229 publications from this institution
Recently, numerous organizations have made progress in developing autonomous ships, motivated by, among other factors, the potential for increased safety. This applies especially to accidents involving human error, as autonomous ships would remove operator role from all or most operations. The reality is that although the human role is reduced, autonomous ships would still rely on operators for supervision, remote control, and involvement in case of a glitch or an unexpected situation. Thus, autonomous ships do not fully eliminate the possibility of human error. In this study, we assess the potential for human error in autonomous ship operations. We analyze an unmanned autonomous ship operation, and through a generic analysis of the interaction between operators working a Shore Control Centre (SCC) and system, we identify possible Human Failure Events (HFE). This provide a starting point for performing human reliability analysis of autonomous ships operation.
This article describes a new product life cycle model that can be used by producers to improve safety and to prevent defective products from being placed on the market. The model has eight phases and the article describes and discusses the required safety-related issues in each phase. Analytical methods that should be used in the various phases are identified. Both consumer and industrial products are covered. The article outlines main product safety requirements with focus on European product safety legislation. The concept adequate safety is introduced as an acceptance criterion for the producer during the product development process, and factors that should be taken into account when deciding whether or not a product has adequate safety are discussed.
In this chapter, the online risk levelRisk level of different dynamic positioningDynamic positioning (DP) systems is assessed based on the methods presented in Chap. 2 . The proposed methods are able to provide an online risk levelRisk level of the system in different operating and environmental conditionsEnvironmental conditions that could assist decision makers to make better (safer) decisions. In the first example, (All proprietary, identification, sensitive, and confidential information are removed.) Subsect. 7.1, a DP drilling unitDrilling unit incidentIncidents is simulated. In this incidentIncidents, the operator has two choices of manual or automaticAutomatic disconnectionDisconnection. A risk modelRisk model is utilized to estimate the risk levelRisk level of these two scenarios and provide useful information to the operator to select the safer option. In this example, two operators with different behaviors are compared, and the effect of human performance on the system risk levelRisk level and scenario selection is discussed. In the second, third and fourth examples (AutomaticAutomatic mode: the DP system automatically maintains the vessel position using the control system and related actuators.) (Subsect. 7.2, 7.3, and 7.4, respectively), supervised failure scenario generationSupervised failure scenario generation is presented. In these examples, different DP incidentsIncidents are investigated, initial eventsInitial event, operating and environmental conditionsEnvironmental conditions are used as risk modelRisk model inputs, and the modelModel predicts the most probable failureFailure scenarios. In each example, the most probable failureFailure scenarios are compared with real incidentsIncidents. The generated scenarios could help operators to make better decisions to avoid most probable failureFailure scenarios.
No abstract is provided for this article.
Sustainable fisheries are the main objective of Norwegian fisheries management. Despite powerful management tools, sustainability in the fisheries sector is not an easy task. There is no formal definition of the concept, and operationalization is vague. In recent years, private actors and non-governmental organizations (NGOs) have increased their impact on defining sustainability in the fisheries, which has reduced the power of the traditional fisheries management to determine its content. The lack of a clear strategy for fisheries management to increase sustainability makes it timely to address three research questions: (i) what is meant by “sustainable fisheries”, (ii) to what extent has the institutionalization of the Norwegian fisheries management channeled the sustainability concept towards specific trajectories, and (iii) what are the options and hard choices available to increase sustainability in the Norwegian fisheries in the future? These questions are investigated in this article.
No abstract is provided for this article.
The International Workshop for Autonomous System Safety (IWASS) is a joint effort by the B. John Garrick Institute for the Risk Sciences at the University of California Los Angeles (UCLA-GIRS) and the Norwegian University of Science and Technology (NTNU). IWASS is an invitation-only event designed to be a platform for cross-industrial and interdisciplinary effort and knowledge exchange on autonomous systems' Safety, Reliability, and Security (SRS). The workshop gathers experts from academia, regulatory agencies, and industry to discuss challenges and potential solutions for SRS of autonomous systems from different perspectives. It complements existing events organized around specific types of autonomous systems (e.g., cars, ships, aviation) or particular safety or security-related aspects of such systems (e.g., cyber risk, software reliability, etc.). IWASS distinguishes itself from these events by addressing these topics together and proposing solutions for SRS challenges common to different types of autonomous systems. IWASS 2022 was held on August 28th in Dublin, Ireland, and gathered 30 participants from 20 organizations from around the globe. In addition, a panel session at the European Safety and Reliability Conference (ESREL 2023) discussed the workshop's main conclusions and additional points with a larger audience. This report summarizes IWASS 2022 discussions. It provides an overview of the main points raised by a community of experts on the current status of autonomous systems SRS. It also outlines research directions for safer, more reliable and secure future autonomous systems.
No abstract is provided for this article.
This article discusses the performance of the Norwegian fishing fleet within an acceptable level of sustainability. Previously, the cod-fishing fleet has been evaluated at the attributes—accident risk, employment, profitability, quality of the fish meat, catch capacity, greenhouse gas emissions/acidification, and bycatch/selection. The assessments focused on the first four steps of the systems engineering process, i.e., from needs identification to trade-offs of system alternatives. The objective of this paper is to focus on the last steps of the process; design, solve, verify, and test, to improve the decision-basis for fisheries management in order to increase sustainability in the fishing fleet. More specifically, this means to analyze the decision-making situation and develop acceptance criteria of a sustainable Norwegian cod-fishing fleet to enable fisheries management to monitor the sustainability performance of the fleet on a regular basis.
A working fishing vessel at sea is an elaborate collection of interacting accident potentials, barely controlled. Even the deck underfoot betrays the unwary, as can every other aspect of the normal daily grind onboard, as fishers ply their trade in weather foul and fair. All elements of the vessel at sea conspire in making this the most dangerous and difficult of all professional callings, an inexplicable calling where life and limb are continually at risk. This article is based on an examination of reported occupational injuries from the Norwegian fishing fleet from 2000 to 2011. The aim is the determination of important characteristics and traits in the statistics, which may be used to focus and further preventative measures to be applied within this fleet. The results indicate that the current intervention programs and improvement measures have to date made a significant impact on injury levels within the fleet. This study has borne witness to a reduction in injury numbers and incident rates year on year for the past 12 years. It identifies the trawler fleet as the seat of the highest incident rates of injury occurrence, while the small coastal fleet had the lowest reported numbers of injuries. Under-reporting of minor injuries is revealed as a problem in the current reporting system of fisher injuries while the manner, location and body regions of reported injuries are also investigated. These findings lead to a discussion on the future requirements for the Norwegian fleet for further injury reduction and improved reporting practices.
<p>Enabling higher levels of autonomy requires an increased ability to identify and handle internal faults and unforeseen changes in the environment. This article presents an approach to improve this ability for a robotic system executing a series of independent tasks by using a dynamic decision network (DDN). A case study of an industrial inspection drone performing contact-based inspection is used to demonstrate the capabilities of the resulting system. The case study demonstrates that the system is able to infer the presence of internal faults and the state of the environment by fusing information over time. This information is used to make risk-informed decisions enabling the system to proactively avoid failure and to minimize the consequence of faults. Lastly, the case study demonstrates that evaluating past states with new information enables the system to identify and counteract previous sub-optimal actions. </p>
Human fatigue is influencing the risk of maritime accidents. A ship`s bridge sailing in trafficked waters is a multi-causal and complex system. Decisions made on the bridge may have invisible and delayed consequences. This article explains how and why accident investigation reports can be used to construct easily updateable quantitative risk assessment models which take human factors into account. The article then makes use of the Barrier and Operational Risk Analysis (BORA) method to illustrate an example by conducting a case study of the effect of human fatigue on maritime groundings. The case study indicates that lowering the probability of human fatigue and alcohol misuse on board does not decrease the probability of grounding as much as lowering the probability of barrier failures (lookouts, watch alarms and VTS radio calls). Less than adequate scores on human fatigue, safety climate and manning levels have a stronger effect on the probability of grounding then adequate scores.
For autonomous maritime systems, tasks and responsibilities are moving from the human operator to hardware and software, which means that the software part grows in size and complexity. Software failures may be introduced from the early life cycle phases intentionally or unintentionally, and these must be mitigated by safe and secure design approaches. This paper addresses the need for systematic and efficient software failure identification and risk mitigation and proposes a novel approach by extending the Systems-Theoretic Process Analysis (STPA) with the System Modeling Language (SysML) as a basis. To demonstrate the proposed method, a case study on a semi-autonomous ferry's navigation system that operates in automatic or manual control mode is performed. The control structure and its extension are modeled utilizing implementation platform independent software, hardware, and human operator parts, covering both the dynamic and static aspects of the software functions from the software specification. The focus is on creating an avoidance map data structure, including both moving and static obstacles to be avoided by the ferry and the subsequent process of collision risk warning calculation. An implementation platform independent software failure questionnaire is developed and applied for a structured and guided search of potential software failures. The criticality of the identified software failures is evaluated over the development of loss scenarios covering cascading failure effects in software. In the case study, the identified software failures are evaluated in a loss scenario where the ferry operates under foggy conditions. Lastly, related to the hazard evaluation and risk reduction of critical software failures, the paper discusses the classic and novel approaches to mitigation in the form of fallback procedures and operational constraints. The paper shows that critical software failures may be handled by design and testing techniques to minimize the potential impact on autonomous systems´ safety and security.
This paper focuses on path planning problems integrating the risk of collision. This challenge is crucial regarding the use of autonomous underwater vehicles (AUVs) for inspection, maintenance and repair operations. The solving of this problem in a reasonable amount of time enables integration of path planning in the AUV control architecture and, by this way, enhances its autonomy capability. Classical approaches rely on the A-Star algorithm to solve this problem, but the heuristic associated to the collision risk appears to be inefficient in some cases. Based on the hierarchical technique, i.e., HPA-Star, another approach is proposed. It leads to paths close to the optimal ones calculated in a faster way. The performances are illustrated in the context of a multi criteria optimization: minimal length and minimal risk path planning.
With higher autonomy in maritime systems, tasks and responsibilities are moved from the human operator to software, increasing the complexity and the importance of safe and reliable functionality. Software failures, however, may be introduced from the early life cycle phases intentionally or unintentionally, and these must therefore be mitigated by safe and secure design approaches. A challenge is that existing methods are not particularly well-suited for analyzing software risks. Thus, the objective of this paper is to propose a systematic and efficient software failure identification approach by extending the Systems-Theoretic Process Analysis (STPA) with a software failure taxonomy and the System Modeling Language (SysML). This enables the control structure in STPA to cover both the dynamic and static aspects of the software functions. Combined with an implementation platform independent questionnaire, this gives a more systematic and guided search for potential software failures than existing approaches. To demonstrate the proposed approach, a case study on a ferry's navigation system that operates in manual control or semi-autonomous mode is performed. In the case study, the focus is on creating an avoidance map data structure, including both moving and static obstacles to be avoided by the ferry, and the subsequent process of collision risk warning calculation. Software failures are identified and evaluated in collision scenarios where the ferry operates under foggy conditions. The paper shows that the proposed systematic approach provides an improved process for identifying and analyzing critical software failures. This facilitates enhanced risk mitigation in the design and testing phases contributing to autonomous systems' safety and security.
