Submit to JMSE Review for JMSE Propose a Special Issue

Journal Menu

Journal Browser

Maritime Safety

Special Issue Editors
Special Issue Information
Keywords
Published Papers

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: closed (15 April 2020) | Viewed by 43079

Share This Special Issue

Special Issue Editors

Prof. Dr. Youngsoo Park

E-Mail Website
Guest Editor

Division of Maritime Transportation Sciences, Korea Maritime and Ocean University, Busan, Republic of Korea
Interests: ship collision avoidance; marine traffic safety
Special Issues, Collections and Topics in MDPI journals

Dr. Volkan Aydogdu

E-Mail Website
Guest Editor

Independent Researcher, Hamburg, Germany
Interests: maritime safety; navigational safety; maritime traffic management
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Jung Sik Jeong

E-Mail Website
Guest Editor

Department of Maritime Transportation Science, Mokpo National Maritime University, Mokpo, Republic of Korea
Interests: autonomous navigation; ship collision avoidance; ship route optimization
Special Issues, Collections and Topics in MDPI journals

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 submissions that pass pre-check are 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 2600 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 (12 papers)

Download All Papers

Research

20 pages, 5856 KiB

Open AccessArticle

Simulation Study of the IAMSAR Standard Recovery Maneuvers for the Improvement of Serviceability

by Inchul Kim, Chongju Chae and Soyeong Lee

J. Mar. Sci. Eng. 2020, 8(6), 445; https://doi.org/10.3390/jmse8060445 - 18 Jun 2020

Cited by 4 | Viewed by 5872

Abstract

Recovery maneuvers are highly important for rescuing a person overboard at sea. This is the prime reason why the International Maritime Organization (IMO) has published the International Aeronautical and Maritime Search and Rescue (IAMSAR) Manual III, which aims to assist vessels and aircrafts in the performance of a search, rescue, or on-scene co-ordinated efforts with aspects of search and rescue (SAR) which pertain to their own emergencies. The IAMSAR Manual III includes the Williamson turn, the Anderson turn and the Scharnov turn. Furthermore, the Lorén turn has been newly included in the 2019 edition of the Manual. Although several studies have pointed out that the Williamson turn needs to be applied in a modified form for proper application, in terms of returning ability to the original track line, it has not yet been modified in the Manual. Therefore, the purpose of this study is to analyze the serviceability of the four standard recovery maneuvers through a series of ship-handling simulations with representative types of ships. Our main results are as follows: firstly, the Anderson turn is the fastest recovery method, regardless of engine power and rudder efficiency; secondly, the actual paths of the Williamson turn are not consistent with the expected ones; and, finally, no correlations were found between the returning ability of the Williamson turn and any ship configuration or maneuvering ability factors, or their combinations. Thus, based on the experimental results, this paper proposes revising the descriptions of the standard recovery maneuvers and IMO regulations on ship maneuverability, as well as posting the actual tracks of the Williamson turn on the bridge in order to improve its serviceability. Full article

(This article belongs to the Special Issue Maritime Safety)

► Show Figures

Figure 1

19 pages, 4277 KiB

Open AccessArticle

Development of Machine Learning Strategy for Predicting the Risk Range of Ship’s Berthing Velocity

by Hyeong-Tak Lee, Jeong-Seok Lee, Woo-Ju Son and Ik-Soon Cho

J. Mar. Sci. Eng. 2020, 8(5), 376; https://doi.org/10.3390/jmse8050376 - 24 May 2020

Cited by 20 | Viewed by 3466

Abstract

Ships are prone to accidents when approaching in a berthing velocity greater than that allowed when determining the risk range corresponding to a port. Therefore, this study develops a machine learning strategy to predict the risk range of an unsafe berthing velocity when the ship approaches in port. To perform analysis, the input parameters were based on the factors affecting the berthing velocity, and the output parameter, i.e., the berthing velocity, was measured at a tanker terminal in the Republic of Korea. Nine machine learning classification algorithms were used to analyze each model, and the top four optimal models were selected through evaluation methods based on the confusion matrix. As a result of the analysis, extra trees, random forest, bagging, and gradient boosting classifiers were identified as good models. As a result of testing using the receiving operator characteristic curve, it was confirmed that the area under the curve of the most dangerous range of berthing velocity was the highest, thus, the risk range was appropriately classified. As such, the derived models can classify and predict the risk range of unsafe berthing velocity before approaching a port; therefore, it is possible to safely berth a ship. Full article

(This article belongs to the Special Issue Maritime Safety)

► Show Figures

Figure 1

20 pages, 8882 KiB

Open AccessArticle

Verification of Novel Maritime Route Extraction Using Kernel Density Estimation Analysis with Automatic Identification System Data

by Jeong-Seok Lee, Woo-Ju Son, Hyeong-Tak Lee and Ik-Soon Cho

J. Mar. Sci. Eng. 2020, 8(5), 375; https://doi.org/10.3390/jmse8050375 - 24 May 2020

Cited by 21 | Viewed by 3311

Abstract

A maritime route is used by sea transportation vessels to access the trading ports, and route design standards for the safety of maritime traffic have been established in various countries and organizations. However, no quantitative safety verification method related to route design currently exists. In this study, a novel maritime route was created and compared with the original route in Incheon, the Republic of Korea, based on the relevant automatic identification system (AIS) data. The attendant traffic density was revealed via kernel density estimation analysis of the AIS data, with the results used to create the boundary of the novel route through an image processing technique. The boundary and the centerline of the maritime route were determined using a line smoothing technique. For safety verification, the centerline of the original route and that of the novel maritime route were compared in terms of sinuosity, intersection angle, and route change envelope (RCE). The sinuosity analysis demonstrated that the route was stable in terms of the outer harbor limit, while the intersection angle analysis demonstrated that the novel maritime route intersection angle was stable. The RCE was used to objectively compare the absolute values of the distance change in the centerline. Full article

(This article belongs to the Special Issue Maritime Safety)

► Show Figures

Figure 1

24 pages, 369 KiB

Open AccessArticle

Analysis of Operational Efficiency Considering Safety Factors as an Undesirable Output for Coastal Ferry Operators in Korea

by Joohwan Kim, Gunwoo Lee and Hwayoung Kim

J. Mar. Sci. Eng. 2020, 8(5), 367; https://doi.org/10.3390/jmse8050367 - 22 May 2020

Cited by 4 | Viewed by 3106

Abstract

In the maritime transportation services industry, marine accidents may lead to fatalities, injuries, and property losses. Coastal ferry operators experience marine accidents and must pay attention to safety to guarantee the sustainability of their business. This study is aimed at analyzing the operational efficiency of coastal ferry operators in Korea from a safety perspective. We designed two slack-based measure of efficiency (SBM) models. One is a normal SBM, which includes only the total passenger volume as the desirable output. The other is a safety-constrained SBM, which includes marine accident records as an undesirable output with the desirable output of passenger transportation performance. We selected 44 coastal ferry operators in Korea that have been continuously operating for five years (2013–2017) as decision-making units (DMUs) and compared their operational efficiency scores. The results showed that the impact of marine accidents on business is greater in DMUs with lower transportation sales than in those with higher sales. This suggests that, while it is important for the government to strengthen safety regulations, a combination of policies that also help small ferry operators to stay in business in the long term is necessary to reduce marine accidents effectively while improving efficiency. Full article

(This article belongs to the Special Issue Maritime Safety)

17 pages, 6139 KiB

Open AccessArticle

A Novel Vision-Based Towing Angle Estimation for Maritime Towing Operations

by Xiong Zou, Wenqiang Zhan, Changshi Xiao, Chunhui Zhou, Qianqian Chen, Tiantian Yang and Xin Liu

J. Mar. Sci. Eng. 2020, 8(5), 356; https://doi.org/10.3390/jmse8050356 - 18 May 2020

Cited by 3 | Viewed by 2162

Abstract

The demand for non-powered facility towing is increasing with the development of large-scale offshore projects. It is of great interest for its safe operation to measure the state of the towing process in real time. This paper proposed a computer vision algorithm designed to measure the tug yawing during the towing operation by estimating the towing line angle. The geometrical projection of the towing line from 3D to 2D is described in detail. By fixing the camera at specific locations and simplifying the calculation procedure, the towing line angle in the 3D world can be estimated by the line angle in the image. Firstly, the sea–sky line is detected to estimate the rolling angle of the tug in the captured image. Then, the towing line angle is calculated by an image processing method. At the same time, the estimation of the towing angle is achieved through the captured video data analysis. Finally, field experiments were carried out and the results demonstrated that this method is suitable for real-time calculation of the towing angle during the towing operation. Full article

(This article belongs to the Special Issue Maritime Safety)

► Show Figures

Figure 1

22 pages, 7836 KiB

Open AccessArticle

An Investigation of the Ship Safety Distance for Bridges across Waterways Based on Traffic Distribution

by Woo-Ju Son, Jeong-Seok Lee, Hyeong-Tak Lee and Ik-Soon Cho

J. Mar. Sci. Eng. 2020, 8(5), 331; https://doi.org/10.3390/jmse8050331 - 8 May 2020

Cited by 15 | Viewed by 3255

Abstract

For ship passage safety, a bridge across a waterway is a risk for accidents. However, no standard for the safe distance between a bridge and a ship is available in Korea. The UK MCA considers the 90% confidence interval of traffic distribution as the acceptable passage range, using it for measuring the separation between offshore wind farms. In this study, an optimal ship safety distance is proposed by evaluating traffic distribution at the Incheon and Busan harbor bridges and analyzing the confidence intervals. The results, based on the Z-score, reveal that at the Incheon bridge, all but one ship for 2-way departure were in circulation within the 95% confidence interval range, whereas at the Busan harbor bridge, six ships for arrival and two ships for departure were outside the 95% range. Based on the results of this study, the design of bridges across waterways can incorporate traffic distribution corresponding to each port. Full article

(This article belongs to the Special Issue Maritime Safety)

► Show Figures

Figure 1

19 pages, 5864 KiB

Open AccessArticle

A Novel Framework of Real-Time Regional Collision Risk Prediction Based on the RNN Approach

by Dapei Liu, Xin Wang, Yao Cai, Zihao Liu and Zheng-Jiang Liu

J. Mar. Sci. Eng. 2020, 8(3), 224; https://doi.org/10.3390/jmse8030224 - 22 Mar 2020

Cited by 24 | Viewed by 3544

Abstract

Regional collision risk identification and prediction is important for traffic surveillance in maritime transportation. This study proposes a framework of real-time prediction for regional collision risk by combining Density-Based Spatial Clustering of Applications with Noise (DBSCAN) technique, Shapley value method and Recurrent Neural Network (RNN). Firstly, the DBSCAN technique is applied to cluster vessels in specific sea area. Then the regional collision risk is quantified by calculating the contribution of each vessel and each cluster with Shapley value method. Afterwards, the optimized RNN method is employed to predict the regional collision risk of specific seas in short time. As a result, the framework is able to determine and forecast the regional collision risk precisely. At last, a case study is carried out with actual Automatic Identification System (AIS) data, the results show that the proposed framework is an effective tool for regional collision risk identification and prediction. Full article

(This article belongs to the Special Issue Maritime Safety)

► Show Figures

Figure 1

18 pages, 4379 KiB

Open AccessArticle

Collision Prevention Algorithm for Fishing Vessels Using mmWAVE Communication

by Myoung-Ki Lee and Young-Soo Park

J. Mar. Sci. Eng. 2020, 8(2), 115; https://doi.org/10.3390/jmse8020115 - 13 Feb 2020

Cited by 10 | Viewed by 2611

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 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)

► Show Figures

Figure 1

13 pages, 2828 KiB

Open AccessArticle

Detection of Small Ship Objects Using Anchor Boxes Cluster and Feature Pyramid Network Model for SAR Imagery

by Peng Chen, Ying Li, Hui Zhou, Bingxin Liu and Peng Liu

J. Mar. Sci. Eng. 2020, 8(2), 112; https://doi.org/10.3390/jmse8020112 - 12 Feb 2020

Cited by 40 | Viewed by 3911

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 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)

► Show Figures

Figure 1

16 pages, 4413 KiB

Open AccessArticle

A Computational Approach to the Prediction of the Floating Condition of ROPAX Vessel after Firewater Accumulation in Firefighting Operation

by Honggui Wang and Zhaolin Wu

J. Mar. Sci. Eng. 2020, 8(1), 30; https://doi.org/10.3390/jmse8010030 - 9 Jan 2020

Cited by 2 | Viewed by 2952

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 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)

► Show Figures

Figure 1

16 pages, 7165 KiB

Open AccessArticle

An Improved Ship Collision Risk Evaluation Method for Korea Maritime Safety Audit Considering Traffic Flow Characteristics

by Yunja Yoo and Tae-Goun Kim

J. Mar. Sci. Eng. 2019, 7(12), 448; https://doi.org/10.3390/jmse7120448 - 7 Dec 2019

Cited by 16 | Viewed by 3922

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 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)

► Show Figures

Figure 1

14 pages, 745 KiB

Open AccessArticle

Investigation of Oil Spills from Oil Tankers through Grey Theory: Events from 1974 to 2016

by Dong-Taur Su, Fu-Ming Tzu and Chung-Hung Cheng

J. Mar. Sci. Eng. 2019, 7(10), 373; https://doi.org/10.3390/jmse7100373 - 19 Oct 2019

Cited by 13 | Viewed by 3577

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 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)

Journal Menu

Journal Browser

Maritime Safety

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (12 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI