Surface Ship Research Articles

The development of algorithms for safe control of an autonomous ship

The paper presents the results of a research on the development of algorithms for ship’s safe ship trajectory calculation and automatic control of the ship along the determined trajectory. These methods are intended for use in the autonomous navigation system of an Unmanned Surface Vehicle (USV) or a Maritime Autonomous Surface Ship (MASS). The work presents the consecutive stages of a research that must be carried out in order to develop a system that will perform the task of multidimensional ship control in a port. The safe trajectory is calculated with the use of the Ant Colony Optimization (ACO) method. The ship motion control is based on the Linear Matrix Inequalities (LMI) method, implemented using the Mathworks and Yalmip libraries. The results of controlling the ship’s motion in accordance with the calculated trajectory are presented in the paper. With the use of the developed system, the ship can move autonomously based on the information from the DGPS system and a gyrocompass. The presented results concerned a computer simulation of maneuvers in the port of the Blue Lady ship from the Foundation for Shipping Safety and Environmental Protection.

Path planning for submersible surface ships in a three-dimensional environment considering safety distance

Currently, path planning for an unmanned ship is usually performed in a single domain on the water surface or underwater, and little research exists on path planning for a three-dimensional (3D) environment where the ship crosses the water’s surface and underwater. The existing 3D path planning research still has improvement possibilities in reserving a safe distance between the ship and the obstacles. In this paper, path planning for a submersible surface ship (SSS) in a 3D environment is carried out based on an ant colony algorithm. Path safety is enhanced by introducing constraints related to boat width to keep the path at a safe distance from obstacles. By extracting key points, the length of the path is further reduced. The algorithmic procedure with the objective of the shortest time was obtained by assigning different speeds to the SSS sailing at the same depth and across different depths. The rationality and superiority of the method given in this paper are verified in several sets of simulations and comparative experiments. The paper concludes that path selection is more inclined to choose the water surface as the depth of the obstacles increases and the density of the obstacles decreases.

Trajectory tracking for autonomous surface ships using Gaussian process regression and model predictive control with BVS strategy

Autonomous navigation is critical to the development of next-generation shipping systems. The proposal of intelligent ships enables innovation in the shipping and shipbuilding industry and increases the safety and efficiency of ship operations. Autonomous control of surface ships to follow a prescribed trajectory is critical in a variety of maritime applications. This paper proposes a trajectory tracking control strategy for autonomous surface ships that combines nonparametric modelling using Gaussian Process Regression (GPR) with the Model Predictive Control (MPC) framework. A Bézier curve-based Virtual Ship(BVS) guidance strategy is proposed to convert dynamic trajectory points into reference heading angles and speeds, such that the trajectory tracking problem can be decomposed into heading control and speed control problems. Gaussian process regression is utilised to identify the correlation between propeller revolution speed and ship speed, as well as the correlation between rudder angle and heading angle based on experimental data. Two GPR models are therefore constructed as the prediction models for designing MPC controllers for heading control and speed control, respectively. Nonlinear optimisation algorithms are utilised to search for optimal control commands in each sampling interval to solve the optimisation problem in MPC with GPR models and input constraints. Simulations are carried out to evaluate the effectiveness of the proposed method.

Quantitative assessment of the effectiveness of adaptive spatial processing algorithms in searching for low-noise underwater vehicles in surface shipping conditions of different density

The article describes the methodology and provides the results of a model quantitative assessment of the effectiveness of solving the problem of detecting and tracking a low-noise underwater object using three algorithms for spatial signal processing at the output of a multi-element antenna — the non-adaptive Bartlett algorithm, the Capon algorithm, and the Capon algorithm combined with a projection procedure limiting the signal power of strong local sources.

Numerical investigation of turbulent wake thermal effects on surface ships

To investigate the evolutionary mechanism of the thermal wake of surface ships, this study has proposed a numerical method for the thermal effects of turbulent wake and computed the near-wake fields for three ship schemes. The study indicates that the thermal wake, formed by vortices produced by the ship's movement and the propeller's rotation, propagates in a fine, thread-like pattern, setting it apart from the characteristic V-shaped diffusion of the Kelvin wake. The diffusion of thermal wake is divided into three distinct stages: formation, growth, and maturity. The thermal wakes generated by ships with shaftless rim-driven systems exhibit significantly lower diffusion rates, extents, and intensities compared to those created by ships with propeller propulsion systems. In summer, the center of the thermal wake exhibits a cold peak that is significantly lower than the ambient temperature. A reduction in temperature of greater than 0.05 K was observed for the three design schemes. In contrast, a warm peak that is above the environmental temperature is present at the edge of the wake. As the speed of the ship increases, the duration of each stage of the thermal wake lengthens and the diffusion range expands. When the temperature gradient is larger, the thermal wake becomes more intense. The findings of this study have revealed the evolution mechanisms of thermal effects in the wake of surface ships, thereby contributing to the advancement of knowledge in the fields of hydrodynamics and thermodynamics.

A human factor analysis of remote-control failure for maritime autonomous surface ships

Human factor management is crucial to the safety of maritime shipping. Whilst there has been extensive research on human factors in conventional shipping, the development of autonomous shipping necessitates the investigation of emerging human factors under the evolving landscape. Given that the research on human factor analysis for remote operation failure is limited, this study aims to enrich the literature by establishing a comprehensive human factor framework and empirically assessing the factors. Based on the literature review and expert interview, a total of ten categories and thirty-one human factors are organized under the human factor analysis and classification system. Adopting the purposive sampling, questionnaire surveys are then distributed to experts specializing in ship operations and automation to collect their degree of belief on potential human factors. A hybrid method composed of evidential reasoning and the rule-based Bayesian network is applied to analyze the data. The empirical results indicate that adverse mental states and adverse cognitive states are perceived to be the most threatening risk categories in remote operations. This study expands the academic research on human factor analysis and highlights the significance of managing psychological and cognitive factors. The findings provide managerial implications for the future safety management of autonomous ships.

The Impact of a Non-Uniform and Transient Magnetic Field on Natural Convective Jeffrey Fluid Flowing over a Heated Porous Plate: A Comparitive Study

Examining the effects of varying transient magnetic fields and their orientations on boundary layers aids in understanding the flow in complex surface geometries, turbulence control, drag reduction, aircraft and ship design, groundwater management, and the study of construction and coastal engineering. The study introduces a novel dynamics of the boundary layer of a natural convective Jeffrey fluid flowing over an erect porous moving plate under the influence a non-uniform and transient magnetic field M ˜ that grows exponentially over time with α as an accelerating parameter. The governing partial differential equations (PDEs) were non-dimensionalized using similarity variables and then solved analytically using the perturbation technique. The impact of various thermosphysical properties including chemical reactions, thermal source, Jeffrey fluid parameter and plate permeability on the fluid flow were presented graphically utilizing finite difference approximation(FDA) technique in MATLAB ODE15s solver. The study highlighted a notable decrease in shear stress (skin friction) by introducing M ˜ to the vertical plate results in the reduction of momentum boundary layer, accompanied by an increment in thermal boundary layer. Also, the results shows that increasing the magnitude of α leads to decrease the velocity and increase the temperature distribution curve. Additionally, the concentration profile was also found to decrease with stronger chemical reactions. Furthermore, key parameters like heat and mass flux were estimated and discussed through comparison tables. Understanding the effects of unsteady and externally applied increasing magnetic field M ˜ on viscous fluid flow have potential applications in biomedical engineering, such as the design of magnetic drug delivery systems and the analysis of blood flow in human body.

A multi-phase mission success evaluation approach for maritime autonomous surface ships considering equipment performance degradation and system composition changes

With the development of Maritime Autonomous Surface Ships (MASSs), the mission success assessment problem cannot be ignored because of potential security issues of MASSs. This paper addresses the issue of performance degradation at different stages, the problem of state dependence in multi-stage missions of MASSs, and the correlation problem between missions of stages. Based on the coupling of the reliability model of each single-stage mission system, a multi-stage mission success evaluation method for MASSs is proposed. By leveraging the ability of the conditional probability tables in Bayesian networks to express the complex relationships between the nodes, the dynamic Bayesian network model of stages is constructed based on the fault tree. Based on the Markov process, the problem of state dependence on shared equipment between stages is solved. Considering the complex relationship between multi-stage missions, the virtual node is introduced, and the multi-state Bayesian network is combined to realize the coupling of the reliability evaluation results of each single-stage mission. It is applied to the multi-stage mission success evaluation of the MASS to obtain the success probability of MASSs and the key equipment of each stage. The results show that evaluation results are more suitable for engineering practice.

Mechanisms for Securing Autonomous Shipping Services and Machine Learning Algorithms for Misbehaviour Detection

Technological developments within the maritime sector are resulting in rapid progress that will see the commercial use of autonomous vessels, known as Maritime Autonomous Surface Ships (MASSs). Such ships are equipped with a range of advanced technologies, such as IoT devices, artificial intelligence (AI) systems, machine learning (ML)-based algorithms, and augmented reality (AR) tools. Through such technologies, the autonomous vessels can be remotely controlled from Shore Control Centres (SCCs) by using real-time data to optimise their operations, enhance safety, and reduce the possibility of human error. Apart from the regulatory aspects, which are under definition by the International Maritime Organisation (IMO), cybersecurity vulnerabilities must be considered and properly addressed to prevent such complex systems from being tampered with. This paper proposes an approach that operates on two different levels to address cybersecurity. On one side, our solution is intended to secure communication channels between the SCCs and the vessels using Secure Exchange and COMmunication (SECOM) standard; on the other side, it aims to secure the underlying digital infrastructure in charge of data collection, storage and processing by relying on a set of machine learning (ML) algorithms for anomaly and intrusion detection. The proposed approach is validated against a real implementation of the SCC deployed in the Livorno seaport premises. Finally, the experimental results and the performance evaluation are provided to assess its effectiveness accordingly.

Data/Knowledge-Driven Behaviour Analysis for Maritime Autonomous Surface Ships—2nd Edition

This Special Issue, entitled “Data/Knowledge-Driven Behaviour Analysis for Maritime Autonomous Surface Ships—2nd Edition”, is the sequel to “Data/Knowledge-Driven Behaviour Analysis for Maritime Autonomous Surface Ships”, including five contributions [...]

A Risk Identification Method for Ensuring AI-Integrated System Safety for Remotely Controlled Ships with Onboard Seafarers

The maritime sector is increasingly integrating Information and Communication Technology (ICT) and Artificial Intelligence (AI) technologies to enhance safety, environmental protection, and operational efficiency. With the introduction of the MASS Code by the International Maritime Organization (IMO), which regulates Maritime Autonomous Surface Ships (MASS), ensuring the safety of AI-integrated systems on these vessels has become critical. To achieve safe navigation, it is essential to identify potential risks during the system planning stage and design systems that can effectively address these risks. This paper proposes RA4MAIS (Risk Assessment for Maritime Artificial Intelligence Safety), a risk identification method specifically useful for developing AI-integrated maritime systems. RA4MAIS employs a systematic approach to uncover potential risks by considering internal system failures, human interactions, environmental conditions, AI-specific characteristics, and data quality issues. The method provides structured guidance to identify unknown risk situations and supports the development of safety requirements that guide system design and implementation. A case study on an Electronic Chart Display and Information System (ECDIS) with an AI-integrated collision avoidance function demonstrates the applicability of RA4MAIS, highlighting its effectiveness in identifying specific risks related to AI performance and reliability. The proposed method offers a foundational step towards enhancing the safety of software systems, contributing to the safe operation of autonomous ships.

Letting losses be lessons: Human-machine cooperation in maritime transport

Navigation safety has been a critical guarantee of global shipping, and it becomes more challenging given the increasing employment of advanced technologies and novel ship design in the era of Maritime Autonomous Surface Ships (MASS). The human-centred risk analysis of human-machine cooperation is scarce in general and emerging in maritime transport in specific. This paper aims to develop a new approach enabling the analysis of significant risk influencing factors (RIFs) in human-machine cooperation through an in-depth investigation of the occurred mistakes and violations in the cooperative operations of seafarers and machines in maritime transport. Its novelties consist of (1) a novel approach to analysing and quantifying the connectivity between humans and machines in safety-critical operations, (2) new integration of the frequency and impact of RIFs in the human-machine cooperation model, and (3) ultilisation of graph theory to generate a network to analyse critical human-machine RIFs and their interactions with the system. The connectivity analysis of RIFs is conducted through a weighted undirected network, showing the features of RIF connectivity accommodating the closed-loop system. The proposed novel approach, which combines the frequency and impact features to identify critical RIFs and analyses graphical features, will aid to realise the human-centred risk analysis for MASS. The findings make contributions for ship designers to rationalise the clustering design of function-based automation and training organisations to improve seafarer skills by rationally considering the identified risk-based human-machine cooperation features, and providing new competence schemes that can fit the demands of MASS in future.

Design of Underwater Cables Applicable to Submarine(KSS-III Batch-II) Navigation Radar

Since the creation of the first submarine telegraph cable connecting England and France in 1850, today, due to the rapid development of the Internet and Communications fields, the demand for submarine communication cables has increased and continues to develop. Submarine cables are designed and manufactured to be suitable for the maritime environment, and many parts are imported from overseas, and several domestic cable manufacturers are producing them for commercial purposes. Field-proven and reliable commercial submarine communication cable technology is also being applied to the military field, and is especially actively utilized in naval surface ships and submarines. This paper is about the design of an underwater cable applicable to submarine(KSS-III Bach-II) navigation radar and also is to secure the performance of an underwater cable with bending durability in extreme marine environments, emergency diving, and repeated mast raising and lowering. Finally, we hop that the domestic development of underwater cables will help improve the performance of navigation radars for submarines.

A Probabilistic Approach to Correct for Oblique Biases in Sea Ice Parametrization from Shipborne Cameras

Abstract This work investigates the perception bias caused by ice floes occluding open water regions behind them when analyzing sea ice from shipborne cameras. We propose a method to model this effect by predicting an occlusion probability for a given surface region based on a stochastic representation of the sea ice fields. We further show how the proposed framework can be used to design an unbiased estimator for image-based sea ice concentration by correcting for these occlusions. The occlusion model and proposed sea ice concentration estimator have been verified through simulated experiments. Results from the experiments showed that predictions from the occlusion model align with the simulated observations and that the proposed estimator remains unbiased for all environments tested. The contributions of this study can be used in algorithms for automated identification and characterization of ice environments from surface ships and are thus an essential step towards improved autonomy in Arctic navigation.

Steering towards sustainability: the impact of autonomous shipping on achieving sustainable development goals

Abstract This study examines the sustainability potential of Maritime Åutonomous Surface Ships (MÅSS) in achieving the United Nations’ Sustainable Development Goals. By engaging various stakeholders through a poll and interviews, the research explores both the anticipated benefits and possible negative impacts of MÅSS, as well as the potential for failed promises of autonomous shipping. The findings highlight the need for incorporating sustainability considerations in further development of autonomous shipping to ensure it positively contributes to sustainable development.

Gap analysis and harmonization of International Standards for Maritime Autonomous Surface Ships

Abstract This paper addresses the challenges and solutions associated with the implementation of autonomous ships, focusing on the Maritime Autonomous Surface Ships (MASS) Code developed by the International Maritime Organization (IMO). With the goal of adopting a mandatory goal-based MASS Code by 2030, this study examines the interoperability and standardization requirements necessary for the effective global operation of autonomous ships. The paper analyses the MASS Code in relation to existing international standards, identifies gaps, and proposes standards works to accommodate the emerging technologies. Additionally, it investigate on the application of Autonomous Navigation Systems (ANS) and introduces the concepts of Shore ANS and Shore Bridge to enhance remote control capabilities. The analysis emphasizes the need for comprehensive standardization to ensure the safe and efficient operation of autonomous ships in diverse maritime environments.

MASS and COLREGS–Adaptability, Challenges and Coping Strategies

Discussions surrounding Maritime Autonomous Surface Ships (MASS) are occurring in academia, industry, and the International Maritime Organization (IMO). Automatic collision avoidance, as one of the key technologies of MASS, is the core of the autonomous navigation function of MASS, and its role is to solve the autonomous collision avoidance problem during MASS navigation. Convention on the International Regulations for Preventing Collisions at Sea (COLREGS) is a fundamental basis for automatic collision avoidance, and the navigation of MASS should adhere to it. However, the applicability of MASS to COLREGS has not yet been resolved. Responding to these issues, the paper proceeds to analyze the principal challenges of MASS to COLREGS in terms of the application of MASS to good seamanship, the neglect provision, the lookout provision, the insight of one another provision, and the problems of the deviation provision. Furthermore, suggestions are put forth for the revision of COLREGS, including the mode of revision, the reconstruction of MASS collision liability, the long-term coexistence of MASS and traditional ships, and the risk control of COLREGS revision in the context of artificial intelligence. These suggestions aim to establish a foundation for a more effective adaptation to the advent of the MASS era.

Safety Assurance of Maritime Autonomous Surface Ships

Abstract Safety of Maritime Autonomous Surface Ships (MASS) is inherently complex owing to the dynamic and unpredictable nature of the maritime environment. This is exacerbated by the pace of change in enabling technologies and their disruptive impact. Integral to the safety assurance of MASS is assessment and mitigation of risk. The International Maritime Organisation (IMO) defines Risk as “the combination of frequency and severity of the consequence”. The advent of software-controlled systems has introduced difficulties in quantifying frequencies; an issue which is more prevalent in the context of autonomy due to the complex interaction between control algorithms and the variabilities of the environment in which they are deployed. Within complex autonomous systems, therefore it is challenging to perform quantitative risk assessments using failure rates, which gives rise to a need for different techniques to assess risk. Novel risk assessment methodologies such as those presented in the European Maritime Safety Agency (EMSA) Risk Based Assessment Tool (RBAT) combined with conventional risk assessment techniques can offer a solution to this challenge. Compliance with legislation and standards is another cornerstone of safety assurance, which is also inherently difficult for MASS vessels owing to their having been developed for conventional vessels. A goal-based approach to legislation compliance could present an interim solution until the IMO goal-based Maritime Autonomous Systems (MAS) provides harmonisation across the industry. Whilst MASS Safety assurance is non-trivial, there are solutions to many of the challenges faced; this paper examines the predominant challenges and presents potential solutions.

A study on improving the international regulations for preventing collisions at sea (COLREG) for the introduction of maritime autonomous surface ships (MASS)

ABSTRACT Maritime Autonomous Surface Ships (MASS) have emerged with the advancements in information and communication technology (ICT), artificial intelligence (AI), and automation technology. MASS offers several advantages, such as reducing maritime accidents, increasing operational efficiency, lowering labour costs, and minimizing human errors. However, there are numerous challenges to address for the practical operation of MASS. In particular, the International Regulations for Preventing Collisions at Sea (COLREG), which governs the navigation rules for vessels, is a crucial international convention for the safety of navigation of MASS at sea. Therefore, this study examines the amendments to COLREG considering the characteristics of MASS. The International Maritime Organization (IMO) has defined various degrees of autonomy for MASS, ranging from full autonomy to remote control, and through the Regulatory Scoping Exercise (RSE), it has identified the need to amend certain provisions of COLREG to ensure the safe operation of MASS. Accordingly, this paper analyzes the results of the RSE conducted by IMO and proposes measures for improving COLREG to ensure the safe navigation of MASS.

Scenarios of Multiple Vessels Encounter for Safety Evaluation for Automatic Collision Avoidance Algorithm using AIS Data

Abstract Interest in Maritime Autonomous Surface Ships (MASS) is growing, and efforts are underway in Japan to realize them. One of the key issues in realizing autonomous operation is automatic collision avoidance. Simulation is effective in developing and evaluating such algorithms. This paper describes the generation of a set of simulation scenarios that consider the actual sea traffic using AIS data, which is traffic flow data in real seas. We assumed that the comprehensiveness of the scenarios could be ensured by generating scenarios by combining typical encounter patterns and collecting difficult situations that are encountered in real situations. First, the characteristics of the target sea area were identified from the AIS data, then difficult traffic situations were extracted from the data, and then a set of scenarios were generated based on them. Considering the presence of manned ships in the test area, we conducted some tests of the generated scenarios not only using fast-time simulations but also using a ship-handling simulator and conducted visual checks from own ship and the target ship.