A Study of the Application Barriers to the Use of Autonomous Ships Posed by the Good Seamanship Requirement of COLREGs

Zhou, Xiangyu; Huang, Jinjing; Wang, Fengwu; Wu, Zedong; Liu, Zhengjiang

doi:10.1017/s0373463319000924

Cited by 49 publications

(31 citation statements)

References 28 publications

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“…A position paper by CMI (2018) describes the relationship between MASS and Rule 2 as follows: 'Autonomous and unsupervised ships, however, would fall foul of Rule 2 in its current form.' Further, Zhou et al (2020) state, 'In summary, this rule requires human intervention for decision making. Theoretically, the remote-controlled mode can still meet the safety requirements, but further revisions may be necessary to resolve the barriers to actual application for fully autonomous mode.…”

Section: Seamanship and Massmentioning

confidence: 99%

“…Other examples of previous research indicate the need for further amendments/revisions to COLREGs with regard to the operation of MASS. According to Zhou et al (2020), in order to solve the problem of misinterpretation of COLREGs, amendment of the ‘look-out’ rule (COLREGs Rule 5) is needed to permit watch keeping solely via ‘computer vision’ alone. Other research on this topic carried out by Porathe (2019) indicates that AI may actually become more proficient than humans, so the software installed on MASS should focus on behaving in a more humanlike manner.…”

Section: Review Of Literaturementioning

confidence: 99%

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Rules required for operating maritime autonomous surface ships from the viewpoint of seafarers

et al. 2022

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Demonstrations and local tests of several maritime autonomous surface ships (MASS) have recently been carried out. From a technological standpoint, MASS are becoming able to handle actual operations in certain sea areas. Since 2017, the MSC (Maritime Safety Committee) of the IMO (International Maritime Organization) has been discussing legal problems with the Regulations for Preventing Collisions at Sea (COLREGs) with regard to MASS operation. The purpose of this paper is to clarify the rules from the perspective of seafarers, who need to interpret COLREGs when dealing with MASS in ship handling situations on the sea, and also to discuss possible required amendments to COLREGs. This paper attempts to clarify the extent of current interpretations while also taking into account the answers to questionnaires received from 130 pilots, ship captains and navigation officers concerning COLREGs for MASS operation. Given the four common principles of COLREGs, it is considered whether the principles need to be changed with the introduction of MASS from the viewpoint of seafarers.

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Section: Seamanship and Massmentioning

confidence: 99%

Section: Review Of Literaturementioning

confidence: 99%

Rules required for operating maritime autonomous surface ships from the viewpoint of seafarers

et al. 2022

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“…The DNSD was formed by fully considering the expansion effect of various factors on the BNSD. In the relative researches, scholars generally use the method of fuzzy mathematics and membership function [22,33,[43][44][45] to study the influence of various factors on navigation safety. In this paper, the influence of each factor on the NSD was given by an extension function.…”

Section: Construction Of the Dynamic Navigation Safety Domainmentioning

confidence: 99%

A COLREGs-Based Dynamic Navigation Safety Domain for Unmanned Surface Vehicles: A Case Study of Dolphin-I

Zhou

Wang

Zhang

2020

JMSE

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Unmanned Surface Vehicles (USVs) are intelligent machines that have been widely studied in recent years. The safety of USVs’ activities is a priority issue in their applications; one effective method is to delimit an exclusive safety domain around the USV. Besides considering collision avoidance, the safety domain should satisfy the requirements of encounter situations in the COLREGs (International Regulations for Preventing Collisions at Sea) as well. Whereas the model providing the safety domain for the USVs is defined through the experience of the manned ships, a specific model for USVs has been rarely studied. A dynamic navigation safety domain (DNSD) for USVs was proposed in this paper. To construct the model, the essential factors that could affect the navigation safety of the USVs were extracted via a rough set, and the extension functions of these factors were carried out. The DNSD was employed in various situations and compared with the ship domain models of common ships. It was found that the domain boundary can be automatically corrected according to the change in the working conditions when the DNSD is in use. Compared with the Fujii and Coldwell models, the DNSD can provide a larger safety area for a USV’s action of collision avoidance.

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“…With the limitation of the seafarer's lookout at the ship bridge, the visual perception of the horizon cannot be done excluding the solar direction [3] and bad weather often affects the seafarer's judgment. Most collisions and grounding are due to wrong interpretation or disregard of improper lookout (COLREGS-1972) [4].…”

Section: Introductionmentioning

confidence: 99%

Survey on Deep Learning-Based Marine Object Detection

Zhang

et al. 2021

Journal of Advanced Transportation

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We present a survey on marine object detection based on deep neural network approaches, which are state-of-the-art approaches for the development of autonomous ship navigation, maritime surveillance, shipping management, and other intelligent transportation system applications in the future. The fundamental task of maritime transportation surveillance and autonomous ship navigation is to construct a reachable visual perception system that requires high efficiency and high accuracy of marine object detection. Therefore, high-performance deep learning-based algorithms and high-quality marine-related datasets need to be summarized. This survey focuses on summarizing the methods and application scenarios of maritime object detection, analyzes the characteristics of different marine-related datasets, highlights the marine detection application of the YOLO series model, and also discusses the current limitations of object detection based on deep learning and possible breakthrough directions. The large-scale, multiscenario industrialized neural network training is an indispensable link to solve the practical application of marine object detection. A widely accepted and standardized large-scale marine object verification dataset should be proposed.

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A Study of the Application Barriers to the Use of Autonomous Ships Posed by the Good Seamanship Requirement of COLREGs

Cited by 49 publications

References 28 publications

Rules required for operating maritime autonomous surface ships from the viewpoint of seafarers

Rules required for operating maritime autonomous surface ships from the viewpoint of seafarers

A COLREGs-Based Dynamic Navigation Safety Domain for Unmanned Surface Vehicles: A Case Study of Dolphin-I

Survey on Deep Learning-Based Marine Object Detection

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