Collision prevention is critical for navigation safety at sea. At early ages, researchers aimed at developing navigational assistance systems for enhancing situational awareness of human operators as human is at the core of collision avoidance. Recently, autonomous vehicles have gained a remarkable amount of attention with a focus on solving collision problems by machines. This results in two groups of studies, both working on preventing collisions but with different focuses: one aims at conflict detection, and the other focuses on conflict resolution. This paper offers a comprehensive overview of collision prevention techniques based on the three basic processes of determining evasive solutions, namely, motion prediction, conflict detection, and conflict resolution. The strengths and weaknesses of different methods for these three fundamental processes are discussed. Limitations and new challenges are highlighted. Moreover, this review points out the differences between the research for manned and unmanned ships and how the research in the two domains can learn from each other. A potential roadmap for the transition from existing manned ships to fully unmanned ships is provided in the end.@en

Autonomous Surface Vessels (ASVs) have been involved in numerous projects since the 1990s. Many ASV projects have been successfully realized, and as many are still under development. Together with the development of those new autonomous vessels, the research on classification about ASVs has become important. The classifications provide clarity to researchers, designers, shipbuilders, equipment manufacturers, ship owners and operators, enabling accurate specification of the desired level of autonomy in design and operations. Moreover, the involved research paves the way to a clearer understanding of the opportunity and challenges of research on autonomous vehicles. In this paper, we introduce the emerging concept of autonomous vessels. A multi-layer multi-agent control architecture of cooperative transport systems from the perspective of ASVs is proposed. Moreover, we provide an overview of existing research on the classification of autonomy. Based on the analysis, a detailed definition and categorization of autonomy levels for ASVs is proposed starting from the characteristics of ASVs and existing classification of autonomy. The proposed autonomy levels categorization assesses the overall autonomy level of a vessel by analyzing the automated sub-systems: Decision, Actions, Exceptions, and Cooperation. This categorization can be used to analyze existing ASV prototypes to gain insight into the status and trend of ASV research.@en

Autonomous Surface Vessels (ASVs) have been involved in numerous projects since the 1990s. Many ASV projects have been successfully realized, and as many are still under development. Together with the development of those new autonomous vessels, the research on classification about ASVs has become important. The classifications provide clarity to researchers, designers, shipbuilders, equipment manufacturers, ship owners and operators, enabling accurate specification of the desired level of autonomy in design and operations. Moreover, the involved research paves the way to a clearer understanding of the opportunity and challenges of research on autonomous vehicles. In this paper, we introduce the emerging concept of autonomous vessels. A multi-layer multi-agent control architecture of cooperative transport systems from the perspective of ASVs is proposed. Moreover, we provide an overview of existing research on the classification of autonomy. Based on the analysis, a detailed definition and categorization of autonomy levels for ASVs is proposed starting from the characteristics of ASVs and existing classification of autonomy. The proposed autonomy levels categorization assesses the overall autonomy level of a vessel by analyzing the automated sub-systems: Decision, Actions, Exceptions, and Cooperation. This categorization can be used to analyze existing ASV prototypes to gain insight into the status and trend of ASV research.@en

Autonomous Surface Vessels (ASVs) have been involved in numerous projects since the 1990s. Many ASV projects have been successfully realized, and as many are still under development. Together with the development of those new autonomous vessels, the research on classification about ASVs has become important. The classifications provide clarity to researchers, designers, shipbuilders, equipment manufacturers, ship owners and operators, enabling accurate specification of the desired level of autonomy in design and operations. Moreover, the involved research paves the way to a clearer understanding of the opportunity and challenges of research on autonomous vehicles. In this paper, we introduce the emerging concept of autonomous vessels. A multi-layer multi-agent control architecture of cooperative transport systems from the perspective of ASVs is proposed. Moreover, we provide an overview of existing research on the classification of autonomy. Based on the analysis, a detailed definition and categorization of autonomy levels for ASVs is proposed starting from the characteristics of ASVs and existing classification of autonomy. The proposed autonomy levels categorization assesses the overall autonomy level of a vessel by analyzing the automated sub-systems: Decision, Actions, Exceptions, and Cooperation. This categorization can be used to analyze existing ASV prototypes to gain insight into the status and trend of ASV research.@en

Autonomous Surface Vessels (ASVs) have been developed for more than 20 years. Many ASV projects have been successfully realized, and as many are still under development. In literature there is a lack of research on the different applications and suitable environments for the deployment of ASV. Recently, a detailed definition and categorization of autonomy levels for ASVs has been proposed based on the characteristics of ASVs and existing classifications of autonomy. With this innovative autonomy level classification, this paper presents an extensive overview of existing ASV prototypes. The tendency and possible future developments of ASVs are analyzed according to the divisions obtained.@en

Autonomous Surface Vessels (ASVs) have various applications in the maritime sector. However, considerable challenges need to be met before integrating the applications in the current environment. Moreover, infrastructures in ports and waterways need to be upgraded to satisfy the requirements for ASV applications. To have an insight into the potential of ASVs in ports, we analyze the applications of autonomous vessels and the impacts that these applications have on port infrastructures. Future scenarios of the application of ASVs in ports are determined based on the analysis of the following three aspects: ASV applications, ASV technology development, and port infrastructure development. To indicate the development of ASV technology and port infrastructures, the Technology Readiness Level (TRL) is employed. Eleven scenarios of ASVs in ports have been identified based on the analysis. @en

Autonomous Surface Vessels (ASVs) have various applications in the maritime sector. However, considerable challenges need to be met before integrating the applications in the current environment. Moreover, infrastructures in ports and waterways need to be upgraded to satisfy the requirements for ASV applications. To have an insight into the potential of ASVs in ports, we analyze the applications of autonomous vessels and the impacts that these applications have on port infrastructures. Future scenarios of the application of ASVs in ports are determined based on the analysis of the following three aspects: ASV applications, ASV technology development, and port infrastructure development. To indicate the development of ASV technology and port infrastructures, the Technology Readiness Level (TRL) is employed. Eleven scenarios of ASVs in ports have been identified based on the analysis. @en

In this paper, a distributed control approach is proposed to enable fuel-efficient Vessel Train Formations (VTF) in inland waterways and port areas for addressing the efficiency and environmental issues of transport over water. For path tracking, collision avoidance, and consensus over the VTF speed a distributed Model Predictive Control (MPC) algorithm is adopted which uses the Alternating Direction Method of Multipliers (ADMM) to guarantee path following and consensus between vessels. The all-electric Direct Current (DC) configuration is considered for the Power and Propulsion Systems (PPS) of the autonomous vessels under study. Considering their PPS specification, the vessels negotiate with each other to agree on the most efficient speed for all the vessels in the VTF. Simulation results suggest that a significant amount of fuel saving can be obtained by using the proposed approach.@en

Urban waterways have great potential in cargo transport to relieve the congestion in the overloaded road networks. This paper explores the potential of applying cooperative multi-vessel systems (CMVSs) to improve the safety and efficiency of transport in urban waterway networks. A framework consisting of vessel train formation (VTF) and cooperative waterway intersection scheduling (CWIS) is proposed. Two types of controllers are introduced. Intersection controllers solve the CWIS problems and assign each vessel a desired time of arrival and vessel controllers are responsible for the VTF in waterway segments and the timely arrival at the intersections. An alternating direction method of multipliers (ADMM)-based negotiation framework is proposed for the cooperation among the controllers. The simulation experiments involving the scenarios in which up to 50 vessels sailing in the canal network in Amsterdam are carried out to illustrate the effectiveness of the proposed approach. In the simulation of an isolated intersection, rescheduling is triggered when some vessels cannot arrive on time. Although some ASVs arrive later, the time that is needed for all the ASVs to pass through is the same after rescheduling. Moreover, we compare the cooperative situation with the proposed CMVSs with a baseline situation. In the baseline situation, vessels avoid collisions using the generalized velocity obstacle (GVO) method and cross the intersection with a first in, first out rule. The CMVSs show better path following performance, while the GVO method needs fewer velocity changes. From the perspective of efficiency, the CMVSs help to reduce the total time to pass through the intersection.@en

Maritime Autonomous Surface Ships (MASS) attract increasing attention in recent years. Researchers aim at developing fully autonomous systems that replace the role of human operators. Studies either focus on supporting conflict/collision detection (for manned ships) or solving conflict automatically (for unmanned ships). The cooperation between human and machine has been less focused on in existing studies. However, this type of cooperation is essential both in practice and in the future: firstly, demands on navigational assistance are still strong for supporting navigators in manned ships; secondly, MASS with different autonomy levels require increasing cooperation between human operators and machines, e.g. monitoring automation, remotely controlling the ship, etc.; thirdly, the intelligence of human and the machines is highly complementary. Moreover, fully autonomous ships cannot replace all the manual ships overnight. Therefore, the future waterborne transport system will be a system in which both human-operated vessels and autonomous vessels exist. In this article, we firstly provide an overview of existing modes of human-machine interaction (HMI) during ship collision avoidance. Then, we propose a framework of HMI oriented Collision Avoidance System (HMI-CAS) whose decision-making process is interpretable and interactive for human operators. The HMI-CAS facilitates automatic collision avoidance and enables the human operators to take over the control of the MASS safely. Moreover, the proposed framework acknowledges the under-actuated feature of ships. Simulations are carried out to demonstrate the proposed HMI-CAS. The results show that the proposed HMI-CAS can not only control the under-actuated MASS to avoid collision automatically but also share the decision-making with human operators and support the operators to control the MASS.@en

Numerous methods have been developed for ship collision prevention over the past decades. However, most studies are based on strong assumptions, such as the need for a constant velocity of the target-ship, the limitation to two-ship scenarios, the simplification of ships’ dynamics, etc. Generalized Velocity Obstacle (GVO) algorithm can bridge these gaps. This paper presents a GVO algorithm for ship collision avoidance and designs a collision avoidance system (GVO-CAS). The proposed system visualizes the changes of one ship's course and speed resulting in collisions, which can be used not only for supporting the officer on watch to prevent collisions, but also for collision prevention of Autonomous Surface Vessels (ASVs) and for human operators taking over the control of ASVs. Simulation experiments show that the proposed collision avoidance system can work properly in various maritime environments. Compared to the original Velocity Obstacle algorithm, the GVO algorithm is more reliable and suitable for close range ship collision avoidance. Moreover, the GVO-CAS can offer rule-compliant evasive actions with a minimum number of required actions for ships. These results show the great potential to use the GVO algorithm in both manned and unmanned ships at sea.@en

This PhD thesis investigates V2V, V2I, and I2I cooperation of CMVSs for improving the safety and efficiency of waterborne transport. A predictive motion control framework and a generic negotiation framework are proposed to achieve consensus among controllers. Different applications provide insights into the impact of CMVSs on the performance of the waterborne transport systems. Specifically, four types of cooperation and their applications to the Port of Rotterdam and the metropolitan area of Amsterdam are investigated, i.e., Vessel Train Formation (VTF), Cooperative Floating Object Transport (CFOT), Waterway Intersection Scheduling (WIS), and Cooperative Waterway Intersection Scheduling (CWIS).@en

Compared to an individual Autonomous Surface Vessel (ASV), greater efficiency and operational capability can be realized by a team of cooperative ASVs for certain operations, such as search and rescue, hydrographic survey and navigation assistance. This paper focuses on cooperative floating object transport, i.e., a group of ASVs coordinate their actions to transport floating objects. We propose a multi-layer distributed control structure for the object transport system. The object transport problem is formulated as the combination of several sub-problems: trajectory tracking of the object, control allocation, and formation tracking of the ASVs. The sub-problems are integrated by a nonlinear towline model that describe the transformation of forces considering the mass and elasticity of the towline. A controller based on Model Predictive Control (MPC) is designed to control the motion of each ASV. A negotiation framework based on the Alternating Direction of Multipliers Method (ADMM) is then proposed to achieve consensus among the ASVs. Numerical simulations of utilizing the proposed cooperative system to move a large vessel sailing inbound the Port of Rotterdam are carried out to show the effectiveness of our method. Besides transporting barges and off-shore platforms, the proposed cooperative object transport system could also be a solution to coordinate non-autonomous vessels and ASVs in future autonomous ports where both human-operated and autonomous vessels exist.@en

Collison between ships is one of the major contributors to maritime accidents. To reduce ship collision accidents, the research on collision avoidance decision-making has been drawing much attention from various parties. In this research, extensive literature and expert knowledge are collected and analyzed to identify the common sense and discrepancies between collision avoidance decision-making for theoretical research and navigation practices. The key factors that are considered in the two perspectives are identified and discussed, based on which, the knowledge structures that can represent the development of the process in the two perspectives are established. A series of comparisons between the knowledge structure based on theoretical research and navigation practices are conducted. The comparisons indicate clear common sense and discrepancies between the theoretical research and navigation practices regarding collision avoidance decision-making. The potential causes of them are also analyzed. The research results would be beneficial for the development of collision avoidance decision-making for both autonomous and conventional manned ships in maritime traffic.@en

Collison between ships is one of the major contributors to maritime accidents. To reduce ship collision accidents, the research on collision avoidance decision-making has been drawing much attention from various parties. In this research, extensive literature and expert knowledge are collected and analyzed to identify the common sense and discrepancies between collision avoidance decision-making for theoretical research and navigation practices. The key factors that are considered in the two perspectives are identified and discussed, based on which, the knowledge structures that can represent the development of the process in the two perspectives are established. A series of comparisons between the knowledge structure based on theoretical research and navigation practices are conducted. The comparisons indicate clear common sense and discrepancies between the theoretical research and navigation practices regarding collision avoidance decision-making. The potential causes of them are also analyzed. The research results would be beneficial for the development of collision avoidance decision-making for both autonomous and conventional manned ships in maritime traffic.@en

Recently, the cooperative control of multiple vessels has been gaining increasing attention because of the potential robustness, reliability and efficiency of multi-agent systems. In this paper, we propose the concept of Cooperative Multi-Vessel Systems (CMVSs) consisting of multiple coordinated autonomous vessels. We in particular focus on the so-called Vessel Train Formation (VTF) problem. The VTF problem considers not only cooperative collision avoidance, but also grouping of vessels. An MPC-based approach is proposed for addressing the VTF problem. A centralized and a distributed formulation based on the Alternating Direction of Multipliers Method (ADMM) are investigated. The distributed formulation adopts a single-layer serial iterative architecture, which gains the benefits of reduced communication requirements and robustness against failures. The impacts of information updating sequences and responsibility parameters are discussed. We furthermore analyze the scalability of the proposed method. Simulation experiments of a CMVS navigating from different terminals in the Port of Rotterdam to inland waterways are carried out to illustrate the effectiveness of our method. The proposed method successfully steers the vessels from different origins to form a vessel train. Due to the effective communication, vessels can timely respond to the velocity changes that others make. After the formation is formed, the distances between vessels become constant. The results show the potential to use CMVSs for inland shipping with enhanced safety.@en

Recently, the cooperative control of multiple vessels has been gaining increasing attention because of the potential robustness, reliability and efficiency of multi-agent systems. In this paper, we propose the concept of Cooperative Multi-Vessel Systems (CMVSs) consisting of multiple coordinated autonomous vessels. We in particular focus on the so-called Vessel Train Formation (VTF) problem. The VTF problem considers not only cooperative collision avoidance, but also grouping of vessels. An MPC-based approach is proposed for addressing the VTF problem. A centralized and a distributed formulation based on the Alternating Direction of Multipliers Method (ADMM) are investigated. The distributed formulation adopts a single-layer serial iterative architecture, which gains the benefits of reduced communication requirements and robustness against failures. The impacts of information updating sequences and responsibility parameters are discussed. We furthermore analyze the scalability of the proposed method. Simulation experiments of a CMVS navigating from different terminals in the Port of Rotterdam to inland waterways are carried out to illustrate the effectiveness of our method. The proposed method successfully steers the vessels from different origins to form a vessel train. Due to the effective communication, vessels can timely respond to the velocity changes that others make. After the formation is formed, the distances between vessels become constant. The results show the potential to use CMVSs for inland shipping with enhanced safety.@en

Recently, Autonomous Surface Vessels (ASVs) have attracted a lot of attention. Developing a fully autonomous vessel is challenging. Existing research provides a track from existing manned vessels to a remote-controlled vessel with reduced crews, an unmanned remote-controlled vessel, and at the end, a fully autonomous vessel. The first step is to equip existing vessels to realize autonomous sailing. In this paper, we focus on the technologies that make existing vessels “smarter”. A categorization of technologies is provided based on the basic architecture of ASV: Navigation, Guidance, Control and Hardware. An overview of the technology developments in each category is presented. The Technology Readiness Level (TRL) is applied to indicate whether these technologies could become commercial in the short term.@en

Recently, Autonomous Surface Vessels (ASVs) have attracted a lot of attention. Developing a fully autonomous vessel is challenging. Existing research provides a track from existing manned vessels to a remote-controlled vessel with reduced crews, an unmanned remote-controlled vessel, and at the end, a fully autonomous vessel. The first step is to equip existing vessels to realize autonomous sailing. In this paper, we focus on the technologies that make existing vessels “smarter”. A categorization of technologies is provided based on the basic architecture of ASV: Navigation, Guidance, Control and Hardware. An overview of the technology developments in each category is presented. The Technology Readiness Level (TRL) is applied to indicate whether these technologies could become commercial in the short term.@en