Publications

Evaluating the effect of risk metrics for supporting operational decision-making by autonomous surface vehicles

Supervised Dynamic Probabilistic Risk Assessment of Complex Systems, Part 1: General Overview

Dynamic probabilistic risk assessment (DPRA) is a systematic and comprehensive methodology that has been used and refined over the past decades to evaluate risks associated with complex systems. However, current approaches to construct and execute DPRA models are challenged by high execution time owing to numerous possible scenarios. This issue will affect the execution time of the model, which is in contrast with the aim of modeling. DPRA models must be sufficiently fast to assist decision-making processes in the required time. In this study, a new method is proposed to enhance the execution times of DPRA models. This method uses optimization algorithms to determine failure scenarios and sort scenarios based on their occurrence probabilities. The most efficient optimization algorithms, considering the nature of the DPRA models, are mixed-integer sequential quadratic programming, modified branch-and-bound algorithm, and modified particle swarm optimization, which are then compared and discussed. To validate the effectiveness of this method, a simple case study is presented. The results show the effectiveness of the method, which has high accuracy and reduces the execution time significantly (e.g. execution time of risk assessment of 16,464 possible behavior scenarios after an incident in a dynamic positioning system is one fifth of the conventional methods). A detailed supervised DPRA model of dynamic positioning systems and its application on three incidents that occurred in the Norwegian offshore sector in previous years is presented in a subsequent article (Part 2 of 1) (Parhizkar et. al.). Case study results confirm that the supervised DPRA method can be applied to other complex systems so that the dynamic probabilistic risk values can be evaluated quickly and accurately.

Fatalities in the Norwegian fishing fleet 1990–2011

Working at sea presents a considerable fatal accident risk to the fishers of the fleet, far exceeding any average land-based job, as far as incident rate per man-labor year. This no-doubt is the result of placing an industrial workplace on a moving, oscillating and inherently unstable working platform subject to the vagaries of the sea. Here hazardous work is conducted in cramped workspaces, on uneven, slippery and cluttered decks, with operations involving heavy fishing gears and mobile rotational machinery. The purpose of this article is to analyze the circumstances of the 281 deaths reported to the Norwegian authorities from the Norwegian fishing fleet over the period 1990–2011. The aim is to determine important characteristics and traits in the statistics, and to facilitate and focus the devising of future preventative intervention strategies. The results indicate that there has been a considerable reduction in the number of fatalities in the fishing fleet of Norway over this time frame. The average incidence rate for fatalities during the 22year study period is 8.71 per 10,000 man years. Single, fatality occurrences are a more important cause of deaths in the fleet than multiple casualty events. The most significant modes of fatality are vessel disasters followed by man overboard events and drowning in port. The findings lead to a discussion on both the significance of the preventative measures put in place over the past two decades and the future directions and evolutions required for continued success in reducing fatalities in the Norwegian fleet.

Supervised dynamic probabilistic risk assessment: Review and comparison of methods

With the adoption of autonomous systems in higher levels of autonomy, large-scale, complex and dynamic systems are becoming commonplace. Ensuring safe operation of safety-critical autonomous systems is paramount, typically approached through risk assessment. Two challenges associated with using traditional risk assessment methods for complex systems are that these systems are dynamic (i.e., their state changes over time) and interactions between subsystems and components may lead to unpredictable behaviors and impact on the surrounding environment and other systems in the close vicinity. Dynamic probabilistic risk assessment (DPRA) methods are possible solutions to these challenges, where the dynamic and uncertain nature of the systems is considered. The methods, however, usually face combinatorial explosion related to hazards and scenarios, which make their practical application prohibitive; in the DPRA literature, this problem is known as the state explosion problem. In this paper, we present a literature review on methods for DPRA, with focus on the existing solutions to the state explosion problem. Specifically, we analyze and compare these solutions in terms of computational time complexity, traceability and state–space coverage. Finally, we discuss the comparisons and propose potential paths to improved solutions for the state explosion problem based on the knowledge gained in the study.

Towards a Framework for Evaluation of Spatial Uncertainty for Risk-Based Robotic Decision-Making

Selecting Robust Sustainability Criteria for Vessel-Level Decarbonisation: A Framework Applied to a Norwegian Gillnet Vessel

Next Generation Subsea Inspection, Maintenance and Repair Operations

This paper presents the latest developments in the project Next Generation Subsea Inspection, Maintenance and Repair (IMR). Subsea IMR operations are frequently carried out in the offshore oil and gas business. Increased efficiency in such operations will reduce time of operations and costs. Autonomous functionalities constitute an enabler for such reduction. To this end, the project is focusing on technologies, algorithms and methods required for enabling the right level of autonomy and human-machine interaction in IMR operations. This includes new perception, localization, path-planning, and shared control technologies, as well as new methods for risk management. Although NextGenIMR has a particular focus on subsea operations in the oil and gas industry, the technologies developed will also be highly relevant for IMR operations in fish farms and in deep sea mining.

Organizational risk indicators for dynamic positioning operations—learnings from 20 years of FPSO—shuttle tanker incidents and accidents

No abstract is provided for this article.

Risk-based supervisory control for autonomous ship navigation

This paper proposes a novel method to transform the results of qualitative risk analysis into a numeric optimal control problem for autonomous ship navigation. Today, making autonomous high-level decisions replacing a crew onboard is considered difficult, in some part due to the complexity of managing the operational risks involved. Although human supervisors, e.g., located in remote operating control centers are still needed for safety and liability reasons, there is a growing demand for complex decisions to be made by the onboard control system itself, both during normal operations and in emergencies. This paper suggests general principles for how the results from systems-theoretic process analysis (STPA) can be transformed into a quantitative and computationally tractable optimization problem, solved by a MPC-based decision-making algorithm for autonomous navigation. The proposed method is demonstrated and evaluated by simulating an autonomous ship navigating in a coastal environment. It is concluded that the proposed method may serve as a reasonable and valuable bridge between the realms of qualitative risk analysis and numerical optimal control for risk-aware autonomous control and decision-making.

In the Aftermath of the Viking Sky Incident; Cruise Ship Safety in Norway and Potential Risk Reduction Measures

On March 23, 2019, the cruise ship Viking Sky with 1373 persons onboard almost grounded in severe weather conditions at Hustadvika, Norway. The near-miss incident had a major accident potential and clearly demonstrated the serious consequences that may result from loss of power and propulsion on a cruise ship close to the coastline in strong onshore winds and rough seas. This incident, combined with an increase in the cruise ship traffic in Norwegian waters, calls for risk reduction measures to be identified, evaluated, and implemented for the industry and society. It is not feasible to have sufficient search and rescue resources to handle worst-case scenarios with large cruise ships, and therefore proactive mitigation measures are necessary. This paper presents the challenges with cruise ship safety and emergency preparedness and gives recommendations for risk reduction measures. The paper is based on a White paper made by a Committee appointed by the Norwegian Government, with members (including the authors) and contributions from the industry, authorities, and academia.

Challenges and Solutions for Autonomous Systems Safety -- Findings from Three International Workshops (IWASS)

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Safety performance monitoring of autonomous marine systems

The marine environment is vast, harsh, and challenging. Unanticipated faults and events might lead to loss of vessels, transported goods, collected scientific data, and business reputation. Hence, systems have to be in place that monitor the safety performance of operation and indicate if it drifts into an intolerable safety level. This article proposes a process for developing safety indicators for the operation of autonomous marine systems (AMS). The condition of safety barriers and resilience engineering form the basis for the development of safety indicators, synthesizing and further adjusting the dual assurance and the resilience based early warning indicator (REWI) approaches. The article locates the process for developing safety indicators in the system life cycle emphasizing a timely implementation of the safety indicators. The resulting safety indicators reflect safety in AMS operation and can assist in planning of operations, in daily operational decision-making, and identification of improvements. Operation of an autonomous underwater vehicle (AUV) exemplifies the process for developing safety indicators and their implementation. The case study shows that the proposed process leads to a comprehensive set of safety indicators. It is expected that application of the resulting safety indicators consequently will contribute to safer operation of current and future AMS.

Human Factor Influences on Supervisory Control of Remotely Operated and Autonomous Vessels

Autonomous ships require efficient remote monitoring and human control intervention to ensure safety. However, there are knowledge gaps concerning human factors influences on remote supervisory control. We investigate the influence of five factors on remote supervisory control using a simulator experiment: (i) Skill, represented by either experienced navigators or gamers; (ii) Vigilance, manipulated by either 5 or 30 minutes in passive monitoring; (iii) Multitasking, represented by either 1 or 3 supervised vessels; (iv) Time Pressure, represented by 20- or 60-second critical time windows; (v) Decision Support, represented by presence or absence of a Decision Support System (DSS). The experiment was a randomized factorial design (n = 32) where volunteers completed a handover (automation detects a critical event and hands over control) and a takeover (operator detects a critical event and takes over control). We observed the following results: (i) Skill influenced performance when combined with Multitasking and Decision Support, favoring gamers; (ii) Vigilance influenced performance when combined with Time Pressure; (iii) Multitasking influenced performance directly, as did (iv) Time Pressure and (v) Decision Support. These outcomes contribute to the empirical basis of maritime human factors research and to safer design of autonomous vessels and their remote control centers.

Modelling the impact of human fatigue on the risk of shipping accidents

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.

Towards Safety Barrier Analysis of Hydrogen Powered Maritime Vessels

This paper focuses on the use of safety barrier analysis, during the design phase of a vessel powered by cryogenic hydrogen, to identify possible weaknesses in the architecture. Barrier analysis can be used to evaluate a series of scenarios that have been identified in the industry as critical. The performance evaluation of such barriers in a specific scenario can lead to either the approval of the design, if a safety threshold is met, or the inclusion of additional barriers to mitigate risk even further. By conducting a structured analysis, it is possible to identify key barriers that need to be included in the system, intended both as physical barriers (sensors, cold box) and as administrative barriers (checklist, operator training). The method chosen for this study is the Barrier and Operational Risk Analysis (BORA) method. This method, developed for the analysis of hydrocarbon releases, is described in the paper and adapted for the analysis of cryogenic hydrogen releases. A case study is presented using the BORA method, developing the qualitative barrier analysis. The qualitative section of the method can be easily adapted to vessels of different class and size adopting the same storage solution. The barrier analysis provides a general framework to analyze the system and check that the safety requirements defined by the ship operator and maritime certification societies are met.

A Bayesian Approach to Risk-Based Autonomy, with Applications to Contact-Based Drone Inspections

<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>

Integration of risk in hierarchical path planning of underwater vehicles

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.

A Novel STPA Approach to Software Safety and Security in Autonomous Maritime Systems

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.