Addressing the Accidental Risks of Maritime Transportation: Could Autonomous Shipping Technology Improve the Statistics?

Hoem, Åsa Snilstveit; Fjørtoft, Kay Endre; Rødseth, Ørnulf Jan

doi:10.12716/1001.13.03.01

Cited by 17 publications

(5 citation statements)

References 10 publications

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“…Works [10,11] consider in detail the errors of operations on board the ship: operations on board the ship are the main factor contributing to 70 % of accidents. However, it is important to consider that these mistakes can be caused not only by technical shortcomings but also by motivational factors of the captains.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Devising an approach to safety management of vessel control through the identification of navigator’s state

Nosov,

Koretsky,

Zinchenko

et al. 2023

EEJET

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The object of this study is the processes of automated management of maritime safety by analyzing the manifestations of the human factor of sea navigators. The task solved is justified by the need for formal and logical analysis and intelligent identification of mental motivational states (MMS) of marine navigators whose actions can cause dangerous situations during the control of the ship’s movement. High accident rates due to the fault of the navigators, in the absence of automated means of monitoring their condition, cause a contradiction between the existing means of safety control in controlling the movement of the vessel and the modern requirements of navigation, which needs to be resolved. A safety management approach was devised that takes into account the specificity of navigational tasks and the p-adic classification of dangerous MMS for navigators. This has made it possible to create three security modes that are activated depending on the detected state of the navigator’s MMS. Features of the results are the combination of analysis by means of p-adic systems and intelligent methods of data processing. As a result, sufficient identification accuracy was obtained for more than 75 % of MMS through neural network training. Experimental data collected during the navigation watch, as well as on the Navi Trainer 5000 navigation simulator (Wärtsilä Corporation, Finland), became the basis for simulation by means of neural networks. In turn, the training of neural networks made it possible to obtain sufficient identification accuracy by performing up to 3000 iterations. Overall, the learning rate of the neural network was 0.98, which indicates a high level of identification. From a practical point of view, the results could be used for the automated management of shipping safety, as well as for evaluating the level of adaptation of the navigator to dynamically changing conditions. The proposed approach provides opportunities for the application of modern intelligent technologies in the field of maritime transport safety, namely artificial neural network tools that determine notification modes or activation of automatic ship traffic control modules. The specified contradiction requires the design of specialized systems for automated safety management of ship traffic control based on the identified states of navigators

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Devising an approach to safety management of vessel control through the identification of navigator’s state

Nosov,

Koretsky,

Zinchenko

et al. 2023

EEJET

View full text Add to dashboard Cite

show abstract

“…MASS is still in an early stage of development, so there are still uncertainties surrounding their operation making, it difficult to predict the likelihood and types of failure that might occur (de Vos et al, 2021; Hoem et al, 2019) It is important to consider the potential of maritime incidents due to the introduction of MASS (de Vos et al, 2021; Hoem et al, 2019). It has been suggested that the use of uncrewed MASS will reduce the likelihood of collisions occurring, but the severity of these accidents may be higher due to the limited recovery capability if there is no longer any crew on board (Thieme et al, 2018; Wróbel et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

The application of a system‐based risk management framework and social network analysis to the Maritime Autonomous Surface Ship system: Who are the decision‐makers in the wider system?

Lynch

Banks

Roberts

et al. 2023

Hum Ftrs & Erg Mfg Svc

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Maritime Autonomous Surface Ships (MASS) currently have no formal regulations developed specifically for their operation, as their regulatory framework is still under development. Rasmussen's Risk Management Framework has been used to develop an actor map of the current MASS system in the UK, to show who the actors, decision‐makers, and planners are within the wider sociotechnical system and the level at which they sit. From the actor map, two social networks were created, one to show the connections that currently exist between the actors within the MASS system and another to show what a future MASS system could look like if regulations and standards were put in place for MASS. Social Network Analysis was then used to investigate the wider MASS system's dynamics, to understand which actors currently have a high degree of influence within the UK MASS system, and where the shortfalls are in the current MASS system. The analysis showed that the industry and end user levels lacked support from the higher system levels, and the addition of formal regulations and standards in the future MASS system would increase the MASS system's resilience. System recommendations for each level in the Risk Management Framework were then made to suggest ways to increase the influence of the regulators and promote the safe operation of MASS.

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“…Nowadays, shipping is an international business that employs some 1.6 million seafarers (UNCTAD 2019) and carries around 90% of global freight (Oksavik et al 2020). However, it is often postulated that the safety and efficiency of the industry could be improved by removing humans from the direct loop (Wróbel et al 2017;Hoem et al 2019). Accordingly, automated ocean-going merchant vessels, also known as Maritime Autonomous Surface Ships (MASSs) (IMO MSC 2018) would navigate the sea either completely without human supervision or under control from a distant land-based facility, sometimes referred to as a shore control center (SCC) (Størkersen 2021;Ramos et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Implications of autonomous shipping for maritime education and training: the cadet’s perspective

et al. 2022

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The Industrial Revolution 4.0 has not left the transportation sector behind. All modes of transportation have, to some extent, already been affected, and maritime is the last to join them. Currently available technology makes autonomous merchant ships a possible alternative to conventional, manned vessels with seafarers. This upcoming shift requires the preparation of necessary policies, such as rethinking obsolete training curricula, in relation to a variety of aspects of the industry, including the future of seafaring as a profession. To formulate such policies, the views of professional seafarers and scholars are sometimes solicited, but the opinions of industry entrants are often neglected. However, the latter may also have some interesting views on the future of their profession, which may be relevant to policy-makers. The results of a worldwide survey, conducted using the Computer-Assisted Web Interviewing (CAWI) method, suggest that the future generation of seafarers fears automation less than their mentors. Although they expect their skills to be useful in automation-driven shipping, they also feel that their Maritime Education and Training institutions (MET) are not doing enough to prepare them for the challenges that the future may hold. This may be due to a lack or poor coverage of shipping autonomization issues in MET curricula, which was mentioned by as many as 41.9% of the respondents. This finding advocates for rethinking the curricula of METs and human resources management in the shipping industry of the future.

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Addressing the Accidental Risks of Maritime Transportation: Could Autonomous Shipping Technology Improve the Statistics?

Cited by 17 publications

References 10 publications

Devising an approach to safety management of vessel control through the identification of navigator’s state

Devising an approach to safety management of vessel control through the identification of navigator’s state

The application of a system‐based risk management framework and social network analysis to the Maritime Autonomous Surface Ship system: Who are the decision‐makers in the wider system?

Implications of autonomous shipping for maritime education and training: the cadet’s perspective

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