Navigational Decision Support Research Articles

Perspectives on Knowledge Representation in Maritime Education: A Qualitative Exploration of STIP Jakarta Cadets

This research investigates the perspectives of 240 Maritime Institute Jakarta (STIP Jakarta) cadets regarding knowledge representation in navigational decision support systems. Grounded in a qualitative descriptive approach, the study unfolds over three semesters, examining academic self-checked intelligence, professional competences, motivations, and the cadets' viewpoints on the complexities of maritime education. The cadets, enrolled in an international programme, undergo extensive preparation for internships within the global shipping industry, necessitating proficiency in English communication aligned with International Maritime Organization standards. The findings reveal a positive correlation between academic self-checked intelligence and professional competences, underscoring the significance of metacognitive strategies in shaping technical proficiency. Motivations, both intrinsic and extrinsic, emerge as crucial influencers shaping cadets' perspectives on knowledge representation. The study also highlights the evolving confidence of cadets in English maritime literacy, emphasising the necessity of tailored language instruction strategies. Recommendations for enhancing maritime education include promoting metacognitive strategies, integrating real-world applications, tailoring language instruction, providing continuous motivational support, and ensuring regular curriculum reviews. These recommendations offer practical insights for educators and administrators to refine instructional practices and align curricula with industry demands.While acknowledging limitations such as reliance on self-reported data and the focus on a specific cohort, this research contributes to the discourse on maritime education. It serves as a foundation for future studies, urging a diversified methodology and extending the scope to include multiple maritime institutions for a more comprehensive understanding. As STIP Jakarta continues to prepare cadets for global maritime challenges, the insights gleaned from this study are integral for adapting and advancing educational practices.

Interaction between COLREG-compliant collision avoidance systems in a multiple MASS scenario

The transportation systems are heading towards increasing autonomy in all domains, and the maritime field makes no exception. The International Maritime Organization has been working on releasing a regulatory framework for Maritime Autonomous Surface Ships (MASS) to keep pace with the technological developments in the field. Autonomous shipping forces the researcher and the designers to face a wide range of scientific challenges, such as navigation decision support systems, collision avoidance algorithms, path planning, navigation and control, sensor data processing and fusion, remote control, and communication, with the final intent of achieving a fully integrated and autonomous worldwide maritime transportation system, where a human-less collaborative conflict resolution could potentially retire the COLREGs. However, the maritime sector will first face a transition period where traditional ships will share the seas and interact with heterogeneous MASS with various autonomous capabilities featuring different and probably incompatible communication protocols. In such a scenario, the COLREGs will still play a primary role in helping the collision avoidance systems resolve conflicts and limiting the degrees of freedom. This paper aims to study the interaction among multiple vessels with autonomous collision avoidance capabilities operating in a close navigation scenario. The ships operate according to a COLREG-compliant collision avoidance algorithm. The paper relies on numerical simulation to systematically investigate different scenarios in which autonomous vessels operate and interact in the presence of fixed obstacles. Results are presented and critically discussed.

Simulation Tool for Winter Navigation Decision Support in the Baltic Sea

This article presents a novel simulation tool for the analysis of winter navigation operations in the Baltic Sea in the context of the Finnish–Swedish Winter Navigation System (FSWNS). The aim of the tool is to simulate the performance of the FSWNS under various potential future operating scenarios and thereby support decision making in matters affecting the operation and development of the FSWNS, for instance, in terms of icebreaking resources and ice class regulations. To this end, the tool considers key performance factors and characteristics of the FSWNS, such as the prevailing ice conditions, the ice-going capability and other technical characteristics of the relevant merchant vessels, the availability of icebreaking resources, and the features of specific icebreaking operations (e.g., convoys). The tool would allow testing of several “what-if” scenarios, answering questions related to optimal engine power for safe, efficient, and environmentally friendly navigation and the optimal scheduling of icebreakers for effective and cost-efficient assistance missions.

Quality Models for Artificial Intelligence Systems: Characteristic-Based Approach, Development and Application

The factors complicating the specification of requirements for artificial intelligence systems (AIS) and their verification for the AIS creation and modernization are analyzed. The harmonization of definitions and building of a hierarchy of AIS characteristics for regulation of the development of techniques and tools for standardization, as well as evaluation and provision of requirements during the creation and implementation of AIS, is extremely important. The study aims to develop and demonstrate the use of quality models for artificial intelligence (AI), AI platform (AIP), and AIS based on the definition and ordering of characteristics. The principles of AI quality model development and its sequence are substantiated. Approaches to formulating definitions of AIS characteristics, methods of representation of dependencies, and hierarchies of characteristics are given. The definitions and harmonization options of hierarchical relations between 46 characteristics of AI and AIP are suggested. The quality models of AI, AIP, and AIS presented in analytical, tabular, and graph forms, are described. The so-called basic models with reduced sets of the most important characteristics are presented. Examples of AIS quality models for UAV video navigation systems and decision support systems for diagnosing diseases are described.

Assessment of Ship-Overtaking Situation Based on Swarm Intelligence Improved KDE.

This paper proposes a data-driven risk assessment model for ship overtaking based on the particle swarm optimization (PSO) improved kernel density estimation (KDE). By minimizing the mean square error between the real probability distribution of the ship overtaking point and the kernel density estimation probability distribution calculated by the current kernel density bandwidth, the longitude and latitude of the ship overtaking point are displayed by the color corresponding to the probability as the cost objective function of the search bandwidth of the algorithm. This can better show the distribution of the overtaking points of channel propagation traffic flow. A probability-based ship-overtaking risk evaluation model is developed through the bandwidth and density analysis optimized by an intelligent algorithm. In order to speed up searching the optimal variable width of the kernel density estimator for ship encountering positions, an improved adaptive variable-width kernel density estimator is proposed. The latter reduces the risk of too smooth probability density estimation phenomenon. Its convergence is proved. Finally, the model can efficiently evaluate the risk status of ship overtaking and provide navigational auxiliary decision support for pilots.

SIRNet: Fine-Grained Surgical Interaction Recognition

Surgical interaction recognition (SIR) plays a crucial role in navigation decision support for minimally invasive surgery (MIS) or robot-assisted MIS. Currently, the research in SIR is at a coarse-grained level and barely considers the surgical interaction dependencies unrelated to endoscopic images. This work proposes a fine-grained SIR method named SIRNet aiming at predicting surgical interaction triplets. In the proposed SIRNet, a multi-head self-attention mechanism learns the relations among surgical interaction triplets without defining them before the training process, while a multi-head cross-attention mechanism learns the relationships between the endoscopic images and each triplet. The bipartite matching loss, which considers the permutation and combination of instruments, verbs, and targets, is adopted to make appropriate learning and prediction for each component in the surgical interaction triplet. Moreover, a weight attention module is designed to weigh the importance of each predicted surgical interaction triplet and each component in triplet when predicting final valid surgical interaction triplets. The experimental results show the proposed method improves the performance of fine-grained SIR. In addition, experiments also present the effectiveness of each module. The code is available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/cynerelee/SIRNet</uri> <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/cynerelee/SIRNet</uri> .

Towards NoSQL-based Data Warehouse Solution integrating ECDIS for Maritime Navigation Decision Support System

Maritime shipping is a complex process because it requires a continuous analysis of huge amounts of information. Much of this information has variable spatial and temporal properties. In addition, the analysis must be effective to help in making decisions in a timely manner. Generally the analysis is applied with Spatial On-Line Analytical Processing (SOLAP) basing on spatial data warehouses SDW. Data warehousing by current technologies with relational database management systems (RDBMS) cannot be applied effectively to manage the increasing complexity and volume of geo-referenced data. In order to increase the performance and availability of services, NoSQL databases technologies have appeared. This paper presents the modeling and the realization of a spatial decision support system (SDSS) for maritime navigation namely “Maritima”, basing on the integration of the ECDIS and OLAP systems. In fact, the spatio-multidimensional analysis of the stored data can benefit from the expressive power of the electronic navigation chart offered by the ECDIS system. In order to benefit from the NoSQL model advantages, we try to apply transformations for the conceptual model to create document NoSQL DW for maritime data. In addition to that, the multidimensional analysis at different dimensions and aggregation levels can generate beneficial indicators for the decision-aid and can be very useful in addition of other steering systems for secure maritime navigation. Finally, “Maritima” is tested with a set of spatial data related to two different harbors “Arzew” and “Oran” in western of Algeria.

An empirical ship domain based on evasive maneuver and perceived collision risk

This paper introduced a new ship domain concept and an analytical framework. The ship domain takes the point of the ship's first evasive maneuver as a basis and correlates it with the navigator-perceived collision risk level. The first evasive maneuver of a ship is detected based on the ship turning point identification and ship intention estimation. The available maneuvering margin (AMM) is utilized as a proxy to measure the perceived collision risk by the navigator. Interpreting the first evasive maneuver in terms of this AMM over a large sample of vessel encounters taken from automatic identification system (AIS) data finally enables an empirical estimation of the size of this ship domain. The method is applied to AIS data in the Northern Baltic Sea, and separate ship domains are constructed for the give-way and stand-on vessels with different maneuverability characteristics. Compared to the existing proximity-based ship domain, this ship domain explicitly incorporates the dynamic nature of the encounter process and the navigator's evasive maneuvers. Several advantages of this proposed ship domain concept and limitations of the presented modeling approach are discussed. Finally, possible future applications are explained, including waterway safety assessment and navigational decision support systems to reduce ship-ship collision risk.

A novel decision support methodology for oceangoing vessel collision avoidance

The wider use of electronic devices in shipping has led to the introduction of new navigation control systems and decision support tools for collision avoidance. The application of these systems improves the data utilisation and allows for the prediction of ship's performance in various operational conditions. In this study, a decision support methodology for collision avoidance of ocean going vessels is developed, taking into account both the ship's manoeuvrability and propulsion system performance whilst employing a new formulation for the estimation of the collision probability indicator. An integrated model that simulates the ship's manoeuvrability and propulsion system performance is employed to predict the required ship's hull and propulsion plant dynamic response. The integrated model couples a 3-DOF manoeuvring model with a mean value engine model, providing a fast but accurate prediction of ship and her propulsion system characteristics during specific manoeuvring scenarios. The derived ship trajectories populate a database that is employed as input to the developed decision support for investigating various encounter situations depending on the target ship's initial position, approach angle, trajectory and speed. The developed decision support provides the collision probability indicator as function of the ordered rudder angle and engine speed as the available control options to avoid the collision. This study provides support to the officer of the watch to make decisions on the ship and propulsion system control parameters during encountering situations, thus contributing to the safer maritime operations.

Ship Path Optimization That Accounts for Geographical Traffic Characteristics to Increase Maritime Port Safety

Maritime ports face challenges associated with navigation safety, operational efficiency, and management. With the development of the Internet of Things, artificial intelligence simulation technologies, geographical information systems, and cloud computing technologies as well as navigation aids and decision support systems in maritime transportation, ports have the potential to better manage traffic, loading, and unloading. Recently, there has been growing attention in unmanned shipping to support the maritime industry and the military. This paper aims to extend the application of geographical theory and methodology in unmanned ship path optimization. Automatic collision avoidance concerning maneuvering capabilities of ships as well as complying with maritime traffic rules remains a challenge. This study attempts to tackle development needs associated with path optimization in maritime travel. By integrating ship movement behavior, geographical features, and the International Regulations for Avoiding Collisions at Sea, the proposed methods seek to reduce the human error associated with maritime accidents. This paper proposes economic efficiency and safety-driven unmanned ship path planning that will promote the future growth of intelligent port development.

Navigation Decision Support: Discover of Vessel Traffic Anomaly According to the Historic Marine Data

During the last years, marine traffic dramatically increases. Marine traffic safety highly depends on the mariner’s decisions and particular situations. The watch officer must continuously observe the marine traffic for anomalies because the anomaly detection is crucial to predict dangerous situations and to make a decision in time for safe marine navigation. In this paper, we present marine traffic anomaly detection by the combination of the DBSCAN clustering algorithm (Density- Based Spatial Clustering of Applications with Noise) with k-nearest neighbors analysis among the clusters and particular vessels. The clustering algorithm is applied to the historic marine traffic data – a set of vessel turn points. In our experiments, the total number of turn points was about 3 million, and about 160 megabytes of computer store was used. A formal numerical criterion to com-pare anomaly with normal traffic flow case has been proposed. It gives us a possibility to detect the vessels outside the typical traffic pattern. The proposed meth-od ensures the right decisions in different oceanic scale or hydro meteorology conditions in the detection of anomaly situation of the vessel.

Towards a decision support system for maritime navigation on heavily trafficked basins

Sea traffic growing from year to year contributes significantly to increase of dangerous ship-ship encounters, which if not handled properly may result in an accident. The existing anti-collision systems installed on ships improve navigation safety significantly. However, navigation decision support systems solving complex encounter situations, providing navigator with simple but reliable information are still at the development stage.Therefore, this paper shows the concept of the Multi-ARPA (MARPA) system along with case studies. The system is intended to deliver to a navigator on board ship information on safe headings while encountering other ships. The safe headings are determined based on the level of hazard that other ships create or will create once the heading of the own ship is altered. The system may evaluate and visualize safe heading adopting multi-level or binary classification. The presented system operates on the basis of an algorithm designating direct hazards for the own ship for the set of manoeuvres in an encounter situation for numerous ships.

Implementation of Anti-Collision System on M/F ‘Wawel’

AbstractThe known navigational systems in use and methods of navigational decision support perform information functions and as such are helpful in the process of safe conduct of a vessel. However, none of these known systems provides a navigator with ready solutions of collision situations taking account of all the vessels in the proximity of own ship, where the Collision Regulations apply. This paper presents verification results of NAVDEC — new Navigational Decision Supporting System created by research team from Szczecin Maritime University both for ocean going ships and pleasure crafts. Verification was carried out in real condition on board Motor Ferry ‘Wawel’ (m/f ‘Wawel’), which belongs to shipowner Polferries (PŻB). During the journey to/from Nynashamn system was tested from customer perspective. Few suggestions for improvements were issued, which were discussed in this article.

The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion.

It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, which, through data fusion, takes into account measurements of the ship’s current position from a number of doubled autonomous devices. This increases the reliability and accuracy of prediction. The algorithm has been implemented in NAVDEC, a navigation decision support system and practically used on board ships.

An Analysis of Possibilities How the Collision Between M/V ‘Baltic Ace’ and M/V ‘Corvus J’ Could Have Been Avoided

Abstract The report presents the simulation results of collision between m/v ‘Baltic Ace’ and m/v ‘Corvus J’. The analysis was performed by means of navigation decision support system (NDSS) in collision situations. This system (NAVDEC) works out anti-collision manoeuvre using AIS (Automatic Identification System) and ARPA (Automatic Radar Plotting Aids) data. Then they are processed by specialized computing algorithms and presented to the operator on a display in the alphanumeric and graphic forms. The data on the specific navigational situation from the report of Bahamas Maritime Authority was used for the generation of signals transmitted to NDSS as a sequence of NMEA strings.

Decision Support in Collision Situations at Sea

The known navigational systems in use perform information functions and as such are helpful in the process of safe conduct of a vessel. One of the ways to assist in reducing the number of marine accidents is the development of systems which perform decision support functions, i.e. automatically generate solutions to collision situations. The use of information (and communication) technologies including knowledge engineering allows the generation of proposals for anti-collision manoeuvres taking into account the COLREGs. Demand for further enhancement of navigational safety by limiting human errors has initiated a trend to convert navigational information systems into decision support systems. The implementation of decision support systems will potentially reduce the number of human errors, which translates into a reduction of accidents at sea and their adverse consequences. This paper presents a summary of the research to date on the navigational decision support system NAVDEC. The system has been positively verified in laboratory conditions and in field tests – on a motor ferry and a sailing ship. Challenges associated with the development and implementation of such systems are outlined.

Multi-target collision avoidance route planning under an ECDIS framework

The universality of the automatic identification system (AIS) as well as the electronic chart display and information system (ECDIS) installations will provide revolutionary solution schemes for the e-navigation era of informatization, intellectualization, and integration. Based on this concept, this study adopted ECDIS as an information platform for navigational decision support and used the real-time navigation information received by the AIS to construct predicted areas of danger (PAD) for target ships. The advantages of direct viewing via the PAD in the collision avoidance give PAD a new application. Subsequently, spatial data from an electronic navigation chart (ENC) was employed as a basis for generating geographical obstacles. Through the integration of a geographic information system (GIS) module, specially designed evolutionary computation, and collision prevention regulations (COLREGS) knowledge as well as by comprehensively considering overall navigation situations, this system conducted obstacle avoidance processing and selection of a route. The system could generate a route that could simultaneously achieve multi-ship encounter collision avoidance and geographical obstacle avoidance. This is expected to provide mariners with greater convenience when working at sea, reducing their workload. This system can also be used as a reference for collision avoidance decision making.

A Trajectory Base Method for Ship's Safe Path Planning

The paper introduces a new algorithmic approach for ship's safe path planning. A new method utilizes a database containing a set of trajectories. An algorithm searches the trajectory base in order to find a safe trajectory that meets the optimality criterion (criteria) selected by the system operator. The method presented can be applied in a navigation Decision Support System. The method can also be adopted for applications in other environments, where similar problem occurs - in navigation of mobile robots or aircrafts. It should be emphasized that dynamic properties of an own ship are included in the calculations.The paper describes assumptions and constraints taken into account in the solution construction process, a presentation of the Trajectory Base Algorithm (TBA) Decision Support System (DSS) and the explanation of the algorithm operation principle. A successful application of the method proposed is confirmed by simulation tests carried out with the use of MATLAB environment. The results of calculations with the use of implemented algorithm are presented and compared with solutions received by an application of an approach based on a heuristic method - the Ant Colony Optimisation. The outcome and achievements are summarized in the conclusions.

Application of codimension one foliation in Zermelo's problem on Riemannian manifolds

We research the Zermelo navigation problem on Riemannian manifolds in dim⁡(R×M)=3 under the force representing the action of the perturbing “wind” distribution modeled by the vector field on manifold M. We consider a fibered manifold π:R×M→R where M represents the “sea”, R represents the time and π is the first canonical projection. We perturb it by a time-(in)dependent vector field on the manifold M with a codimension one foliation. We aim to research the behavior of the paths in reference to their optimization. Geometrically we find the deviation of geodesics under the action of a time-dependent vector field. We present corresponding simulation with the whirlpool perturbation. We also consider a new concept of real application in the navigational decision support systems.

Navigation Decision Supporting System (NAVDEC) — Testing In Real Condition

AbstractThe known navigational systems in use and methods of navigational decision support perform information functions and as such are helpful in the process of safe conduct of a vessel. However, none of these known systems provides a navigator with ready solutions of collision situations taking account of all the vessels in the proximity of own ship, where the Collision Regulations apply. This paper presents testing results of NAVDEC — new Navigational Decision Supporting System created by research team from Szczecin Maritime University both for ocean going ships and pleasure crafts Tests were carried out in real condition on board container vessel. Testing results were presented on example encounter situation between Hammonia Berolina (own ship) and FR8 Fortitude (target ship). Encounter parameters were compared with data received from Full mission simulator.