Special Issue "Maritime Safety"

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: 15 April 2020.

Special Issue Editors

Prof. Dr. Young-Soo Park
E-Mail Website
Guest Editor
Korea Maritime and Ocean University, Division of Maritime Transportation Science, Busan, South Korea
Interests: Marine Traffic Risk Assessment, Marine Traffic Engineering, Vessel Traffic Service Assessment, Collision Avoidance System, Ship Route Design
Dr. Volkan Aydogdu
E-Mail Website
Guest Editor
Carnival Maritime
Interests: navigational safety; maritime traffic management; e-nav; MASS; maritime safety
Prof. Jungsik Jeong
E-Mail Website
Guest Editor
Mokpo National Maritime University
Interests: Intelligent Navigation, Collision Avoidance, Maritime Information System

Special Issue Information

Dear Colleagues,

After the disastrous event of M/V Titanic, many concerns regarding maritime safety have arisen, and the discussion continuous on to this day. The reason why safety of maritime is so important today, is because most trade is done through shipping of materials by ships, and the safety of it cannot be ignored. Thus, safety on water has been a big issue for decades.

Due to advances in technology today, new developments such as Smart ship, Vessel Traffic Service technology, e-navigation technology, and MASS(Maritime Autonomous Surface Ship) have been achieved. But regardless of how innovative these developments are, they should also be considered for safety on water. In case of MASS, the level of safety around ships was previously determined by humans, but the actor for determination would be change to computers now. Therefore, basic data accumulation and research on maritime safety are essential factors to take into account.

We have chosen “Maritime Safety” as the special issue. This issue invites researchers and scientist involved in related studies to step forward with their research and share their findings and opinions with the vast audience.

Prof. Dr. Young-Soo Park
Dr. Volkan Aydogdu
Prof. Jungsik Jeong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Navigational Risk Assessment
  • Maritime Traffic Engineering
  • Vessel Traffic Service
  • Local maritime traffic management
  • E-Navigation and training needs
  • Navigation Decision Support System
  • MASS and Human factor
  • Ship route design
  • Marine accident

Published Papers (5 papers)

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Research

Open AccessArticle
Collision Prevention Algorithm for Fishing Vessels Using mmWAVE Communication
J. Mar. Sci. Eng. 2020, 8(2), 115; https://doi.org/10.3390/jmse8020115 - 13 Feb 2020
Abstract
This study leveraged the millimeter wireless access in vehicular environments (mmWAVE) communication technology to reflect the maneuvering characteristics of small fishing vessels and constructed a collision prevention algorithm that can be applied relatively easily. The algorithm was verified through simulation and actual ship [...] Read more.
This study leveraged the millimeter wireless access in vehicular environments (mmWAVE) communication technology to reflect the maneuvering characteristics of small fishing vessels and constructed a collision prevention algorithm that can be applied relatively easily. The algorithm was verified through simulation and actual ship experiments. The algorithm had four components: detection of vessels within three miles; identification of dangerous vessels by applying the time to the closest point of approach (TCPA) and distance at the closest point of approach (DCPA) criteria; continuous monitoring of maritime traffic risk; and incremental alarm signaling. The simulations and experiments confirmed that the alarm was generated incrementally in accordance with the distance to a dangerous situation, with no false alarms. Thus, the proposed algorithm offers potential to enhance the safety of small fishing vessels. Full article
(This article belongs to the Special Issue Maritime Safety)
Open AccessArticle
Detection of Small Ship Objects Using Anchor Boxes Cluster and Feature Pyramid Network Model for SAR Imagery
J. Mar. Sci. Eng. 2020, 8(2), 112; https://doi.org/10.3390/jmse8020112 - 12 Feb 2020
Abstract
The synthetic aperture radar (SAR) has a special ability to detect objects in any climate and weather conditions. Consequently, SAR images are widely used in maritime transportation safety and fishery law enforcement for maritime object detection. Currently, deep-learning models are being extensively used [...] Read more.
The synthetic aperture radar (SAR) has a special ability to detect objects in any climate and weather conditions. Consequently, SAR images are widely used in maritime transportation safety and fishery law enforcement for maritime object detection. Currently, deep-learning models are being extensively used for the detection of objects from images. Among them, the feature pyramid network (FPN) uses pyramids for representing semantic information regardless of the scale and has an improved accuracy of object detection. It is also suitable for the detection of multiple small ship objects in SAR images. This study aims to resolve the problems associated with small-object and multi-object ship detection in complex scenarios e.g., when a ship nears the port, by proposing a detection method based on an optimized FPN model. The feature pyramid model is first embedded in a traditional region proposal network (RPN) and mapped into a new feature space for object identification. Subsequently, the k-means clustering algorithm based on the shape similar distance (SSD) measure is used to optimize the FPN. Initial anchor boxes and tests are created using the SAR ship dataset. Experimental results show that the proposed algorithm for object detection shows an accuracy of 98.62%. Compared with Yolo, the RPN based on VGG/ResNet, FPN based on VGG/ResNet, and other models in complex scenarios, the proposed model shows a higher accuracy rate and better overall performance. Full article
(This article belongs to the Special Issue Maritime Safety)
Open AccessArticle
A Computational Approach to the Prediction of the Floating Condition of ROPAX Vessel after Firewater Accumulation in Firefighting Operation
J. Mar. Sci. Eng. 2020, 8(1), 30; https://doi.org/10.3390/jmse8010030 - 09 Jan 2020
Abstract
A reliable estimation of the floating condition of a roll on/roll off cargo (ROPAX) vessel after the accumulation of firewater on the vehicle deck is extremely important for making correct decisions on evacuation and abandonment. Thus, for the seafarer working on a ROPAX [...] Read more.
A reliable estimation of the floating condition of a roll on/roll off cargo (ROPAX) vessel after the accumulation of firewater on the vehicle deck is extremely important for making correct decisions on evacuation and abandonment. Thus, for the seafarer working on a ROPAX vessel, there is a demand for a time-dependent prediction of the floating condition of the vessel after the firewater accumulation. For this purpose, a new iterative computational approach, based on quasi-static theory, is presented. The approach is examined through the records observed in an accident of the M/V Dashun. The results show that the approach has good accuracy and feasibility provided that the actual heeling angle and cargo shift during the accident are carefully monitored. Full article
(This article belongs to the Special Issue Maritime Safety)
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Open AccessArticle
An Improved Ship Collision Risk Evaluation Method for Korea Maritime Safety Audit Considering Traffic Flow Characteristics
J. Mar. Sci. Eng. 2019, 7(12), 448; https://doi.org/10.3390/jmse7120448 - 07 Dec 2019
Abstract
Ship collision accidents account for the majority of marine accidents. The collision risk can be even greater in ports where the traffic density is high and terrain conditions are difficult. The proximity assessment model of the Korea Maritime Safety Audit (KMSA), which is [...] Read more.
Ship collision accidents account for the majority of marine accidents. The collision risk can be even greater in ports where the traffic density is high and terrain conditions are difficult. The proximity assessment model of the Korea Maritime Safety Audit (KMSA), which is a tool for improving maritime traffic safety, employs a normal distribution of ship traffic to calculate the ship collision risk. However, ship traffic characteristics can differ according to the characteristics of the sea area and shipping route. Therefore, this study simulates collision probabilities by estimating the best-fit distribution function of ship traffic flow in Ulsan Port, which is the largest hazardous cargo vessel handling port in Korea. A comparison of collision probability simulation results using the best-fit function and the normal distribution function reveals a difference of approximately 1.5–2.4 times for each route. Moreover, the collision probability estimates are not accurate when the normal distribution function is uniformly applied without considering the characteristics of each route. These findings can be used to improve the KMSA evaluation method for ship collision risks, particularly in hazardous port areas. Full article
(This article belongs to the Special Issue Maritime Safety)
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Open AccessArticle
Investigation of Oil Spills from Oil Tankers through Grey Theory: Events from 1974 to 2016
J. Mar. Sci. Eng. 2019, 7(10), 373; https://doi.org/10.3390/jmse7100373 - 19 Oct 2019
Abstract
An oil spill from a vessel is a critical maritime accident that can severely damage the environment. In this study; we utilize the basic construction of grey relational analysis to explore oil spill events statistics from 1974 to 2015 and successfully analyze the [...] Read more.
An oil spill from a vessel is a critical maritime accident that can severely damage the environment. In this study; we utilize the basic construction of grey relational analysis to explore oil spill events statistics from 1974 to 2015 and successfully analyze the causes of incidents in 2016. The results illustrate that grey relational analysis effectively identifies the factors causing oil spills with an accuracy of over 96%. The research is aimed to reduce the marine accidents and predict the cause of oil spill in advance. The analysis is dealing with the incidents to approach the circumstance in various intensity of oil spill in the last 40 years. Moreover, an application of grey theory demonstrates accurate and reliable methodology to decision maker. Thus, the investigation can predict the causes of pollution from oil spill accidents in the future. Full article
(This article belongs to the Special Issue Maritime Safety)
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