Search Results (46)

With the increasing demands of long-term overseas assignments, workers in isolated environments, such as maritime crews, often experience heightened psychological stress and a lack of accessible emotional support. This study investigates the effectiveness of online song intervention program based on contextual support model in reducing work-related distress and enhancing psychological resilience among the ship crews dispatched for an extensive period for work. Eighteen overseas workers participated in a four-week intervention that included both individual and group sessions, where they engaged with songs to cultivate personal and interpersonal resources. A deductive content analysis following the intervention revealed 3 main categories, 6 generic categories, and 14 subcategories. The three main categories identified were relationships, autonomy, and mood regulation. The relationships category encompassed support systems and bonding, focusing on empathy, consolation, positive perspective, vicarious empowerment, trust, and changes of perspective. Autonomy involved fostering a sense of control and fulfillment through determination, anticipation, motivation, and achievement. Mood regulation was divided into grounding and emotional resolution, which included containment, sedation, externalization, and ventilation. The findings highlight that song lyrics offer valuable insights for developing resources aimed at mood regulation, social support, and self-efficacy, helping to alleviate work-related stress during dispatch periods. Songs also foster a sense of control, competence, and relational connectedness, with mood regulation emerging as a key feature of their emotional impact. These results suggest that incorporating songs with lyrics focused on personal and interpersonal resources could be an effective strategy to support remotely dispatched workers. Furthermore, this approach appears to be a viable and scalable solution for online programs. Full article

The rise of the Internet of Things (IoT) has made it possible to explore different types of communication, such as underwater IoT (UIoT). This new paradigm allows the interconnection of ships, boats, coasts, objects in the sea, cameras, and animals that require constant monitoring. The use of sensors for environmental monitoring, tracking marine fauna and flora, and monitoring the health of aquifers requires the integration of heterogeneous technologies as well as wireless communication technologies. Aquatic mobile sensor nodes face various limitations, such as bandwidth, propagation distance, and data transmission delay issues. Owing to their versatility, wireless sensor networks support remote monitoring and surveillance. In this work, an architecture for a general packet radio service (GPRS) wireless sensor network is presented. The network is used to monitor the geographic position over the coastal area of the Gulf of Mexico. The proposed architecture integrates cellular technology and some ad hoc network configurations in a single device such that coverage is improved without significantly affecting the energy consumption, as shown in the results. The network coverage and energy consumption are evaluated by analyzing the attenuation in a proposed channel model and the autonomy of the electronic system, respectively. Full article

Driven by the commercialization of intelligent ships, the increasingly complex mixed maritime traffic environment presents significant challenges for collision avoidance between multiple ships due to cognitive and behavioral differences between intelligent and traditional ships. Therefore, it is essential to develop a human-like collision avoidance strategy that incorporates traditional navigational experience and handling practices, enhancing explainability and autonomy. By addressing the actual decision-making needs for predicting other ships’ intentions and considering potential risk impacts, a hierarchical strategy is designed that first seeks course direction adjustment and then determines the magnitude of adjustment. A direction adjustment intention estimation model is proposed, accounting for risk membership and COLREGS, to predict other ships’ collision avoidance intentions. Additionally, an intention influence model and a state influence model are introduced to design decision-making objectives, forming an optimization function based on angle range and maneuvering time constraints to determine the appropriate adjustment magnitude. The results demonstrate the strategy’s effectiveness across various scenarios. Specifically, the distance between ships increased by nearly 25% during the process, significantly enhancing safety. It is worth mentioning that the model has the potential to enhance intelligent ships’ capabilities in complex situational handling and intention understanding. Full article

The maritime industry is rapidly advancing toward the initial stages of the digitised era of shipping, characterised by considerable advances in maritime autonomous technology in recent times. This study examines the effectiveness of training packages and the impact of rank during the failure of a sophisticated autopilot control system. For this study, the fault recognition and diagnostic skills of 60 navigational seafarers conducting a navigational watch in a full mission bridge watchkeeping simulator were analysed. Participants had either significant experience as qualified navigational officers of the watch or were navigational officers of the watch cadets with 12 months’ watchkeeping experience. These groups were subdivided into those who were given a training package focused on behavioural aspects of managing automation, such as maintaining situational awareness, and those given a technical training package. The findings were analysed using an Event Tree Analysis method to assess the participants’ performance in diagnosing a navigation fault. Additionally, the fault recognition skills were assessed between groups of training and rank. The study found that participants who received the behavioural training were more successful in both recognising and diagnosing the fault during the exercise. Behavioural training groups outperformed technical training groups, even when technical training participants were experienced seafarers. This difference in performance occurred without any apparent differences in workload or secondary task performance. Understanding the data gathered from the study could lead to the development of future training regimes for navigational officers of the watch and help to optimise the evolution of the seafaring role. Full article

Maintenance of offshore wind farms requires the transportation of tools and spare parts in close coordination with the deployment of technicians and the cost-intensive shutdown of the wind turbines. In addition to ships and helicopters, drones are envisioned to support the offshore transportation system in the future. For cost-efficient and scalable offshore drone operations, autonomy is key to minimize the required infrastructure and personnel. In this work, we present a system architecture that integrates the key onboard capabilities for autonomous offshore drone operations: onboard mission and contingency management, en-route trajectory planning, robust flight control, safe landing, communication management, and runtime monitoring. We also present technical solutions for each of these capabilities and discuss their integration and interaction within the autonomy architecture. Furthermore, remaining challenges and the feasibility of autonomous drone operations for offshore wind farm cargo delivery are addressed, contributing to the realization of this vision in the near future. The work presented here summarizes the results of autonomous cargo drone operations within the UDW research project, a joint project between the German Aerospace Center (DLR) and the energy supplier EnBW. Full article

The autonomy of transport systems presents a transformative opportunity to enhance logistics efficiency, improve safety, and support decarbonization. In the maritime sector, the International Maritime Organization (IMO) has been working since 2016 to develop a mandatory regulatory framework for Maritime Autonomous Surface Ships (MASSs), aiming to finalize a comprehensive code. Simultaneously, pilot projects are underway in national waters under the oversight of national administrations. Naval applications of autonomous ships demonstrate their potential, as emerging doctrines highlight their strategic and operational advantages. Although the military sector is not governed at the international level, safely managing interactions between military and commercial MASSs is crucial for ensuring safe navigation. Classification societies play a vital role in achieving high safety standards and ensuring regulatory compliance. This study aims to propose a framework for certifying maritime autonomous vessels. Through a thorough analysis of the existing literature and by identifying gaps, this study outlines a structured pathway to facilitate the certification and operation of MASSs, addressing key technical, operational, and safety considerations. This research contributes to designing a risk-informed approach for the development of autonomous surface vehicles. Full article

In this study, a hybrid heading control framework for unmanned surface vehicles (USVs) is proposed, combining variable domain fuzzy Proportional–Integral–Derivative (VUF-PID) with an improved algorithmic Beetle Antennae Search–Particle Swarm Optimization–Simulated Annealing (BAS-PSO-SA) optimization to address the multi-objective control challenge. Key innovations include a self-tuning VUF mechanism that improves disturbance rejection by 42%, a weighted adaptive optimization strategy that reduces parameter tuning iterations by 37%, and an asymmetric learning factor that balances global exploration and local refinement. Benchmarks using Rastrigin, Griewank, and Sphere functions show superior convergence and 68% stability improvement. Ocean heading simulations of a 7.02 m unmanned surface vehicle (USV) using the Nomoto model show a 91.7% reduction in stabilization time, a 0.9% reduction in overshoot, and a 30% reduction in optimization iterations. The experimental validation under wind and wave disturbances shows that the heading deviation is less than 0.0392°, meeting the IMO MSC.1/Circ.1580 standard, and an 89.5% improvement in energy efficiency. Although the processing time is 12.7% longer compared to the GRO approach, this framework lays a solid foundation for ship autonomy systems, and future enhancements will focus on MPC-based time delay compensation and Field-Programmable Gate Array (FPGA) acceleration. Full article

Recent efforts on the decarbonization, autonomy, and safety of the maritime vehicles required comprehensive analyses and prediction of the behavior of the existing vessels and prospective adaptations. To predict the performance of vessels, a better understanding of ship hydrodynamics is necessary. However, it is necessary to conduct dozens of experiments or computational fluid dynamics simulations to characterize the hydrodynamic behavior of the vessels, which require significant amounts of cost and time. Thus, system identification studies to characterize the hydrodynamics of ships have gained attention. The present study proposes a hybrid methodology that combines the existing hydrodynamic databases, and a prediction model of ship hydrodynamics based on motion indexes obtained by turning and zigzag tests. Firstly, singular value decomposition was applied to extract the main hydrodynamic variations, and an artificial yet realistic hydrodynamic behavior generation systematics was developed. Then, turning and zigzag tests were simulated to train artificial neural network models which predict how hydrodynamic behavior varies based on the motion indexes. Finally, the proposed methodology was applied to two vessels to predict the hydrodynamic behaviors of the target ships based on given motion indexes. It was found that the motion obtained via the predicted hydrodynamics showed a high correlation with the given motion indexes. Full article

Autonomy is being increasingly used in domains like maritime, aviation, medical, and civil domains. Nevertheless, at the current autonomy level, human takeover in the human–autonomy interaction process (HAIP) is still critical for safety. Whether humans take over relies on situation awareness (SA) about the correctness of autonomy decisions, which is distorted by human anchoring and omission bias. Specifically, (i) anchoring bias (tendency to confirm prior opinion) causes the imperception of key information and miscomprehending correctness of autonomy decisions; (ii) omission bias (inaction tendency) causes the overestimation of predicted loss caused by takeover. This paper proposes a novel HAIP safety assessment method considering effects of the above biases. First, an SA-based takeover decision model (SAB-TDM) is proposed. In SAB-TDM, SA perception and comprehension affected by anchoring bias are quantified with the Adaptive Control of Thought-Rational (ACT-R) theory and Anchoring Adjustment Model (AAM); behavioral utility prediction affected by omission bias is quantified with Prospect Theory. Second, guided by SAB-TDM, a dynamic Bayesian network is used to assess HAIP safety. A case study on autonomous ship collision avoidance verifies effectiveness of the method. Results show that the above biases mutually contribute to seriously threaten HAIP safety. Full article

Achieving the required decarbonisation targets by the shipping industry requires a transition to technologies with zero or near-zero greenhouse gas (GHG) emissions. One promising shipping fuel with zero emission of exhaust gases (including CO₂) is green hydrogen. This type of fuel, recognised as a 100% clean solution, is being investigated for feasible use on a service offshore vessel (SOV) working for offshore wind farms. This study aims to examine whether hydrogen may be used on an SOV in terms of the technical and economic challenges associated with the design process and other factors. In the analyses, a reference has been made to the current International Maritime Organization (IMO) guidelines and regulations. In this study, it was assumed that hydrogen would be directly combusted in a reciprocating internal combustion engine. This engine type was reviewed. In further research, hydrogen fuel cell propulsion systems will also be considered. The hydrogen demand was calculated for the assumed data of the SOV, and then the volume and number of high-pressure tanks were estimated. The analyses revealed that the SOV cannot undertake 14-day missions using hydrogen fuel stored in cylinders on board. These cylinders occupy 66% of the ship’s current volume, and their weight, including the modular system, accounts for 62% of its deadweight. The costs are over 100% higher compared to MDO and LNG fuels and 30% higher than methanol. The actual autonomy of the SOV with hydrogen fuel is 3 days. Full article

Small Modular Reactors (SMRs) offer transformative potential for maritime propulsion by providing significant benefits such as reduced emissions, enhanced fuel efficiency, and greater operational autonomy. However, their integration into the maritime sector presents complex regulatory challenges due to the convergence of nuclear and maritime laws. A unified, harmonized regulatory framework is essential to ensure safety, radioactive waste management, and accident prevention. While initiatives led by the International Atomic Energy Agency (IAEA) and International Maritime Organization (IMO) are progressing, key gaps remain, particularly regarding maritime-specific risk assessments, emergency response protocols, and cross-border regulatory harmonization. Enhanced collaboration between regulatory bodies, pilot projects, and transparent engagement with stakeholders will be critical to refining safety protocols and accelerating regulatory alignment. Public acceptance remains a vital factor, requiring rigorous environmental impact assessments (EIAs) and transparent communication to build trust and align SMR-powered vessels with global sustainability objectives. While challenges persist, they also present opportunities for innovation and international cooperation. By addressing these regulatory and public acceptance challenges through coordinated efforts and policies, SMR propulsion can become a cornerstone of a more sustainable, efficient, and technologically advanced maritime sector. Successful deployment will position SMRs as a key component of the global energy transition, driving progress toward low-carbon shipping and a greener maritime industry. Full article

A novel Boundary Element Method (BEM) is presented for predicting the hydrodynamic behavior of twin-hull vessels, traveling at low speeds, aiming to quantify the benefits of integrating solar technology onboard. In particular, the power requirements of an electric 33 m long twin-hull ship are examined. The study discusses the placement of solar panels on deck and assesses their utilization in terms of real-time energy generation, aiming to extend the autonomy range while also reducing carbon emissions. The discussed methodology predicts the power needs by considering various operational variables, design specifications and hydrodynamic principles. In addition, it addresses the viability and possible advantages of integrating solar technology onboard and provides preliminary estimates regarding the extent to which solar energy may compensate for power needs, based on several factors, including the velocity, the prevailing sea state and the incident solar irradiance. The results provide useful information regarding the utilization of solar energy in the shipping sector, in addition to advancing sustainable maritime propulsion. Full article

Phased injection of natural gas into internal combustion marine engines is a promising solution for optimizing performance and reducing harmful emissions, particularly unburned methane, a potent greenhouse gas. This innovative practice distinguishes itself from continuous injection because it allows for more precise control of the combustion process with only a slight increase in system complexity. By synchronizing the injection of natural gas with the intake and exhaust valve opening and closing times while also considering the gas path in the manifolds, methane release into the atmosphere is significantly reduced, making a substantial contribution to efforts to address climate change. Moreover, phased injection improves the efficiency of marine engines, resulting in reduced overall fuel consumption, lower fuel costs, and increased ship autonomy. This technology was tested on a single-cylinder, large-bore, four-stroke research engine designed for marine applications, operating in dual-fuel mode with diesel and natural gas. Performance was compared with that of the conventional continuous feeding method. Evaluation of the effect on equivalent CO₂ emissions indicates a potential reduction of up to approximately 20%. This reduction effectively brings greenhouse gas emissions below those of the diesel baseline case, especially when injection control is combined with supercharging control to optimize the air–fuel ratio. In this context, the boost pressure in DF was reduced from 3 to 1.5 bar compared with the FD case. Full article

Remotely operated vehicles (ROVs) provide practical solutions for a wide range of activities in a particularly challenging domain, despite their dependence on support ships and operators. Recent advancements in AI, machine learning, predictive analytics, control theories, and sensor technologies offer opportunities to make ROVs (semi) autonomous in their operations and to remotely test and monitor their dynamics. This study moves towards that goal by formulating a complete navigation, guidance, and control (NGC) system for a six DoF BlueROV2, offering a solution to the current challenges in the field of marine robotics, particularly in the areas of power supply, communication, stability, operational autonomy, localization, and trajectory planning. The vehicle can operate (semi) autonomously, relying on a sensor acoustic USBL localization system, tethered communication with the surface vessel for power, and a line of sight (LOS) guidance system. This strategy transforms the path control problem into a heading control problem, aligning the vehicle’s movement with a dynamically calculated reference point along the desired path. The control system uses PID controllers implemented in the navigator flight controller board. Additionally, an infrastructure has been developed that synchronizes and communicates between the real ROV and its digital twin within the Unity environment. The digital twin acts as a visual representation of the ROV’s movements and considers hydrodynamic behaviors. This approach combines the physical properties of the ROV with the advanced simulation and analysis capabilities of its digital counterpart. All findings were validated at the Point Rouge port located in Marseille and at the port of Ancona. The NGC implemented has proven positive vehicle stability and trajectory tracking in time despite external interferences. Additionally, the digital part has proven to be a reliable infrastructure for a future bidirectional communication system. Full article

As seafarers are involved in Maritime Autonomous Surface Ships (MASS), except for those in the fourth level of autonomy, the decision making of autonomous berthing should be carried out and be understood by human beings. This paper proposes a fuzzy logic-based human-like decision-making method for ultra-large ship berthing, which considers locations, ship particulars and the natural environment, and these factors are treated as the input variables. The IF–THEN rules are then established after the fuzzification of the input variables and are used for fuzzy inference to derive the decision of ship handling. It can be implemented in the decision-making system for safe navigation or be included in the process of autonomous berthing. The pilotage data are collected with nautical instruments and a distance measurement system during the berthing process, which are used to validate the proposed model and calculate the speed and turn errors. The overall and individual error of the decision-making model is in a reasonable and small range, which indicates that the model has good accuracy. The results of this research offer theoretical and practical insights into the development of a human-like decision-making method for autonomous navigation in port waters and maritime safety management in the shipping industry. The model can be further applied to develop a more widely applicable decision-making system for autonomous navigation in confined waters. Full article