The article presents integrated digital and analog radio communication technologies to be used in inland navigation. The communication model of an integrated Iridium satellite system with DSC-VHF in emergency situations for the needs of inland navigation was presented. The functional requirements of the Iridium satellite system for inland navigation were characterized in detail. Finally, the applicability of the Thuraya satellite system for inland navigation was presented.
The Norwegian Coastal Authority has introduced Reference Routes for Navigation to enhance maritime safety and efficiency along the Norwegian coast. These routes provide predefined tracks aimed at minimizing human errors in route planning, improving traffic separation, and promoting predictable traffic patterns. This study evaluates the impact of these reference routes by analysing AIS tracking data from before and after their implementation. A quantitative approach was used, incorporating statistical methods such as T-tests, linear regression, and K-Means clustering to assess vessel compliance and adaptation. The findings indicate a statistically significant, yet modest, improvement in adherence to reference routes, with vessel characteristics playing an important role in compliance levels. These results suggest that while voluntary routing measures influence traffic patterns, complete compliance remains unlikely. Further research is recommended to validate and expand upon these findings.
Maritime traffic is prevalent worldwide, with particularly high density in coastal waters. To ensure safety and efficiency, Vessel Traffic Service (VTS) centers monitor and coordinate maritime traffic. For this purpose, VTS centers utilize various sensor and communication technologies such as radar, Automatic Identification System (AIS), electro-optical systems or radio communication. Additionally, any Vessel Traffic Service Operator (VTSO) is motivated to utilize a Decision Support Tool (DST). The LEAS project addresses emerging challenges at VTS centers. One key challenge results from the continuous evolution of maritime traffic, in particular, its ever increasing automation and autonomization. Another key challenge is the growing shortage of skilled workers. Consequently, it is crucial to process increasing volume of maritime traffic data while maintaining or improving safety and efficiency. DSTs at VTS centers must be adapted to these emerging challenges, accordingly. In the LEAS project, we develop and evaluate a demonstrator which represents a DST. This demonstrator is being developed in close collaboration with VTSOs to address these challenges. Most notably, it has a situation detection which makes use of Artificial Intelligence (AI) methods and displays relevant information in an intuitive Human-Machine Interface (HMI). The demonstrator is evaluated using simulated traffic scenarios in the German Bight and Baltic Sea, with VTSOs as test subjects. This paper provides an overview of the project and demonstrator. First, we introduce the key requirements for the demonstrator and discuss their impact on the system architecture. Next, we present its AI-based situation detection. We explain the underlying formalism of the situation detection and resolution as well as its implementation in the demonstrator. Finally, we evaluate the capabilities and limitations. The paper concludes with an outlook to future work with focus on potential deployment at DST at VTS centers.
Automatic Radar with Plotting Aids is the basic means of preventing collisions at sea for many years. However, the use of the radar on a moving vessel requires image stabilization, which has been at least for the last 50 years solved by coupling with the gyrocompass and the log. In the present century, the widespread use of Global Navigation Satellite System receivers has led to the common practice of interconnecting this receiver with many other systems on ships. This is often also the case for radar, although GNSS gives information about movement related to the ground, whereas the International Maritime Organization recommends using parameters relating to water. The mandatory and widespread equipping ships with the Automatic Identification System means that this system is increasingly used in the process of collision avoidance, but also with the use of ground-referenced data. The aim of the paper is to investigate whether this is acceptable and what are the limits of this practice. This question becomes increasingly important in the context of the growing number of unmanned vessels. Not all, especially small autonomous surface vehicles will be equipped with radar and may also use AIS transmissions in collision avoidance algorithms. Studies have shown that this may pose a risk of collision. At low ship speeds, if the current speed exceeds 5 knots and the direction of the current significantly deviates from the course of one of the ships, there is a risk that the planned maneuver will not be carried out. This may mean that the closest approach distance will be significantly different from the planned one.
In contemporary maritime navigation, ships in distress primarily rely on satellite systems in conjunction with radio systems within the framework of the Global Maritime Distress and Safety System (GMDSS) to transmit distress signals. However, the insufficient confidentiality of satellite data enables pirates engaged in ship hijacking to intercept these signals, potentially endangering the safety of hostages on board. Additionally, the high communication costs associated with satellite information transmission often discourage fishing ships from incurring these expenses. Given these cost constraints, this study seeks to develop an intelligent emergency distress notification method integrated with the Automatic Identification System (AIS). Specifically, this study introduces an innovative intelligent radio emergency notification system by incorporating the concept of radio relay stations. The proposed system integrates the Genetic Algorithm (GA) with the Maritime Geographic Information System (MGIS) as an alternative rescue method for ships in distress. The system collects all relevant information from the distressed ship through shore stations, enabling it to respond to the ship and verify the receipt of distress messages transmitted via AIS. The proposed method functions as an intermediary for distress signal transmission and confirmation. By gathering ship positions, it establishes a mobile network for message dissemination, thereby enhancing the reliability and efficiency of emergency distress communications at sea.
Maritime navigation is currently evolving along two parallel paths: e‑Navigation, designed to integrate and harmonize ship‑ and shore‑based information for enhanced decision‑making, and Autonomous Navigation, which seeks to transfer these decisions to automated and remotely supervised systems. This paper explores how these two trajectories align and diverge, focusing on their impact on marine pilots. The e‑Navigation concept, including the IMO‑endorsed S‑Mode interface standardization, has demonstrated tangible benefits for pilotage by improving situational awareness, operational safety, and data exchange through standardized user interfaces and information flows. In contrast, the transition toward autonomous vessels raises significant technological, operational, legal, and human‑factor challenges, including redefined pilot roles, liability issues, mixed‑fleet operations, and cybersecurity risks. While both approaches rely on similar enabling technologies, their design philosophies differ fundamentally: e‑Navigation augments human expertise, whereas Autonomous Navigation seeks to reduce or replace it. The paper concludes with recommendations for pilot training, competencies, and regulatory frameworks, emphasizing human‑machine collaboration and staged implementation.
This paper examines the influence of lateral wind forces on ferry operations within the port of Gazenica, situated on the Croatian Adriatic coast. Utilizing wind data collected from May 2017 to June 2024, the study identifies southeasterly (SE) winds as the most critical factor affecting ferry maneuverability due to their frequency and intensity. The research assesses wind-induced forces on three specific ferries—"Brac," "Ugljan," and "Juraj Dalmatinac"—comparing these forces against their maximum propulsion capabilities. Findings reveal that extreme SE wind conditions can surpass the thrust capacity of these vessels, elevating the risk of drifting and grounding, as illustrated by the grounding incident of the ferry "Cres". Consequently, the study highlights the necessity for advancements in ship design, propulsion systems, navigational aids, and port infrastructure to mitigate risks associated with high wind speeds. Implementing such measures is vital for ensuring the safety and operational reliability of maritime activities in the port of Gazenica and comparable settings.
Navigation through the TSS represent a certain amount of stress for watch crew. In such areas the traffic is heavier and close quarter situations and collisions are more likely to occur. Despite the COLREG regulations for navigation in TSS there are always situations which are differently interpretated by navigators and due to dense traffic avoiding collision can be challenging. As the COLREG rules state the collision can be most efficiently avoided by altering ship course, however sometimes that can be difficult in TSS during heavy traffic. This paper analyses the collisions and close quarter situations in TSS which could be avoided by reducing ship speed and reproduce similar situations in navigation simulator. Such reproduction on navigation simulator is used to analyses behaviors of navigator in collision situations and what prevents them to use speed reduction in collision avoidance. The results of the research may be used to familiarize the navigators that in certain situations reducing ship speed could be most efficient action to avoid collision.
The maritime sector’s rapid digital transformation – including the integration of IT and operational technology (OT) systems and the rise of autonomous vessels – has significantly expanded the cyberattack surface[1] . Artificial Intelligence (AI) now plays a dual role in this landscape, acting as both a powerful enabler of cyberattacks and a critical tool for cybersecurity defense [2] . This paper explores current and emerging uses of AI in offensive and defensive cyber operations targeting maritime systems and infrastructure. On the offensive side, threat actors are leveraging AI for sophisticated attacks such as AI-generated spear phishing, polymorphic malware generation, GPS spoofing, and manipulation of industrial control systems (ICS)[3], [4]. On the defensive side, AI is employed in anomaly detection, predictive analytics, autonomous vessel and port monitoring, and other security applications[5]. The paper also examines vulnerabilities of AI itself – including adversarial attacks, data poisoning, and model manipulation – and discusses strategies to enhance maritime cyber resilience. Key strategies include the use of digital twin simulations, AI-driven deception (honeypots), adversarial training, explainable AI, and international cooperation for information sharing. By analyzing both offensive and defensive developments, this study provides a comprehensive perspective on the dual-use nature of AI in shaping the future of maritime cybersecurity.
This paper provides a demonstrative method between theoretical and practical concept for understanding NMEA lines. This research arises from a teaching innovation project called "NMEA Protocol: from theory to practice in internal communications" whose objective is to analyze and give visibility to radio engineering students, in a practical, simple and real way, complex concepts present in internal communications on board. These allow the transmission; reception and processing of information shared by the radio and navigation teams of a wheelhouse. The challenge will be met using easily accessible electronic devices both for their low cost and for their availability on the market. The results indicate that it is possible to demonstrate to the student complex theoretical concepts explained in class, in part has aroused the interest of them to innovate and experiment on their own and in a particular way, making them partners of their own formation.
Maritime and coastal areas are the lifeblood of many countries. They are vital to the prosperity of countries because they provide trade routes, regulate the climate, are a source of organic and inorganic resources and energy, and provide a place for the public to live and relax. Increasingly, however, there are divergences and barriers to the use of marine areas. On the one hand, available and developed technology and knowledge enable increasingly improved use of the sea. On the other hand, the combined effect of these activities leads to conflicts of interest and the deterioration of the marine environment. The purpose of this study is to analyze the feasibility of using automatic identification system (AIS) maritime traffic data, in terms of its suitability, to correctly assess the utilization of the potential of a specific fleet within the offshore shipping industry. In addition, the authors undertake the task of determining to what extent activities relating to the GPS position of the ship, ship type (i.e., cargo or passenger), ship status (i.e., aground, anchored, moored, not under command, restricted maneuverability, underway sailing, or underway using its engine), ship draught, service speed, total engine power, and deadweight constitute areas and methods for optimizing the use of the offshore fleet under all the conditions previously described that limit this optimization. Given the stated goal, this paper uses both a literature review procedure and statistical methods to conduct a comparative analysis.
Over the last decade, the Baltic ports have welcomed a remarkable growth, especially oil transportation and containerised flows. The regional container network is mainly made up of feeders services. Consequently, Baltic ports as nodes of a regional maritime network are integrated into a larger system. Indeed, the port development and the evolution of maritime traffic are symptomatic of economic and territorial mutations. In this context, the Polish ports, Gdansk and Gdynia, were originally mainly connected to the Polish hinterland and Central European market. They are now becoming new transhipment ports for the regional traffic. It is especially the case for Gdansk which recorded considerable and continued growth in container traffic during the last years. The purpose of this paper is to analyse the activity of the polish container ports and examine their role and position in the Baltic and European container network. This study is based on a literature review and mainly on the analysis of a statistical database as well as using Automatic Identification System data.
With economic globalization, ships tend to be larger and faster, and the volume of maritime traffic is increasing. Ships sailing in waters with dense traffic flow are easy to fall into complicated multi-ship encounter situations and have a high risk of collision. Thus, it is crucial to conduct risk analysis in such situations. In this paper, a modified collision analysis method for detecting dangerous multi-ship encounters in ports and waterways is proposed. The velocity obstacle algorithm is utilized to detect encounters. The model of the elliptic ship domain was integrated into the algorithm as the criteria. The Boolean operation was also used in the multi-ship encounter. A case study is conducted to illustrate the efficacy of the improved model, and a comparison between the existing method and the formal model is also performed. The results indicate that with the integration of the ship domain, the proposed method can effectively detect the encounters of multiple ships which are dangerous to collide.
The Automatic Identification System (AIS) device is mandatory for ships that comply with the International Convention for the Safety of Life at Sea (SOLAS). AIS is intended for vessel traffic monitoring to improve shipping safety. In the examined area, the base station received 22 128 345 messages in April 2019. Approximately 80% of these messages included position reports, which were subjected to geospatial analysis. One possible utilization of AIS messages is used in an intelligent maritime transport statistics production system called TranStat in the Gospostrateg project. This specific study compares the speed of executing geospatial queries in a relational PostgreSQL database engine and a non-relational MongoDB database engine. For the purpose of this research, we have defined four AIS datasets, four test polygons of varied number of vertices, and a reference point on a fairway. The tests were used to assess the execution of the queries in a database that returns the number of ships located in a predefined area and the number of ships located at a preset distance from the defined point. It has been determined from the test results that test queries are performed faster and data stored in the database occupy less disk space in MongoDB than in PostgreSQL. Faster geospatial analysis of AIS messages may improve the navigation safety by earlier detection of dangerous situations.
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The stress-strain characteristics of a clot during loading/unloading mechanical cycles are significant features to assess the underlying mechanisms of thrombectomy, especially when multiple thrombectomy attempts are required. We investigated a damage model to predict loading/unloading response of clots. To study the validity of the model, we tested theoretical models to reproduce the experimentally obtained mechanical characteristics of clots under various conditions. Three types of clot analogs with different red blood cell (RBC) compositions were prepared. Cylindrical clot analogs were formed for the tensile and compression tests. Loading/unloading tests at 80% of strain were conducted, where the material parameters were determined by fitting the results to a theoretical curve combining the damage model and the elasto-plastic constitutive model. Through the computation for theoretical curves, unique characteristics of clots were revealed such that the hysteresis loss rate did not change by varying RBC contents, except for the clot created with 0% RBC composition, under compressive loading. In addition, the plastic strain decreased as the RBC content decreased under tensile loading, whereas it increased as the RBC content decreased under compressive loading. A three-dimensional finite element method (FEM) was employed with the determined parameters. The FEM could accurately reproduce the experimental stress-strain curves for all types of clot analogs and for both loading types up to a strain of 80%. The results indicate that the theoretical model which incorporates and combines the damage model and the elasto-plastic constitutive model is applicable to predict the non-linear stress–strain behavior of clots under loading and unloading.
The production and analysis of transport statistics is part of the process of maritime transport management and monitoring. As there is strong need to protect the environment through the reduction of greenhouse gas emissions by the transport sector, CO2 in particular, it is necessary to assess the emissions of pollutants emitted by sea-going ships. The article presents an intelligent method of estimating pollution volumes based on harmonised sets of data on vessel traffic obtained from the monitoring of the Automatic Identification System and developed artificial intelligence models. The created methods allow estimating emissions of pollutants from individual sea vessels, aggregate pollutant amounts in a selected geographical area, or on a selected route and in port. The data obtained can be visualized for conducting statistical analyses. The work was performed under the TranStat project executed jointly with the Central Statistical Office. "The project financed by the National Centre of Research and Development as part of the program Gospostrateg, Agreement Gospostrateg1/383385/12/NCBR/2018”.
The main aim of this article is to present a method to process Inland AIS (automatic identification system) data that is part of RIS (river information services), as well as to synthesize and visualize information obtained from it for further analysis. This article presents problems with imaging the position of inland navigation units in the immediate vicinity of the Długi and Kolejowy Bridges in Szczecin. The passing of 80 inland units on this section of the Western Oder River was analyzed. Data were obtained from the AIS message database and industrial cameras of the RIS Monitoring Centre at the Inland Navigation Office in Szczecin. 35 units were equipped with AIS messaging devices. This article analyzed the data after previous processing, which consisted of selecting appropriate research units and decoding AIS messages recorded in the VDM message type (VHF Data Link Message). Then, the acquired positions of inland navigation units on the map were visualized to calculate the number of errors and their location. The obtained data were used to illustrate the locations of interference during the operation of transmitter-receiver equipment that prevented determining the exact position of inland navigation units in the immediate vicinity of the above-mentioned bridges.
This research features an overview of the available PLB technologies, their advantages, shortcomings and areas of their optimum application. A test of the locator transmitter emitting both 406 MHz AIS and 121.5 MHz signals was performed with a focus on tracking the homing 121.5 MHz signal. The efficiency of the homing signal was examined by using two separate radio locating systems. One of them comprised multi-purpose and widely available components and programs, while the other was a specialised radio beacon system with dedicated components. In addition to the results, their analysis and evaluation of efficiency, the paper discusses the applicability of the available PLB technologies and provides guidelines for adequate selection of the PLB devices and position indicating radio equipment.
This paper proposes an approach for identifying and characterizing shipping routes using information contained in Automatic Identification System messages broadcasted by ships and recorded by the coastal Vessel Traffic Service centre. The approach consists of using historical Automatic Identification System data to build a graph, where nodes are cells of a grid covering the geographical area being studied and the weights of directional edges are inversely related to ship movements between cells. Based on this graph, the Dijkstra algorithm is used to identify a potential safe route, assumed to be the most used route by ships between two locations. A second graph is created simultaneously, with the same nodes and edges, but with edge weights equal to the average speed of transitions between cells, thus allowing the determination of the average speed profile for any possible path within the graph. The proposed approach is applied to two scenarios: an approach to the port of Lisbon and the entry through the fairway to a RO-RO terminal in the port of Setubal in Portugal.
W artykule zaprezentowano koncepcję systemu R-Mode Baltic budowanego z wykorzystaniem stacji bazowych systemu AIS. Przedstawiono analizę teoretyczną dokładności wyznaczania odległości dla różnych wariantów wiadomości nawigacyjnej. Dodatkowo opisano wykonaną implementację programową a także zaprojektowane stanowiska pomiarowe.
EN
The article presents the concept of the R-Mode Baltic system using AIS base stations. Theoretical analysis of the accuracy of distance determination for different navigation message variants have been described. In addition, the software implementation and the designed test-bed are also depicted.
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