Quantifying protocol evaluation for autonomous collision avoidance

Collision avoidance protocols such as COLREGS are written primarily for human operators resulting in a rule set that is open to some interpretation, difficult to quantify, and challenging to evaluate. Increasing use of autonomous control of vehicles emphasizes the need to more uniformly establish entry and exit criteria for collision avoidance rules, adopt a means to quantitatively evaluate performance, and establish a “road test” for autonomous marine vehicle collision avoidance. This paper presents a means to quantify and subsequently evaluate the otherwise subjective nature of COLREGS thus providing a path toward standardized evaluation and certification of protocol-constrained collision avoidance systems based on admiralty case law and on-water experience. Notional algorithms are presented for evaluation of COLREGS collision avoidance rules to include overtaking, head-on, crossing, give-way, and stand-on rules as well as applicable entry criteria. These rules complement and enable an autonomous collision avoidance road test as a first iteration of algorithm certification prior to vessels operating in human-present environments. Additional COLREGS rules are discussed for future development. Both real-time and post-mission protocol evaluation tools are introduced. While the motivation of these techniques applies to improvement of autonomous marine collision avoidance, the concepts for protocol evaluation and certification extend naturally to human-operated vessels. Evaluation of protocols governing other physical domains may also benefit from adapting these techniques to their cases. Keywords: COLREGS; Autonomous collision avoidance; Human–robot collaboration; Marine navigatio

Quantifying protocol evaluation for autonomous collision avoidance

Collision avoidance protocols such as COLREGS are written primarily for human operators resulting in a rule set that is open to some interpretation, difficult to quantify, and challenging to evaluate. Increasing use of autonomous control of vehicles emphasizes the need to more uniformly establish entry and exit criteria for collision avoidance rules, adopt a means to quantitatively evaluate performance, and establish a “road test” for autonomous marine vehicle collision avoidance. This paper presents a means to quantify and subsequently evaluate the otherwise subjective nature of COLREGS thus providing a path toward standardized evaluation and certification of protocol-constrained collision avoidance systems based on admiralty case law and on-water experience. Notional algorithms are presented for evaluation of COLREGS collision avoidance rules to include overtaking, head-on, crossing, give-way, and stand-on rules as well as applicable entry criteria. These rules complement and enable an autonomous collision avoidance road test as a first iteration of algorithm certification prior to vessels operating in human-present environments. Additional COLREGS rules are discussed for future development. Both real-time and post-mission protocol evaluation tools are introduced. While the motivation of these techniques applies to improvement of autonomous marine collision avoidance, the concepts for protocol evaluation and certification extend naturally to human-operated vessels. Evaluation of protocols governing other physical domains may also benefit from adapting these techniques to their cases. Keywords: COLREGS; Autonomous collision avoidance; Human–robot collaboration; Marine navigatio

Path Planning and Performance Evaluation Strategies for Marine Robotic Systems

The field of marine robotics offers many new capabilities for completing dangerous missions such as deep-sea exploration and underwater demining. The harshness of marine environments, however, means that without effective onboard decision-making, vehicle loss or mission failure are likely. Thus, to enable more autonomous operation while building trust that these systems will perform as expected, this thesis develops improved path planning and testing strategies for two different types of marine robotic platforms. The first portion of the research focuses on improved environmental data collection with an autonomous underwater vehicle (AUV). Gaussian process-based modeling is combined with informative path planning to explore an environment, while preferentially collecting data in regions of interest that exhibit extreme sensory measurements. The performance of this adaptive data sampling framework with a torpedo-style AUV is studied in both simulation and field experiments. Results show that the proposed methodology is able to be fielded on an operational platform and collect measurements in regions of interest without sacrificing overall model fidelity of the full sampling area. The second portion of the research then focuses on autonomous surface vessel (ASV) navigation that must comply with international collision avoidance standards and basic ship handling principles. The approach introduces a novel quantification of good seamanship that is used within an ASV path planner to minimize the collision risk with other vessels. This approach generalizes well to both single-vessel and multi-vessel encounters by avoiding rule-based conditions. The performance of this ASV planning strategy is evaluated in simulation against other baseline planners, and the results of on-water testing with a 29-ft ASV demonstrate that the approach is scalable to real systems. Beyond developing improved path planning frameworks, this research also explores methods for improved testing and evaluation of black-box autonomous systems. Statistical learning techniques such as adaptive scenario generation and unsupervised clustering are used to extract the failure modes of the autonomy from large-scale simulation datasets. Subsequently, changes in these failure modes are tracked in a novel form of performance-based regression testing. The effectiveness of this testing framework is demonstrated on the aforementioned ASV planner by discovering several types of unexpected failures

Charting Regulatory Frameworks for Maritime Autonomous Surface Ship Testing, Pilots, and Commercial Deployments

The report discusses how Maritime Autonomous Surface Ships (MASSs), ships capable of autono-mous and remote operations, should be regulated. It consists of an introduction and three main chapters. Chapter 2 introduces MASS technologies, focusing on the sensors, software components, and algo-rithms needed in autonomous navigation systems. The report provides an overview of the role of machine learning models in autonomous navigation systems. These are necessary especially in automating watchkeeping duties and require testing in multiple phases of the system development cycle. Chapter 3 discusses the existing IMO, EU, and national regulatory frameworks, in the context of MASS trials and pilot deployments in test areas in the Baltic Sea. It also considers how the rules should be changed to facilitate the trials and pilot deployment. It concludes that the current rules will allow MASS trials, provided that they are approved by the authorities. Permanent MASS deploy-ments, however, still require amendments of national and international rules. Chapter 4 discusses theme 4, outlining the building blocks and challenges of building a future regu-latory framework for MASS commercial deployments. The Chapter focuses on MASS ethics, auton-omous navigation system regulation, and liability and accountability for MASSs. Chapter 5 provides an executive summary of the main findings

Space Governance for the 21st Century: Balancing Space Development with Sustainability

The development of space is occurring in new ways and at an accelerated pace compared to even just a decade ago. As new and greater volumes of space activities, like large constellations of small satellites, space traffic management, and on orbit rendezvous, proximity, servicing, and assembly operations become routine, new international governance will be necessary to balance the development of space with space sustainability. While some international space governance does exist, it is poorly suited to govern new space activities and the environmental threats posed by space development. The need for new governance is well documented, yet the international community, and specifically the United Nations Committee on the Peaceful Uses of Outer Space (COPUOS), has been unable to organize around space governance and produce effective international governance measures.This research will compare governance regimes of the air, maritime, and internet domains to understand how stakeholders and international organisations approach governance of a global commons. Through the examination of the International Maritime Organization, International Civil Aviation Organization, and the multistakeholder group responsible for internet governance this research will draw insight into the organisational structures, processes, tools, and techniques that aid in the creation of international governance to inform new governance for space.Findings offer insight into the organisational qualities, governance tools, and necessary change needed to govern space more effectively. First, despite differences across case studies, there are key features of effective international governance present in each. Each system of governance is designed based on unique features and qualities of that domain and its stakeholders. Still, decision-making processes, membership participation, enforcement, and keeping pace with new technology all play central roles in effective international governance.Proper consensus decision-making can play an outsized role in whether a forum can advance governance or not. The case studies make clear that to properly use consensus as a decision-making approach requires thoughtful consideration of the increased transaction costs weighed against necessary agreement compliance. For example, not all governance outputs require a high degree of compliance to be effective and therefore do not justify higher transaction costs associated with strict consensus processes. Similarly, thoughtful use of consensus also requires evaluating where in the diplomatic process consensus is required. Not every diplomatic decision requires full consensus. Yet, COPUOS currently does not adjust its decision-making approach based on output or where in the diplomatic process it requires consensus, which has allowed the forum's use of consensus to hinder the development of new governance.Another finding is that strong governance leverages a multitude of governance tools. Treaties are an important governance measure, but so too are standards and recommended practices, guidelines, codes, performance-based measures, audit schemes, scoping exercises, and educational resources, among other tools. Many of the emerging space activities will continue to evolve quickly, which requires producing governance in a timely manner and continuous evolution of agreements. In each case study, evolving activities were governed by a spectrum of measures that allowed the IO to affect member behaviour quickly and overtime through complementary outputs.Each case study made clear that effective governance requires constant work across multiple workstreams, yet COPUOS is a small three body organisation with too few resources to increase work cadence or volume. A larger secretariat and the capacity to create new subcommittees or working groups is likely to aid space governance. COPUOS will require major changes to accommodate space governance needs. Finally, this research offers recommendations for future research capable of exploring additional possible solutions to existing space governance problems

An agent-based model for the sustainable management of navigation activities in the Saint Lawrence Estuary

Natural resource managers of protected areas are concerned with the management of human activities potentially harmful to ecosystems’ health and/or integrity. These systems where human interact with natural resources are called social-ecological systems (SES) and possess the characteristics of complex adaptive systems (e.g. co-evolution). The SES of navigation activities and whales interacting within the Saguenay–St. Lawrence Marine Park (SSLMP) and the projected St. Lawrence Estuary Marine Protected Area in Quebec, Canada, has been investigated and modelled using the agent-based modelling (ABM) technology: The resulting Marine Mammal and Maritime Traffic Simulator (3MTSim) is designed to support marine protected area managers in their effort to reduce the frequency and intensity of boat-whale co-occurrences within the St Lawrence Estuary and mitigate the risks of vessel strikes. This dissertation presents the building process of the 3MTSim’s boat ABM. The knowledge extracted from analyses of gathered and collected data relative to all forms of sailing and motorized navigation supported the decision to first focus on the modelling of commercial excursions (including whale-watching trips), cargo ships, and cruise liners. Data analyses allowed, for the first time, to draw a comprehensive portrait of navigation activities throughout the region where whales congregate in great numbers during the summer season. Among others, a quantitative analysis led to an accurate estimate of the total navigation time within each separate ecosystem of the region. This study identified areas intensively used by maritime traffic such as the mouth of the Saguenay River and offshore Les Escoumins. Several field campaigns carried out in the context of this project allowed to link some undesirable collective patterns of whale-watching excursions (regarding both whale conservation and SSLMP visitors’ experience) with contextual factors including whale species’ abundance and distribution, management gaps, and companies and captains’ decisions. The bounded rationality framework was chosen to investigate captains’ decision making and more generally the dynamics of the whole whale-watching SES. A portrait of the decision strategies followed by whale-watching captains has been drawn. The results will lead to a set of recommendations regarding the sustainable management of whale-watching excursions in and around the SSLMP. Results from field investigations and data analyses have fed the model building process, including an explicit representation of the whale-watching captains’ decision making. Data analyses revealed that cargo ships and ocean liners tend to follow predictable routes with low variability. Consequently, a complex behavioural modelling approach was deemed unnecessary in favour of a statistical approach, justified by the large volume of high-quality historical data available for both components. The pattern-oriented modelling approach proved appropriate for selecting a valid model of whale-watching excursions. Model simulations confirmed that whale-watching captains do favour the observation of a few rare rorqual species (e.g. humpback whales), leaving aside the most abundant one, namely the minke whales. Therefore, 3MTSim was run to quantify the impact that whale-watching captains changing their decision strategy could have on both whale exposure to boats (conservation concern) and excursion content (commercial concern). It was found that captains willing to avoid crowded observation sites and/or seeking to increase the diversity of species observed could have statistically significant benefits regarding conservation issues without affecting important features of their excursions. Finally, the convincing performance of the 3MTSim’s boat ABM ensures its safe use as a decision-support tool for management insofar as model limitations are understood and accounted for in the results and discussion

Methods for enhanced learning using wearable technologies. A study of the maritime sector

Maritime safety is a critical concern due to the potential for serious consequences or accidents for the crew, passengers, environment, and assets resulting from navigation errors or unsafe acts. Traditional training methods face challenges in the rapidly evolving maritime industry, and innovative training methods are being explored. This study explores the use of wearable sensors with biosignal data collection to improve training performance in the maritime sector. Three experiments were conducted progressively to investigate the relationship between navigators' experience levels and biosignal data results, the effects of different training methods on cognitive workload, trainees' stress levels, and their decision-making skills, and the classification of scenario complexity and the biosignal data obtained by the trainees. questionnaire data on stress levels, workload, and user satisfaction of auxiliary training equipment; performance evaluation data on navigational abilities, decision-making skills, and ship-handling abilities; and biosignal data, including electrodermal activity (EDA), body temperature, blood volume pulse (BVP), inter-beat interval (IBI), and heart rate (HR). Several statistical methods and machine-learning algorithms were used in the data analysis. The present dissertation contributes to the advancement of the field of maritime education and training by exploring methods for enhancing learning in complex situations. The use of biosignal data provides insights into the interplay between stress levels and training outcomes in the maritime industry. The proposed conceptual training model underscores the relationship between trainees' stress and safety factors and offers a framework for the development and evaluation of advanced biosignal data-based training systems

The Future of Ocean Governance and Capacity Development

The International Ocean Institute – Canada has compiled more than 80 insightful essays on the future of ocean governance and capacity development, based largely on themes of its Training Program at Dalhousie University in Canada, to honor the work of Elisabeth Mann Borgese (1918-2002). Readership: The essays cover a broad range of ocean governance and capacity development issues and explore future benefits and challenges. This essential collection is aimed at professionals, students and citizens alike