GreenHopper is the first Danish zero-emission ferry developed as a test platform for autonomous waterborne navigation technologies. The paper presents technology development within the innovation project ShippingLab Autonomy, which led to the commissioning of GreenHopper at Limfjorden (DK) in December 2022. The technology research resulted in a holistic system architecture for surface vessel autonomy, based on distribution of functionality and responsibility on software modules, similar to the structure observed in the International Maritime Organization (IMO) Seafarers Training Certification and Watch-keeping (STCW) regulatory framework. The paper shows how this approach results in an architecture that supports safe behaviours of individual modules and of autonomous navigation at a system level. The paper presents the individual modules, specific features and benefits. Elements of the regulatory framework are highlighted to poise technology approval by maritime authorities. The paper reflects on lessons learned, discusses continued technology validation in dedicated operational scenarios.
Background: Autonomous ships have the potential to increase operational efficiency and reduce carbon footprints through technology and innovation. However, there is no comprehensive literature review of all the different types of papers related to autonomous ships, especially with regard to their integration with ports. This paper takes a systematic review approach to extract and summarize the main topics related to autonomous ships in the fields of container shipping and port management. Methods: A machine learning method is used to extract the main topics from more than 2000 journal publications indexed in WoS and Scopus. Results: The research findings highlight key issues related to technology, cybersecurity, data governance, regulations, and legal frameworks, providing a different perspective compared to human manual reviews of papers. Conclusions: Our search results confirm several recommendations. First, from a technological perspective, it is advised to increase support for the research and development of autonomous underwater vehicles and unmanned aerial vehicles, establish safety standards, mandate testing of wave model evaluation systems, and promote international standardization. Second, from a cyber–physical systems perspective, efforts should be made to strengthen logistics and supply chains for autonomous ships, establish data governance protocols, enforce strict control over IoT device data, and strengthen cybersecurity measures. Third, from an environmental perspective, measures should be implemented to address the environmental impact of autonomous ships. This can be achieved by promoting international agreements from a global societal standpoint and clarifying the legal framework regarding liability in the event of accidents.
This paper introduces a resilience assessment methodology for sustainable autonomous maritime transport networks developed by the European project entitled “Advanced, Efficient, and Green Intermodal Systems” (AEGIS). This problem being addressed in this paper concerns the investigation of threats, incidents, and risks in an autonomous- and sustainable shipping context, and the research question is the development of both preventive measures and reactive actions to maintain an acceptable level of operational constraints. The paper's methodology aids in designing sustainable logistics systems for highly automated waterborne transport, identifying threats and barriers to mitigate event consequences, thereby facilitating a seamless green transition. To examine the usability, this methodology is applied in a case study for cargo transportation, where we in this paper consider the maritime corridor between Trondheim and Rotterdam. The findings encompass the spectrum of possible actions to prevent and mitigate unwanted events and enhance resilience and flexibility. This can be used as a tool to respond to unwanted threats, enhance safety, and introduce new strategies. These results are deemed important as resilience is one of the prerequisites for the development of a sustainable transport system. This is true both for the companies that are engaged in the operation of such systems and for policymakers.
The implementation of unmanned vessels will evidently come with its own legal challenges. One of the most crucial of these is the identification of the role and status of the shore-based controller (SBC) for the purposes of determining liability. Different liability regimes apply different legal principles in this regard. This article will explore these issues from the perspective of English law and Scandinavian law.
Abstract: In recent years, the development of ground robots with human-like perception capabilities has led to the use of multiple sensors, including cameras, lidars, and radars, along with deep learning techniques for detecting and recognizing objects and estimating distances. This paper proposes a computer vision-based navigation system that integrates object detection, segmentation, and monocular depth estimation using deep neural networks to identify predefined target objects and navigate towards them with a single monocular camera as a sensor. Our experiments include different sensitivity analyses to evaluate the impact of monocular cues on distance estimation. We show that this system can provide a ground robot with the perception capabilities needed for autonomous navigation in unknown indoor environments without the need for prior mapping or external positioning systems. This technique provides an efficient and cost-effective means of navigation, overcoming the limitations of other navigation techniques such as GPS-based and SLAM-based navigation. Graphical Abstract: [Figure not available: see fulltext.]
The European Union (EU) transport policy recognizes the importance of the waterborne transport systems as key elements for sustainable growth in Europe. By 2030, 30% of total road freight over 300 km should shift to rail or waterborne transport, and more than 50% by 2050. Thus far, this ambition has failed but there have been several project initiatives within the EU to address these issues. In one of these projects, we consider a new waterborne transport system for Europe that is green, robust, flexible, more automated and autonomous, and able to connect both rural and urban terminals. The purpose of this paper is to describe work and preliminary results from this project. To that effect, and in order to assess any solutions contemplated, a comprehensive set of Key Performance Indicators (KPIs) has been defined, and three specific use cases within Europe are examined and evaluated according to these KPIs. KPIs represent the criteria under which the set of solutions developed are evaluated, and also compared to non-autonomous solutions. They are grouped under economic, environmental and social KPIs. KPIs have been selected after a consultation process involving project partners and external Advisory Group members. Links to EU transport and other regulatory action are also discussed.
The European Union (EU) transport policy recognizes the importance of the waterborne transport systems as key elements for sustainable growth in Europe. By 2030, 30% of total road freight over 300 km should shift to rail or waterborne transport, and more than 50% by 2050. Thus far, this ambition has failed but there have been several project initiatives within the EU to address these issues. In one of these projects, we consider a new waterborne transport system for Europe that is green, robust, flexible, more automated and autonomous, and able to connect both rural and urban terminals. The purpose of this paper is to describe work and preliminary results from this project. To that effect, and in order to assess any solutions contemplated, a comprehensive set of Key Performance Indicators (KPIs) has been defined, and three specific use cases within Europe are examined and evaluated according to these KPIs. KPIs represent the criteria under which the set of solutions developed are evaluated, and also compared to non-autonomous solutions. They are grouped under economic, environmental and social KPIs. KPIs have been selected after a consultation process involving project partners and external Advisory Group members. Links to EU transport and other regulatory action are also discussed.
Marine autonomy research has focused on algorithmic and technical developments, targeting autonomous craft in restricted areas where international rules and regulations are not prioritised. This paper addresses the system engineering aspect of a highly complex system in which the seamless, predictable, and secure interoperability of vendorspecific hardware and software subsystems is a fundamental requirement for designing and implementing cyber-physical systems with artificial intelligence to assist or replace the navigating officer, such as autonomous marine surface vehicles. It addresses international rules in the sector and exhibits a system architecture that can fulfil the criteria for safe behaviour in foreseen occurrences and the capacity to request human aid if the autonomous system cannot manage a problem. The system thinking and engineering provided in this article have been applied to The GreenHopper, a harbour bus currently under construction and intended to undergo certification and enter commercial service.
Highly reliable situation awareness is a main driver to enhance safety via autonomous technology in the marine industry. Groundings, ship collisions and collisions with bridges illustrate the need for enhanced safety. Authority for a computer to suggest actions or to take command, would be able to avoid some accidents where human misjudgement was a core reason. Autonomous situation awareness need be conducted with extreme confidence to let a computer algorithm take command. The anticipation of how a situation can develop is by far the most difficult step in situation awareness, and anticipation is the subject of this article. The IMO International Regulations for Preventing Collisions
at Sea (COLREGS), describe the regulatory behaviours of marine vessels relative to each other, and correct interpretation of situations is instrumental to safe navigation. Based on a breakdown of COLREGS rules, this article presents a framework to represent manoeuvring behaviours that are expected when all vessels obey the rules. The article shows how nested finite automata can segregate situation assessment from decision making and provide a testable and repeatable algorithm. The suggested method makes it possible to anticipate own ship and other vessels’ manoeuvring in a multi-vessel scenario. The framework is validated using scenarios from a full-mission simulator.
Offshore pipelines and structures require regular marine growth removal and inspection to ensure structural integrity. These operations are typically carried out by Remotely Operated Vehicles (ROVs) and demand reliable and accurate feedback signals for operating the ROVs efficiently under harsh offshore conditions. This study investigates and quantifies how sensor delays impact the expected control performance without the need for defining the control parameters. Input-output (IO) controllability analysis of the open-loop system is applied to find the lower bound of the H-infinity peaks of the unspecified optimal closed-loop systems. The performance analyses have shown that near-structure operations, such as pipeline inspection or cleaning, in which small error tolerances are required, have a small threshold for the time delays. The IO controllability analysis indicates that off-structure navigation allow substantial larger time delays. Especially heading is vulnerable to time delay; however, fast-responding sensors usually measure this motion. Lastly, a sensor comparison is presented where available sensors are evaluated for each ROV motion’s respective sensor-induced time delays. It is concluded that even though off-structure navigation have larger time delay tolerance the corresponding sensors also introduce substantially larger time delays.