A generic approach to analysing failures in human – System interaction in autonomy

Ramos, Marilia Abílio; Thieme, Christoph Alexander; Utne, Ingrid Bouwer; Mosleh, Ali

doi:10.1016/j.ssci.2020.104808

Cited by 37 publications

(15 citation statements)

References 52 publications

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“…Based on this data, an alerting system must be established in order to detect the conditions, their deterioration, and subsequently attract operators’ attention. 43,66–68 However, this will only be based on the data collected by the vessel itself and LPIs implemented therein. Interestingly, the papers focused on the perspective of shore-based centers are mainly concentrated on the collision avoidance issue.…”

Section: Resultsmentioning

confidence: 99%

On the use of leading safety indicators in maritime and their feasibility for Maritime Autonomous Surface Ships

Wróbel

Gil

Krata

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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Although the safety of prospective Maritime Autonomous Surface Ships will largely depend on their ability to detect potential hazards and react to them, the contemporary scientific literature lacks the analysis of how to achieve this. This could be achieved through an application of leading safety indicators. The aim of the performed study was to identify the research directions of leading safety indicators in three safety-critical operational aspects of Maritime Autonomous Surface Ships: collision avoidance, intact stability, and communication. To achieve this, literature review is performed, taking into account scientific documents including journal and conference papers. The results indicate that the need for establishing operational leading safety indicators is recognized by numerous scholars, who sometimes make suggestions of what the set of indicators shall consist of. Some leading safety indicators for autonomous vessels are readily identifiable in the scientific literature and used in current practice. However, the research effort is lacking a holistic approach to the issue.

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Section: Resultsmentioning

confidence: 99%

On the use of leading safety indicators in maritime and their feasibility for Maritime Autonomous Surface Ships

Wróbel

Gil

Krata

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…The system may operate within one LoA by design or adapt its LoA during operation based on external factors or as part of a troubleshooting mechanism. 18 Several LoAs have been proposed depending on the application or the purpose of the LoA classification (design, operation, human factors analysis, etc.). A review of several LoAs tables can be found at Vagia et al 19 One of the most well-known LoAs was developed for motor vehicles and by the SAE International, published at the ''Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles.''…”

Section: Safety Challenges Of Increasingly Autonomous Systemsmentioning

confidence: 99%

“…The system may operate within one LoA by design or adapt its LoA during operation based on external factors or as part of a troubleshooting mechanism. 18…”

Section: Autonomy and Aviation: History Levels Of Autonomy And Challe...mentioning

confidence: 99%

The need for and conceptual design of an AI model-based Integrated Flight Advisory System

Ramos

Sankaran

Guarro³

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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Automation and an increasing level of autonomy are not novelties in aircraft cockpits. One of the main goals of automation in aviation is to increase pilots’ situation awareness (SA) and reduce their workload – both of high importance for a safe flight. Increasing automation has historically reduced aviation accident rates and improved efficiency. Yet, currently implemented systems have also contributed to accidents, when failed, or were insufficient to increase pilots’ SA for improving their decision-making. This paper discusses the need for an enhanced decision-support system and its potential benefits for safer aviation. A model-based decision support system that leverages artificial intelligence, Integrated Flight Advisory System (IFAS), is presented. Further, the conceptual design of this system is described. The overview and roadmap provided in this paper consist of an effort toward a more holistic, pilot-centered, AI-based decision-support that can contribute to safer aviation.

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“…Academic interest in shore control of autonomous ships has increased in tandem with the growth of "Maritime 4.0." In the field of safety and risk science, researchers have examined the role of humans as safety controls in the operation of autonomous ships, applying advanced modelling techniques to predict how critical scenarios like collision avoidance will be coordinated [10][11][12][13][14]. Others have raised the challenges associated with human factors and training requirements of Shore Control Center Operators [15][16][17][18][19][20].…”

Section: State-of-the Art In Researchmentioning

confidence: 99%

NTNU Shore Control Lab: Designing shore control centres in the age of autonomous ships

Alsos

Veitch

Pantelatos

et al. 2022

J. Phys.: Conf. Ser.

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As highly automated ships become unmanned, their operators will move into shore-based control centers. In the last years, NTNU has built an advanced and flexible research infrastructure for performing research on autonomous ships and the monitoring and control of these. The infrastructure comprises of (1) the milliAmpere1 and milliAmpere2, which are two all-electric autonomous urban passenger ferries equipped with advanced sensors and equipment for autonomous navigation, (2) the Shore Control Lab, a flexible shore control center, where operators can monitor and control a fleet of autonomous ships, (3) a lab section for researchers to give instructions to operators in the control center, and to record, observe, and analyze their behavior, (4) an observation room adjacent to the control room for stakeholders to observe ongoing experiments in the control room, (5) the ferry simulator Autoferry Gemini that allows researchers to create challenging or high-risk scenarios where operators can be stress tested without being a danger to ship, crew and passengers, (6) the mixed reality lab MRLAB, where we can test physical designs of urban autonomous passenger ferries in a virtual environment, and (7) a dock for passenger handling and with inductive charging capabilities. In this paper, we first describe the research infrastructure’s purpose and scope of operation, as well as the technical design, physical setup, and equipment. Secondly, we present a roadmap for the development of the research infrastructure to meet the future research challenges for autonomous ships and the supervision and control of these. Thirdly, we present a number of research questions that are going to be explored in the lab in the years to come.

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A generic approach to analysing failures in human – System interaction in autonomy

Cited by 37 publications

References 52 publications

On the use of leading safety indicators in maritime and their feasibility for Maritime Autonomous Surface Ships

On the use of leading safety indicators in maritime and their feasibility for Maritime Autonomous Surface Ships

The need for and conceptual design of an AI model-based Integrated Flight Advisory System

NTNU Shore Control Lab: Designing shore control centres in the age of autonomous ships

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