Table of contents

Preface

This special Issue presents peer-reviewed papers presented the 3^rd International Conference on Maritime Autonomous Surface Ships (ICMASS), held in Ulsan, R. O. Korea, 11 – 12 November 2020. The ICMASS is the conference which presents cutting edge works on autonomous ships to both academic and industry researchers. The first International Conference on Maritime Autonomous Surface Ships (ICMASS) was arranged in 2018 in Busan, Korea and in 2019 in Trondheim in Norway. Due to COVID-19 pandemic, the conference program this year is provided with online conference. ICMASS 2020 is organized by UIPA (Ulsan ICT Promotion Agency), KMOU (Korea Maritime and Ocean University) and KAUS (Korea Autonomous and Unmanned Ship Forum) and, and co-organized with the International Network for Autonomous Ships (INAS).

List of ICMASS 2020 Editorial Board, ICMASS 2020 Steering Committee, ICMASS 2020 Program Committee, ICMASS 2020 Local Organizing Committee and images are available in this pdf.

All papers published in this volume of IOP Conference Series: Materials Science and Engineering have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

• Type of peer review: Single-blind

• Conference submission management system: Yes

• Number of submissions received: 72

• Number of submissions sent for review: 38

• Number of submissions accepted: 35

• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 48.61

• Average number of reviews per paper: 2

• Total number of reviewers involved: 30

• Any additional info on review process: N/A

• Contact person for queries:

Kwangil Lee

Korea Maritime and Ocean University

leeki@kmou.ac.kr

Misunderstanding the intentions of other vessels is one of the most common causes of ship collisions today. Such misunderstandings are particularly dangerous during navigation in restricted areas, such as fairways, port areas, and inland water ways, and may be exacerbated with the introduction of unmanned vessels. To ensure safe operations, the understanding of the intentions and future positions of manned and unmanned vessels, the PREParE SHIPS project is creating a system capable of determining a ship's position with high accuracy, predicting its future positions, and communicating the current and future positions. The positioning sub-system combines the signals of Galileo and EGNOS, EGNSS and SBAS respectively, with land based RTK corrections, providing a positioning accuracy of centimetres. Furthermore, by taking advantage of Galileo's authentication features, the positioning system provides enhanced security measures against spoofing attacks. The prediction sub-system will use a ship dynamic model and machine learning to predict the future positions of the ship and improve said predictions with time, while the communication sub-system will broadcast the prediction through VDES ship2ship and ship2shore. PREParE SHIPS will improve the navigation and handling of ships, through high accuracy positioning and dynamic predictions, as well as reduce the risk of ship collisions, through the communication of present and predicted future positions. PREParE SHIPS is expected to increase safety and efficiency significantly and will be the base of future autonomous operations and standardisations.

The ASD tug is considered the modern habour tug due to its versatility in performing a wide variety of tugging/towing operations. With the advent of autonomous systems and desire to improve operations, there are benefits to automating the tug operations. Under different operating environments, there could be uncertainties in the model and the disturbance from the environment significant enough to affect the performance and control of the tug. In this paper, we consider the problem of tracking a desired trajectory for an autonomous ASD tug in the presence of uncertainties and unknown disturbances. The numerical modelling of an ASD tug based on a modified 4-DoF MMG model is first presented. The modified Maneuvering Modeling Group (MMG) model is then used to design a model based backstepping control. Thereafter, a adaptive neural network approximator is introduced which has the capability to account for uncertainties and unknown disturbance. The combination of approximation-based and backstepping design techniques allows us to handle time-varying model uncertainties. Stability analysis is carried out for the control design via Lyapunov analysis. Simulation are carried out for the tracking of maneuvering motion paths to demonstrate the performance of proposed approach.

The concept of autonomous mobile robots (AMR) has gained much popularity in recent years, particularly in commercial settings where the name industrial autonomous mobile robot (IAMR) is proposed. In addition to automatic guided vehicles and automated mining trucks, IAMR also includes autonomous merchant ships. AMR is an old concept which was first introduced in the 1980s. Although the concept of AMRs is old and broadly used, there is still no common definition of autonomy when mobile robots are concerned. This paper will review some of the most known definitions and develop a taxonomy for autonomy in mobile autonomous robots. This will be used to compare the different definitions of robotic autonomy. This paper will mainly look at industrial autonomous mobile robots, i.e. systems that are designed to operate with a clear commercial objective in mind and which are normally supported by a remote control centre. This means that the robot is not fully autonomous, but to varying degrees dependent on humans in some control and monitoring functions.

The Concept of Operations, or ConOps, has become a central document for the specification, design and approval of autonomous ship systems and operations in the absence of prescriptive rules and regulations. The flexible structure of the ConOps and the fact that it is written in prose text makes it very accessible for all involved stakeholders, but also prone to discrepancies between the descriptions and the actual design. This paper proposes a description framework, for autonomous ship systems and operations, that covers the information items requested through the ConOps. The proposed framework has the potential to facilitate development of a formalized ConOps, which in turn could lead to a standardization of the current approval procedures for autonomous ship systems and operations.

The development of unmanned and autonomous vessels has accelerated, resulting in the requirement to study the law surrounding shipping. This article studies recent literature and case laws to determine the various interpretations of the word 'ship'. It, thereafter, seeks to determine which of these will have a bearing on autonomous vessels and whether the foreseeable technological incorporation is a challenge. Primarily, the focus is on showcasing that definitions across jurisdictions vary. The author points out that in the domain of private international law, this will result in disputes regarding applicability of admiralty laws.

The Autonomous Ship(AS) is a dream ship which navigates the sea on its own without any captains or crews. Many related studies on AS and the advent of deep learning technologies enable ASs voyage in the near future. They have been focused on proposing and verifying feasibility of their concept. However, there have not been little tried to compare results of ASs to that of captains. In this paper, we propose an Intelligent Autonomous-Ship Framework(IASF) which enables to develop ASs based on deep-learning while supporting fundamental functions necessary for ASs such as collecting navigational information, recognizing navigational status, and controlling route. The IASF-based AS was evaluated through simulation with compared to results of captains.

This is a concept paper making propositions for MASS navigation in national coastal waters. The focus is on human factors and the interaction between automation and operators in a remote control centre, as well as seafarers on conventional ships interacting with MASS. Important element is to understand the hand-over process of command, from automation to humans in control, based on the automation on board the vessel as well as the infrastructure surrounding the vessel.

This paper presents an overview of the aspects related to meaningful human control in autonomous shipping. Autonomy is described as a multi-faceted construct including self-sufficiency and self-directedness, which are related to a range of conditions a ship can deal with. This means that autonomy levels will vary in different operational situations. As a consequence, active operator involvement and workload will fluctuate and will sometimes be unpredictable. In case of supervising multiple ships, it is not feasible to maintain a minimal level of situation awareness of all the ships. In order to facilitate operator situation awareness recovery and other human-automation collaboration principles an Intelligent Operator Support System concept is outlined. Whether the large-scale application of Maritime Autonomous Surface Ships will provide equivalent safety and resilience levels will largely depend on the intelligence of the onboard control systems, the design quality of the human-autonomy collaboration system, and the competence and training level of the SC-operators.

5G, the next generation of mobile networks, aims to deliver wireless connectivity for new applications beyond traditional connectivity and mobile broadband for the smartphone market. For the maritime industry, 5G has the potential to address a wide range of usage scenarios within ship-to-ship, ship-to-shore, and onboard communication. In this paper, we give an introduction to mobile network technologies and systems in general, as well as an overview of technical capabilities and novelties introduced by the forthcoming 5G specifications relevant for maritime operations. Furthermore, perspectives related to applications and opportunities enabled by 5G networks are discussed, along with the potential benefits for unmanned and autonomous ships.

Autonomous shipping is considered to be one of the most important technologies in the maritime industry. Remote control of autonomous shipping is supported by communication solutions featuring long coverage, high throughput and low latency. Since 2018, together with the Norwegian Internet Service Provider (ISP) Telia, we have performed tests with a massive MIMO (Pre-5G) LTE base station, using the 3.7 GHz band, in Horten close to the Oslo fjord. The first Pre-5G tests with user terminal mounted on a 40 feet sailboat performed in 2018, showed great potential for maritime applications in terms of throughputs [1]. The Customer Premise Equipment (CPE) used in 2018 was a LTE Pre-5G terminal from Telia for fixed LAN use, and a modified version of it in 2019. However, since both the base station and the user terminal/CPE are not originally designed and optimized for maritime radio propagation environments, the test results in 2018 unveiled that a CPE designed for land usage experienced limited coverage and instability caused by received unstable signal level. Since 2019, a new user terminal prototype dedicated and optimized for maritime propagation conditions, was designed by Super Radio AS. This new CPE was tested in autumn 2019 under the similar setups as in 2018. The test results of the Reference Signal Receive Power and throughput are analysed and compared the test results in 2018. The comparison proved that the new user terminal solution showed considerable improvement with respect to stability and throughputs in the harsh maritime environments, which means that the new designed solution can be a potential maritime terminal solution for the remote control of autonomous shipping. The prototypes mounted at different places of the sailboat also show different system performances at the same TX-RX distances, which indicates the potential of exploiting the system diversity in the similar propagation environments.

Global Navigation Satellite System (GNSS) has been used as a key position, navigation and timing (PNT) input in applications or services provided by ships. However, GNSS is vulnerable to space-vehicle failures, solar disturbances, unintentional radio interference and deliberate jamming. Despite these weaknesses, GNSS has become a key element not only of maritime navigation, but also of critical national infrastructure, often without any backup being provided. In autonomous ships, the use of various integrated systems increases and the dependence on the location data of GNSS increases. Therefore, in the event of a GNSS failure, it is impossible to guarantee the safe operation of the ship and it has various accident possibilities. In this paper, we propose and describe the system newly that can collect PNTs from various equipment to detect anomalies, and measure and distribute PNTs from digital sextants, which are backup systems, when anomalies occur. In the future, we will verify the performance of the implemented system by a test with the full mission bridge simulator provided by the Kongsberg.

In this paper, AIS (Automatic Identification System), ship performance measurement and ECMWF (European Centre for Medium-Range Weather Forecasts) weather data were synchronized as a complete dataset. Detailed processing steps and methods are introduced which can be used as best practice for future related studies. All the data preparation was processed on a spark cluster. The optimization and turning of cluster performance will also be introduced. The synchronized dataset was adapted to train different machine learning models to predict ship propulsion power. The dataset includes 228 container vessels covering a time scale of 50 months. The performance of deep learning models with different architecture was compared and discussed. Compared to previous paper [1] in the same project, this paper is an extended scenario which combines the data adapted in scenario 1 and 2. The analysis of the models' performance in different scenarios was discussed. More features were included in scenario 3 (this study). Hence, the best performing model from scenario 3 has more complex structure compared to scenario 1 and 2. The overall absolute R² score for test data is slightly lower than scenario 2. However, the performance for individual ships (relative R² score) is much better. This means, models that consider more features (operation, ship characters and environment) are beneficial for individual analysis. For general fleet or wide scope analysis, models that require less data and fewer features are better.

The Maritime Safety Committee (MSC) of the International Maritime Organization (IMO) included an agenda item "Regulatory Scoping Exercise (RSE) for the use of Maritime Autonomous Surface Ships (MASS)" in order to determine how the safe, secure and environmentally sound operation of MASS may be introduced in the regulations. The results of the RSE have been reported to the MSC, and they will be discussed in the 102th session. The purpose of this study is to provide suggestions for making decisions on the necessary future work at the MSC. The authors have reviewed all the results of the RSE under the purview of the MSC and made discussions on the ways of addressing some important common issues. The suitability of the specific ways of addressing these issues may be turned out in the actual works for amendments. On the other hand, regarding the priority of the discussions, the authors consider that it is appropriate to give priority to the discussions on the partial automation and remote operation with seafarers on board over the fully autonomous or remote operations without seafarers on board. Also, it seems appropriate to give priority to the discussions on the navigation systems and tasks.

Currently, IMO discusses to develop international standard regulations for the use of Maritime Autonomous Surface Ships(MASS), and as a preliminary work to develop them, it carries out RSE work to identify measures that might arise when the existing conventions are applied to MASS. The RSE work is done by the Maritime Safety Committee (MSC), the Legal Committee (LEG), and the Facilitation Committee (FAL) for the conventions under the purview of each committee. In this paper, based on the results of the RSE work performed by each committee, a comprehensive analysis of potential gaps and themes that require further discussion and consideration in the next stage of international standard regulations for the use of MASS is presented.

Maritime autonomous surface ship (MASS) has been developed rapidly. MASS could be disruptive technology that will bring about a paradigm shift in related industries as well as the maritime transport system. Due to huge implications and uncertainties, it is required to understand complex socio-economic behaviour induced by MASS for the international society. This paper presents the key findings and some recommendations from technology assessment on MASS which investigated the potential effects from MASS in terms of economic, social, cultural and ethical aspects. The results can be used to design a future driven by MASS in a desirable direction.

Whilst the maritime world is preparing for autonomous vessels or Maritime Autonomous Surface Ships (MASS), as defined by IMO, we suggest an approach to investigate the risks involved with introducing such ships into service. This case study investigates the risks regarding other surface vessels that the MASS can encounter on their voyage between two berths used by coastal ferries in Norway. The ferries in this case, operate within a fjord declared as testbed for autonomous operations. Albeit the technology is available and declared ready, the area of operation is not. This paper seeks to address some of the remaining obstacles with regards to the risks involved.

Shipping undergoes rapid digitization, covering safety and security reporting, mandatory ship documentation, electronic port clearance as well as commercial and operational information exchanges. Increasing automation of information processing, including the specific needs for autonomous ships, requires increased "digital trust" to allow humans to remove themselves from the information processing loops. This includes better safeguards against cyber threats such as counterfeiting contents or the originator of critical messages. This paper describes thirteen use cases for maritime services and analyse how a Public Key Infrastructure (PKI) system can provide security barriers to mitigate relevant cyber threats and possible consequences of unwanted events. Such a PKI needs to be designed with the special maritime business constrains in mind; the most important being the international nature of shipping, the lack of connectivity for ships that are far from shore, the network constraints associated with existing communication technologies and regulatory considerations.

The digitalization of the maritime sector is continuously growing, leading to increased automation, such as, the development of autonomous vessels. The Autonomous Passenger Ship (APS) is a characteristic instantiation of this development, aiming to transport people on urban waterways. Although emerging technologies deployed in such APS aim to facilitate the functions and operations of the navigation and communication systems, various safety and security risks are inherent to the communication infrastructure due to their interconnectivity. The aim of this work is to study the safety and cyber security of the communication system of an APS, namely the MilliAmpere2 APS. The six step model (SSM) is utilized to facilitate the joint analysis. The application of the SSM enables, among others, the capturing of relationships between cyber attacks and component failures, the assessment of safety and cyber security countermeasures, as well as, the synergies between them. It has been found that most countermeasures in both categories are reinforcing or are conditionally dependent on each other, while few antagonize each another. These findings will allow for improved design and implementation of integrated safety and security management solutions.

While digitalization drives the development of autonomous ships, the risks rising out of digitalization were reviewed. Adoption of digital technology has many benefits, but the technology itself has its own faults, which will have users suffering from the learning curve. The digital devices onboard are not permanently reliable, and they can fail due to harsh utilization conditions, fatigue, or latent defects. As the shipping industry continues to move down the road towards digitalization, an alert need to be delivered ahead in order to minimize the potential future risks.

In a previous paper we have suggested that the transferal of human accountability from an on-site human actor (such as the captain) to a remote human actor (such as the creator of the autonomous control system) could be regarded as the defining characteristic of autonomous systems. In this paper we take this approach one step further, by suggesting a methodology for how accountability can be used as a basis for systems design of autonomous and remote-controlled operations. Furthermore, the suggested methodology is applied on a hypothetical case of a vessel supporting both autonomous and remote-controlled operation.

A reliable collision avoidance method is essential when operating an autonomous vessel. For this to become a reality, a number of researches have been conducted in order that the autonomous vessel could take an action for collision avoidance by herself. However, it may lead to dangerous situation without knowing the navigation intention of target-ships. In order to solve the issue, we developed the process map for collision avoidance based on information exchange via the communication relay system as follows: (i) the navigation situation analysis of the autonomous vessel was conducted based on manned ship voyage definition; (ii) the sequence diagram for information exchange was developed based on the autonomous vessel's navigation context and the communication relay system, and (iii) the process map for collision avoidance based on information exchange was proposed based on the developed sequence diagram and the existing collision avoidance method. It would be expected that the autonomous vessel could avoid collision more safely than taking an action by herself.

Resilience is an important feature of autonomous systems. To be resilient, a control system must be stable, robust, and safe. This paper explores the use of hybrid feedback controllers to ensure robustness towards uncertainties and disturbances in motion control systems for autonomous ships. Motivated by recent developments in control barrier functions (CBFs) for safe maneuvering of autonomous ships, a CBF-based hybrid kinematic controller for obstacle avoidance is proposed. The controller uses course angle as control input, making it suitable for ships with a limited speed envelope. The performance of the controller is illustrated by simulations, using an underactuated ship as a case study.

Autonomous ships rely on sensory data to perceive objects of interest in their environment. Deep Learning based object detection in the image domain commonly used to solve this issue. The robustness of such approaches in non-ideal conditions is, however, still to be proven. In this work state of the art methods are applied on the RetinaNet architecture attempting to create a more robust object detection network given noisy input data. The GroupSort activation function and Spectral Normalization is used and the results are compared to the standard RetinaNet network. Our findings show that these modifications perform better and ensure robustness under moderate noise levels, than the standard RetinaNet network.

Standardised test manoeuvres are used to identify the manoeuvrability of a vessel. Currently, most of these tests are unsatisfactory to properly judge the manoeuvring capabilities of an inland vessel which sails in different environments than the seagoing ships for which these tests were initially designed. Moreover, inland vessels tend to have non-conventional propulsion systems and configurations which further decreases the adequacy of these standardised tests. Therefore, this study investigates the inland-applicability of these existing standardised test manoeuvres. In addition, this study suggests three new manoeuvres: (i) the Counter Thrust Test, (ii) the Sine Angle Test, and (iii) the Simultaneous Zigzag Test. In order to validate the suitability of these tests, an autonomous inland cargo vessel performed two of these suggested manoeuvres, (i) and (ii), and one existing manoeuvre, named the Crabbing test. The data of these experiments show fruitful insights in the wide range of manoeuvring capabilities of the examined inland vessel, which the standardised tests would not have uncovered.

The paper aims to show possible ways in which increasing automation can be utilised in vessel navigation control especially in relation to Superyachts. It will start with a brief section on how navigation systems have been evolving to where we are now. It will then explore what is currently accepted and what benefits superyachts in particular may gain from further autonomy mainly from the aspect of possible changes to space utilisation. Finally a suggested path of evolution towards autonomy, in order to give enhanced owner and guest experience, will be outlined.

The objective of this paper is to describe a protocol for exchange of navigational data between ships operating in close proximity. The protocol supports the exchange of data needed for relative positioning and includes geometry data of the objects involved in the operation in addition to inertial and positional data. The protocol takes into account the variable and limited communication capabilities that may be available for maritime operations. The paper describes one use case where two ships perform a simultaneous operation and another use case where a ship broadcasts its intended route. A S-100 Application Schema covering the required data is presented. Examples of the message exchange and bandwidth requirements are given. The resulting protocol will be useful for autonomous systems and ships that need standardized exchange of data to support situational awareness during their passage. The paper is written as part of the H2H project [1] which is developing an open system architecture to ensure interoperability between different vendors of autonomous systems when it comes to the data exchange related to position and geometry data.

Using digital twins in voyage performance evaluation is becoming critical for ocean vessels to reduce GHG emissions. A novel GBM approach is proposed in this paper to establish a digital twin model for voyage performance prediction. The weather hindcast data are introduced to enrich noon reports (NR) and automatic identification system (AIS) datasets, which are split into training and validation sets to develop GBM. The NR and AIS datasets collected from a 57000DWT bulk carrier are used to demonstrate the fidelity and capability of the proposed GBM. The voyage performance prediction from the GBM shows better accuracy than those from pure WBM or pure BBMs. An arrival time forecast and a weather routing showcase are also presented to demonstrate the application effects of GBM. The proposed GBM provides a satisfying prediction of ship speed and fuel consumption without mandatory sensor-collected data, thus applicable for a varity of vessels. In those cases where more sensors are available onboard, the proposed approach can incorporate sensor data to improve the model accuracy further.

Maritime Autonomous Surface Ships (MASS) do require shifting from human information processing to automation functions. While supporting the sensory processing of human navigation by automated information acquisition from different sensors is an already established (and even in many cases mandatory) technology with a set of framing standards and information exchanges, defining a common data set for a perceived environment model is currently neglected which hinders modularization of MASS technology development. Beginning with an introduction into the navigational process as well as information processing, this paper subsequently proposes an initial minimum data set for different aspects of ship navigation.

Aiming at the problems of miscellaneous navigation safety information and the difficulty of multi-source heterogeneous information fusion, a novel ontology-based collision avoidance decision making method is proposed in this paper. first of all, the structured ontology model of navigation situation is built on the basis of analysing the hierarchy and interactivity of various scene elements in driving scene and constructing the semantic model of entity class and binary attribute of scene elements, implement effective modelling of navigation scenarios. Secondly, the knowledge base of collision avoidance decision and online reasoning system are constructed based on the semantic expression of typical scene elements to realize the efficient utilization of navigation prior knowledge. Finally, the simulation experiment is carried out for the typical ship encounter scenarios in open water. The results show that the ontology method can effectively improve the cognition ability of Maritime Autonomous Surface Ships (MASS), and meet the requirements for real-time, safety and rationality of collision avoidance decision.

The European maritime transport policy recognizes the importance of the waterborne transport systems as key elements for sustainable growth in Europe. A major goal is to transfer more than 50% of road transport to rail or waterways within 2050. However, waterways are at a disadvantage as they normally depend on transhipment and land transport to and from final destination. To meet this challenge we need a completely new approach to short sea and inland waterways shipping in Europe. This needs to include ships as well as ports and the digital information exchanges between them. A key element in this is automation of ships, ports and administrative tasks. The AEGIS project has been funded by the EU Commission to develop new knowledge and technology to address this challenge.

Vessel groundings pose a major risk for maritime safety, constituting 20 percent of all incidents in the last decade. Frequent dredging and bottom mapping are resource intensive solutions currently employed, but these services cannot be maintained with the necessary frequency in all critical areas. While ships are carrying echo sounders to acquire precise and current under keel clearance data, it does not allow the vessel to react to possible deviations from the map data. Within the RoboVaaS project, a service is designed, implemented and tested in simulation. This service consists of one or more small MASS travelling ahead of a merchant vessel, collecting bathymetric data with enough lead time for the merchant vessel to react to possible threats, e.g. by course correction. This service is tested in compliance with the IMO HCD guideline in a quick approach and safe environment using a ship handling simulator. The simulator is augmented by a display system based on an ECDIS map and displaying the bathymetric data in three different scenarios. These scenarios are tested with nautical officers to collect feedback for service design and implementation with trained personnel and show the effectiveness of the chosen human machine interface.

Testing that ships are compliant to specified safety requirements have traditionally relied on real world data, which is not scalable and limited to testable scenarios due to financial and ethical reasons. Low fidelity simulations have been used to counteract some of these problems, which is sufficient for emulating simpler systems such as radar detectors, but not for testing complex systems as found in computer vision. In the automotive industry the use of game engines have shown to be a great testing platform due to their customizability, and combination of real-time physics with computer graphics to create large volumes of high fidelity images. In the work presented here, development of an open-source maritime platform named Autoferry Gemini based on the Unity game engine is used to simulate sensors in real-time. Utilizing simulated optics and general purpose GPU programs, the render pipeline is capable of modeling lidar, radar, visible-light and infrared camera sensors simultaneously. Results from visible-light cameras and lidar have already proven to satisfy other research activities on sensor fusion for autonomous ship technology. Infrared cameras motivates further research in gathering empirical data, while GPU algorithms have made it possible to simulate 3D radar models and multiple lidar types in real-time.

This paper is intended to reflect the achievements of the European Maritime Simulator Network (EMSN Connect) and the Asian Pacific Maritime Simulation Network (APMSN established in 2019), and the achievements of this project, to create a global digital testbed for the entire shipping industry.

In recent years, Autonomous Surface Vehicles have secured the focus of major research and industrial initiatives around the world. Following this trend in the wake of fourth industrial revolution of oceans, Marine Autonomous Surface Ships (MASS) have become the focus of numerous research. In order to shift from conventional ships to autonomous transportation, manoeuvring data collected through real-ship trials have to be available, and analysed. In this study, manoeuvring characteristics of a real ship were studied over a period of three years, data were collected and analysed to identify changes of manoeuvring characteristics over time. Real-ship data were then compared with simulation data to validate a manoeuvring simulator program. Through the real-ship experiments, not only the simulation results were validated, but also the possibility of predicting ship manoeuvrability using simulations in controlled environments was identified. In addition, the importance of accumulation of manoeuvring data in helping future designs of ships with similar characteristics is identified.

This paper describes how different motion sensors can be integrated and fused to obtain necessary navigational requirements needed for autonomous operations. Both autonomous coastal navigation and automatic docking operations are analysed with respect to trade-offs in position and velocity accuracies, integrity, availability and continuity. By using AIS measurements from typical docking operations for the Norwegian coastal express vessels it is possible to define feasible safe trajectories for the docking operations. Justified requirements can be obtained using closed-loop analysis for the specific vessel and its operation. Both vessel and passenger safety can be related to vessels horizontal velocity and the safe velocity concept has been introduced to derive requirements for integrity, availability, alarm limit and continuity in case of unreported/unhandled errors in the navigation system. The outcome of this study is a design tool, or a generic methodology for selecting the most promising combination of the integrated sensor components to obtain necessary navigation system performance for safe autonomous navigation.