal equations, excessive measurements.

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The article examines the development and implementation of an intelligent system for commercial risk analysis in sea agency operations based on a hybrid combination of deep learning methods. The relevance is determined by increasingly complex maritime commercial relations, high uncertainty, heterogeneous data, and the limited effectiveness of classical approaches to multidimensional risk assessment. The purpose of the study is to develop an intelligent system capable of integrating financial and operational time series, counterparty tabular data, and textual information to generate consistent predictive assessments of commercial risks. The proposed approach formalizes overall commercial risk as an aggregated nonlinear function of credit–counterparty, liquidity, operational–financial, and market–macroeconomic risk components. The system pipeline includes data collection, preprocessing, intelligent modeling, integration, and interpretation of results. Its analytical core combines recurrent neural networks, deep models for tabular data, and transformer architectures within a unified hybridization module. Experimental results demonstrate that the hybrid model outperforms individual approaches in forecasting accuracy and risk-state classification, as reflected in lower MAE and RMSE values and a higher area under the ROC curve. The results confirm the synergistic effect of integrating deep learning models and substantiate the feasibility of applying the system to support proactive managerial decision-making in sea agency companies.

Keywords: ensemble machine learning, deep learning, Sea Agency, decision support system, lightgbm, gradient boosting, operational risk mitigating, service-ergatic systems, stacking generalization, predictive analytics, port logistics.

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This paper presents an experimental evaluation of a YOLOv8n-based computer vision model for ship aspect recognition under real maritime observation conditions, with particular emphasis on its relevance to COLREG (International Regulations for Preventing Collisions at Sea). From a navigational perspective, a vessel’s aspect relative to the observer is more critical than its type, as it directly informs the assessment of encounter situations and collision risk. Unlike most existing studies focused on vessel detection using curated image datasets, this work addresses the more complex task of determining vessel orientation and evaluates model performance using real-world video data collected under varying conditions of distance, illumination, and weather. The model was trained on an annotated image dataset including eight aspect classes and negative examples and tested on operational video sequences. A structured evaluation methodology is applied, distinguishing between correct localization and correct aspect classification. Results indicate that reliable recognition is achieved at short to medium distances, with optimal performance up to approximately 0.85 nautical miles in daylight. Performance degrades with increasing distance and in low-light conditions. A key source of false positives is identified as structural elements of the observer vessel not represented in the training data. The study demonstrates the feasibility of using lightweight deep learning models for COLREG-relevant situational awareness, while highlighting current limitations and the need for dataset expansion and targeted augmentation to improve robustness.

Keywords: YOLOv8n, object detection, object localization, object classification, confidence score.

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The presence of a water layer moving together with a ship during any maneuver leads to the occurrence of added masses and moments acting on the ship hull, which significantly affect the components of inertial forces and moments. This effect becomes particularly noticeable at shallow depths and becomes critical in shallow water conditions. In planar motion of a symmetric ship, four hydrodynamic characteristics of the hull are considered non-zero: longitudinal and transverse added masses, the added moment about the ship’s axis of rotation, and the static moment caused by the shift of transverse added masses relative to the axis of rotation. When developing mathematical models of ship motion, dimensionless quantities are introduced, referred to as the coefficients of the corresponding added masses and moments. The shallow water effect is described by means of an influence function defined as the ratio of these coefficients in shallow water to those in deep water. Numerous studies have been devoted to the development of mathematical models for influence functions, based on both theoretical and experimental investigations. In this paper, a comparative analysis of existing mathematical models for influence functions is carried out, revealing significant discrepancies in the results obtained using these models. The analysis of available data also made it possible, using regression analysis methods, to develop new adequate mathematical models of the influence function and to investigate the effect of relative water depth and hull geometric characteristics on added masses and moments.

Keywords: ship hull, added masses and moments, added mass coefficients, shallow water effect, mathematical models.

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The articles investigates a method for automatic determining the position of a vessel and the formation of sentences of the digital interface of navigation and radio communication devices according to the IEC 61162-1 (NMEA-0183) standard in conditions of degradation or complete loss of signals of global navigation satellite systems (GNSS). The proposed alternative approach is based on the combined use of Automatic Identification System (AIS) data received from the neighbouring vessels that are not in the GNSS impact zone and measurements from the ship’s own radar/ARPA are available. Two mathematical models for position computation are examined: one utilizing range and bearing measurements (Range+Bearing) and another using range-only measurement via trilateration (Range only). Simulations were conducted in MATLAB using the Monte Carlo method, accounting for standard radar and AIS measurement errors as well as the asynchrony between their respective measurement cycles. It is established that synchronization of AIS and radar data through extrapolation of target coordinates is a fundamentally essential element of the algorithm, as it significantly reduces the root mean square error of vessel position determination. The Range+Bearing model demonstrates superior accuracy under most conditions; however, the Range only model may be preferable when bearing measurement quality is poor. The statistical distribution of position errors is well approximated by the Rician distribution. The results confirm the viability of the proposed approach as a reliable backup navigation method in conditions of electronic warfare conditions to counter jamming or spoofing cyber-attacks.

Keywords: Global Navigation Satellite Systems (GNSS), electronic warfare, digital interface, trilateration, coordinate extrapolation, data synchronization.

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This paper discusses improvements to the methodological support of a laboratory course on ship seaworthiness. The course uses an experimental facility based on a scale ship model and is intended to help students understand the relationship between loading conditions and ship stability, compare theoretical calculations with model-test results, and apply stability criteria in practice. Processing the experimental data requires accurate hydrostatic characteristics of the model hull. Therefore, the laboratory course can be significantly improved by extending and refining the available hydrostatic data without modifying the experimental apparatus. The geometry of the model hull was reconstructed using reverse-engineering techniques. A CAD model was developed from laser scans of the outer surface of the scale model and then used to calculate hydrostatic elements and cross-curves of stability. The resulting hydrostatic tables are more detailed than those previously available and provide a more convenient basis for accurate student calculations. The newly obtained cross-curves of stability, which were absent from the existing laboratory manuals, make it possible to substantially improve the laboratory work devoted to constructing curves of statical stability and allow students to perform independent calculations for different loading conditions. The proposed approach was tested for several loading conditions of the model. In addition, methods for evaluating measurement errors were analyzed. Based on this analysis, an additional randomness check for small samples and an uncertainty evaluation procedure using Student’s t-distribution are recommended. The results can be used to improve both the experimental and calculation components of the laboratory course.

Keywords: experimental study of ship stability, scale models for stability trainings, reverse engineering in shipbuilding, statistical processing of measurement errors, laboratory works in maritime education.

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This paper presents a formalized mathematical framework for constructing Limiting Danger Lines (LDLs) on Electronic Navigational Charts (ENCs), incorporating hydrographic data uncertainty represented by CATZOC quality categories. The study addresses the lack of automated LDL generation in modern ECDIS systems, particularly for linear and polygonal bathymetric features, as well as the insufficient integration of data quality indicators into existing navigational safety models. A review of current ship-routing methods demonstrates that most approaches rely on discrete or approximate spatial representations, which limits the accuracy of the geometric interpretation of navigational hazards. In contrast, the proposed framework introduces a novel interpretation of CATZOC as a parameter of geometric uncertainty, transforming it from a descriptive attribute into an operational component of spatial modeling. The model is based on computational geometry techniques, including Minkowski sums and buffer operations, ensuring consistent spatial expansion of ENC objects such as soundings, isobaths, and depth areas. This enables the formation of a continuous hazard field rather than discrete safety contours. Additionally, the framework incorporates route dependence through cross-track distance (XTD), allowing hazard boundaries to be dynamically adjusted based on the planned vessel trajectory. The proposed approach unifies point, line, and polygonal ENC features within a single geometric structure, eliminating inconsistencies in hazard representation. It also enables a transition from threshold-based safety checks to continuous spatial analysis of navigational risk. The model is particularly effective in areas with low-confidence hydrographic data, especially CATZOC C, D, and in restricted waters where precise hazard delineation is critical. The results demonstrate that the LDL-based ENC safety framework provides a consistent and mathematically rigorous approach to modeling navigational uncertainty, offering significant potential for enhancing ECDIS functionality and improving maritime safety.

Keywords: ECDIS, safety navigation, CATZOC, LDL, Safety Depth, Safety Contour, XTD, Minkowsky sum, route check, spatial uncertainty, geometric buffering.

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The article examines modern approaches to ensuring maritime safety through the use of both traditional and innovative aids to navigation on seaways. A comparative analysis of the functioning of physical (visual) navigation aids and AIS-based aids to navigation (AIS AtoN) is presented.The main operational characteristics of traditional navigation aids are identified, along with their advantages and limitations under various hydro-meteorological conditions. Special attention is given to AIS-based aids to navigation, including physical, virtual, and synthetic AIS AtoN. Their operational principles, data transmission features, and representation on onboard navigation systems are analyzed. It is established that AIS AtoN provide high information availability regardless of weather conditions and enable rapid deployment for marking navigational hazards. At the same time, the study identifies key limitations associated with AIS AtoN, including positioning inaccuracies, potential technical failures and vulnerability to radio interference and signal manipulation. The feasibility of the integrated use of physical and AIS-based navigation equipment to enhance the level of maritime safety has been substantiated, and an upgrade option using controlled reception pattern antennas (CRPA) has been proposed to prevent the impact of false positioning signals.

Keywords: aids to navigation, AIS AtoN, e-Navigation, maritime safety, virtual navigation aids, CRPA.

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This article offers a comparative analysis of seaport automation, focusing on fully and semi-automated container terminals across the main maritime regions. The study systematizes the technological basis of automation – automated stacking cranes (ASC), automated guided vehicles (AGV), terminal operating systems and digital-twin tools – and links these solutions to engineering reliability, cyber resilience and terminal-level operational efficiency.The analysis distinguishes three dominant regional models: the European evolutionary model, based mainly on gradual semi-automation and social compromise; the North American environmentally driven model, where automation is closely connected with electrification and emissions reduction; and the Asian accelerated-transformation model, represented primarily by large-scale greenfield FACT projects in China.The paper identifies four cross-regional challenges that limit the practical effect of FACT implementation: vulnerabilities of operational technology systems, high capital intensity and long payback periods, weak interoperability between equipment and software suppliers, and the need for systematic workforce retraining.The results show that port automation should be considered not only as the deployment of robotic equipment, but as a complex techno-organizational transformation that requires coordinated engineering, digital, economic and institutional decisions.

 Keywords: port automation, container terminal, FACT, automated stacking cranes (ASC), automated guided vehicles (AGV), ship handling, safety of navigation, interoperability, digital twin, cybersecurity.

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