Maritime Security and Risk Assessments

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 (1 October 2023) | Viewed by 26169

Special Issue Editors

Faculty of Navigation, Maritime University of Szczecin, 70-500 Szczecin, Poland
Interests: maritime traffic engineering; risk assessment of maritime systems; ship navigational systems
Special Issues, Collections and Topics in MDPI journals
German Aerospace Center (DLR), Institute of Systems Engineering for Future Mobility, Escherweg 2, 26121 Oldenburg, Germany
Interests: safety engineering methods; classification of automated and assisted maritime systems; maritime traffic management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Maritime transport is relatively safe and clean, but intensive and costly efforts are required to maintain this status. Because of continuing technological advances, the operation of systems aboard commercial vessels is becoming more specialized and complex. The development of automated systems to monitor, analyze, and regulate the various operations or services on board relies on the use of computer applications to centralize and optimize decision-making. Such systems are highly vulnerable to cyberattacks. In addition, crew downsizing and the general trend of reducing the number of people on ships are being implemented on a large scale. In some ports, pilotage services are already being performed remotely. Recently, the first LNG ship sailed autonomously across the ocean, and various maritime universities are already preparing for the new era of seafarers who will remotely monitor and control the navigation and propulsion elements of ships. There are many technical and regulatory challenges, such as the robustness and resilience of autonomous navigation technology, onboard systems, communications, shore traffic management, piracy, and cybersecurity; additionally, ports are a key element in the maritime transport chain that are also vulnerable to cyberattacks. In addition, larger ships and higher traffic volumes at ports can lead to higher risks at the shipping level.

We seek contributions that address theoretical and technical challenges (as well as best practices) that promote potential solutions for maritime risk mitigation. Beyond the scientific interest of various studies and the technical task of proposing new measures to improve maritime safety in the face of challenges uninvited by ports, we would like this Special Issue to relate to current issues in general, such as the role of seafarers in autonomous shipping and related training issues.

We are seeking high-quality papers presenting new research and case studies in the field of maritime safety, security and risk in general.

Dr. Marko Perkovic
Prof. Dr. Lucjan Gucma
Dr. Sebastian Feuerstack
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

  • maritime cyber risk and security
  • safety of navigation
  • threat modeling
  • maritime risk management
  • VTS systems
  • e-navigation
  • pilotage
  • remote pilotage
  • large ship berthing operations
  • navigation in narrow and restricted areas
  • port risk assessment
  • autonomous vessels
  • education and training

Related Special Issue

Published Papers (16 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Review, Other

21 pages, 9162 KiB  
Article
AIS Data Manipulation in the Illicit Global Oil Trade
by Andrej Androjna, Ivica Pavić, Lucjan Gucma, Peter Vidmar and Marko Perkovič
J. Mar. Sci. Eng. 2024, 12(1), 6; https://doi.org/10.3390/jmse12010006 - 19 Dec 2023
Viewed by 977
Abstract
This article takes a close look at the landscape of global navigation satellite system (GNSS) spoofing. It is well known that automated identification system (AIS) spoofing can be used for electronic warfare to conceal military activities in sensitive sea areas; however, recent events [...] Read more.
This article takes a close look at the landscape of global navigation satellite system (GNSS) spoofing. It is well known that automated identification system (AIS) spoofing can be used for electronic warfare to conceal military activities in sensitive sea areas; however, recent events suggest that there is a similar interest of spoofing AIS signals for commercial purposes. The shipping industry is currently experiencing an unprecedented period of deceptive practices by tanker operators seeking to evade sanctions. Last year’s announcement of a price cap on Russian crude oil and a new ban on Western companies insuring Russian cargoes is setting the stage for an increase in illegal activity. Our research team identified and documented the AIS position falsification by tankers transporting Russian crude oil in closed ship-to-ship (STS) oil transfers. The identification of the falsified positions is based on the repeated instances of discrepancies between AIS location suggestions and satellite radar imagery indications. Using the data methods at our disposal, we reconstructed the true movements of certain tankers and encountered some surprising behavior. These false ship positions make it clear that we need effective tools and strategies to ensure the reliability and robustness of AISs. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

27 pages, 11220 KiB  
Article
A Contextually Supported Abnormality Detector for Maritime Trajectories
by Kristoffer Vinther Olesen, Ahcène Boubekki, Michael C. Kampffmeyer, Robert Jenssen, Anders Nymark Christensen, Sune Hørlück and Line H. Clemmensen
J. Mar. Sci. Eng. 2023, 11(11), 2085; https://doi.org/10.3390/jmse11112085 - 31 Oct 2023
Viewed by 863
Abstract
The analysis of maritime traffic patterns for safety and security purposes is increasing in importance and, hence, Vessel Traffic Service operators need efficient and contextualized tools for the detection of abnormal maritime behavior. Current models lack interpretability and contextualization of their predictions and [...] Read more.
The analysis of maritime traffic patterns for safety and security purposes is increasing in importance and, hence, Vessel Traffic Service operators need efficient and contextualized tools for the detection of abnormal maritime behavior. Current models lack interpretability and contextualization of their predictions and are generally not quantitatively evaluated on a large annotated dataset comprising all expected traffic in a Region of Interest. We propose a model for the detection of abnormal maritime behaviors that provides the closest behaviors as context to the predictions. The normalcy model relies on two-step clustering, which is first computed based on the positions of the vessels and then refined based on their kinematics. We design for each step a similarity measure, which combined are able to distinguish boats cruising shipping lanes in different directions, but also vessels with more freedom, such as pilot boats. Our proposed abnormality detection model achieved, on a large annotated dataset extracted from AIS logs that we publish, an ROC-AUC of 0.79, which is on a par with State-of-the-Art deep neural networks, while being more computationally efficient and more interpretable, thanks to the contextualization offered by our two-step clustering. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

22 pages, 5006 KiB  
Article
A Decision Support System Using Fuzzy Logic for Collision Avoidance in Multi-Vessel Situations at Sea
by Tanja Brcko and Blaž Luin
J. Mar. Sci. Eng. 2023, 11(9), 1819; https://doi.org/10.3390/jmse11091819 - 18 Sep 2023
Viewed by 1272
Abstract
The increasing traffic and complexity of navigation at sea require advanced decision support systems to ensure greater safety. In this study, we propose a novel decision support system that employs fuzzy logic to improve situational awareness and to assist navigators in collision avoidance [...] Read more.
The increasing traffic and complexity of navigation at sea require advanced decision support systems to ensure greater safety. In this study, we propose a novel decision support system that employs fuzzy logic to improve situational awareness and to assist navigators in collision avoidance during multi-vessel encounters. The system is based on the integration of the rules of the Convention on International Regulations for Preventing Collisions at Sea (COLREGs) and artificial intelligence techniques. The proposed decision model consists of two main modules to calculate the initial encounter conditions for the target vessels, evaluate the collision risk and navigation situation based on COLREG rules, sort the target vessels, and determine the most dangerous vessel. Fuzzy logic is used to calculate the collision avoidance maneuver for the selected ship, considering the closest point of approach, relative bearing, and the ship’s own speed. Simulation tests demonstrate the effectiveness of the fuzzy-based decision model in scenarios with two ships. However, in complex situations with multiple ships, the performance of the model is affected by possible conflicts between evasive maneuvers. This highlights the need for a cooperative collision avoidance algorithm for all vessels in high traffic areas. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

21 pages, 6706 KiB  
Article
An Analytic Model for Identifying Real-Time Anchorage Collision Risk Based on AIS Data
by Zihao Liu, Dan Zhou, Zhongyi Zheng, Zhaolin Wu and Longhui Gang
J. Mar. Sci. Eng. 2023, 11(8), 1553; https://doi.org/10.3390/jmse11081553 - 05 Aug 2023
Viewed by 919
Abstract
With the increasing volume of ship traffic, maritime traffic safety is facing a great challenge because the traffic in port becomes more and more crowded and complicated, which will make ship collisions more likely to happen. As a special water area of the [...] Read more.
With the increasing volume of ship traffic, maritime traffic safety is facing a great challenge because the traffic in port becomes more and more crowded and complicated, which will make ship collisions more likely to happen. As a special water area of the port, the anchorage is also threatened by collision risk all the time. For accurately assessing the collision risk in anchorage and its adjacent waters in real time, this paper proposed an analytic model based on Automatic Identification System (AIS) data. The proposed anchorage collision risk model was established in microscopic, macroscopic, and complexity aspects, which considered ship relative motion, anchorage characteristics, and ship traffic complexity, respectively. For validation, the AIS data of the anchorages near the Shandong Peninsular were used to carry out a series of experiments. The results show that the proposed model can identify the anchorage collision risk effectively and has an advantage in dealing with complicated scenarios. The proposed anchorage collision risk model can help maritime surveillance better monitor and organize the ship traffic near the port and provide mariners with a reference about the collision risk situation of the anchorage on their route, which are important to improving maritime traffic safety. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

17 pages, 3674 KiB  
Article
Exploring the Pirate Attack Process Risk along the Maritime Silk Road via Dynamic Bayesian Network Analysis
by Xiaoyue Hu, Haibo Xia, Shaoyong Xuan and Shenping Hu
J. Mar. Sci. Eng. 2023, 11(7), 1430; https://doi.org/10.3390/jmse11071430 - 17 Jul 2023
Cited by 3 | Viewed by 1282
Abstract
The Maritime Silk Road (MSR) is an important channel for maritime trade between China and other countries in the world. Maritime piracy has brought huge security risks to ships’ navigation and has seriously threatened the lives and property of crew members. To reduce [...] Read more.
The Maritime Silk Road (MSR) is an important channel for maritime trade between China and other countries in the world. Maritime piracy has brought huge security risks to ships’ navigation and has seriously threatened the lives and property of crew members. To reduce the likelihood of attacks from pirates, it is necessary to study the risk to a ship exposed to attacks from pirates on the MSR. Firstly, risk factors were established from three risk component categories (hazard, mitigation capacity, and vulnerability and exposure) and the risk index system of piracy and armed robbery events was founded. Secondly, the dynamic Bayesian network (DBN) method was introduced to establish a pirate attack risk assessment model ad to conduct a quantitative analysis of the process risk of a ship being attacked by pirates. Finally, combined with the scene data of the MSR, the process risk of a ship being attacked by pirates was modeled and applied as an example. The results showed that the overall risk of a ship being attacked by pirates is the lowest in July and the highest in March. In the whole route, when the ship was in the Gulf of Guinea, the Gulf of Aden–Arabian Sea, and the Strait of Malacca, the risk of pirate attack was the highest. This dynamic network model can effectively analyze the level of risk of pirate attacks on ships, providing a reference for the safety decision-making of ships on ocean routes. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

15 pages, 3817 KiB  
Article
A Network Model for Identifying Key Causal Factors of Ship Collision
by Jianzhou Liu, Huaiwei Zhu, Chaoxu Yang and Tian Chai
J. Mar. Sci. Eng. 2023, 11(5), 982; https://doi.org/10.3390/jmse11050982 - 05 May 2023
Viewed by 1137
Abstract
In the analysis of the causes of ship collisions, the identification of key causal factors can help maritime authorities to provide targeted safety management solutions, which is of great significance to the prevention of ship collisions. In order to identify the key causal [...] Read more.
In the analysis of the causes of ship collisions, the identification of key causal factors can help maritime authorities to provide targeted safety management solutions, which is of great significance to the prevention of ship collisions. In order to identify the key causal factors leading to ship collisions, we first construct a network model of ship collisions, in which the nodes represent the causal factors, and the edges represent the interrelationship between the causal factors. Second, based on the constructed network model, we propose a successive safety analysis method. This method can quantify the importance of each causal factor, and the quantified results allow us to identify the key causal factors of ship collisions. Finally, we verify the validity of the model using numerical cases. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

14 pages, 2667 KiB  
Article
Evaluating the Vulnerability of YOLOv5 to Adversarial Attacks for Enhanced Cybersecurity in MASS
by Changui Lee and Seojeong Lee
J. Mar. Sci. Eng. 2023, 11(5), 947; https://doi.org/10.3390/jmse11050947 - 28 Apr 2023
Cited by 1 | Viewed by 2049
Abstract
The development of artificial intelligence (AI) technologies, such as machine learning algorithms, computer vision systems, and sensors, has allowed maritime autonomous surface ships (MASS) to navigate, detect and avoid obstacles, and make real-time decisions based on their environment. Despite the benefits of AI [...] Read more.
The development of artificial intelligence (AI) technologies, such as machine learning algorithms, computer vision systems, and sensors, has allowed maritime autonomous surface ships (MASS) to navigate, detect and avoid obstacles, and make real-time decisions based on their environment. Despite the benefits of AI in MASS, its potential security threats must be considered. An adversarial attack is a security threat that involves manipulating the training data of a model to compromise its accuracy and reliability. This study focuses on security threats faced by a deep neural network-based object classification algorithm, particularly you only look once version 5 (YOLOv5), which is a model used for object classification. We performed transfer learning on YOLOv5 and tested various adversarial attack methods. We conducted experiments using four types of adversarial attack methods and parameter changes to determine the attacks that could be detrimental to YOLOv5. Through this study, we aim to raise awareness of the vulnerability of AI algorithms for object detection to adversarial attacks and emphasize the need for efforts to overcome them; these efforts can contribute to safe navigation in MASS. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

22 pages, 3408 KiB  
Article
Detecting Maritime GPS Spoofing Attacks Based on NMEA Sentence Integrity Monitoring
by Julian Spravil, Christian Hemminghaus, Merlin von Rechenberg, Elmar Padilla and Jan Bauer
J. Mar. Sci. Eng. 2023, 11(5), 928; https://doi.org/10.3390/jmse11050928 - 26 Apr 2023
Cited by 3 | Viewed by 2722
Abstract
Today’s maritime transportation relies on global navigation satellite systems (GNSSs) for accurate navigation. The high-precision GNSS receivers on board modern vessels are often considered trustworthy. However, due to technological advances and malicious activities, this assumption is no longer always true. Numerous incidents of [...] Read more.
Today’s maritime transportation relies on global navigation satellite systems (GNSSs) for accurate navigation. The high-precision GNSS receivers on board modern vessels are often considered trustworthy. However, due to technological advances and malicious activities, this assumption is no longer always true. Numerous incidents of tampered GNSS signals have been reported. Furthermore, researchers have demonstrated that manipulations can be carried out even with inexpensive hardware and little expert knowledge, lowering the barrier for malicious attacks with far-reaching consequences. Hence, exclusive trust in GNSS is misplaced, and methods for reliable detection are urgently needed. However, many of the proposed solutions require expensive replacement of existing hardware. In this paper, therefore, we present MAritime Nmea-based Anomaly detection (MANA), a novel low-cost framework for GPS spoofing detection. MANA monitors NMEA-0183 data and advantageously combines several software-based methods. Using simulations supported by real-world experiments that generate an extensive dataset, we investigate our approach and finally evaluate its effectiveness. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

21 pages, 1965 KiB  
Article
Risk Assessment of Bauxite Maritime Logistics Based on Improved FMECA and Fuzzy Bayesian Network
by Jiachen Sun, Haiyan Wang and Mengmeng Wang
J. Mar. Sci. Eng. 2023, 11(4), 755; https://doi.org/10.3390/jmse11040755 - 31 Mar 2023
Viewed by 1439
Abstract
Because of the many limitations of the traditional failure mode effect and criticality analysis (FMECA), an integrated risk assessment model with improved FMECA, fuzzy Bayesian networks (FBN), and improved evidence reasoning (ER) is proposed. A new risk characterization parameter system is constructed in [...] Read more.
Because of the many limitations of the traditional failure mode effect and criticality analysis (FMECA), an integrated risk assessment model with improved FMECA, fuzzy Bayesian networks (FBN), and improved evidence reasoning (ER) is proposed. A new risk characterization parameter system is constructed in the model. A fuzzy rule base system based on the confidence structure is constructed by combining fuzzy set theory with expert knowledge, and BN reasoning technology is used to realize the importance ranking of the hazard degree of maritime logistics risk events. The improved ER based on weight distribution and matrix analysis can effectively integrate the results of risk event assessment and realize the hazard evaluation of the maritime logistics system from the overall perspective. The effectiveness and feasibility of the model are verified by carrying out a risk assessment on the maritime logistics of importing bauxite to China. The research results show that the priority of risk events in the maritime logistics of bauxite are “pirates or terrorist attacks” and “workers’ riots or strikes” in sequence. In addition, the bauxite maritime logistics system is at a medium- to high-risk level as a whole. The proposed model is expected to provide a systematic risk assessment model and framework for the engineering field. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

21 pages, 2048 KiB  
Article
Multi-Criteria Decision Analysis for Nautical Anchorage Selection
by Danijel Pušić and Zvonimir Lušić
J. Mar. Sci. Eng. 2023, 11(4), 728; https://doi.org/10.3390/jmse11040728 - 27 Mar 2023
Cited by 3 | Viewed by 1167
Abstract
Considering that moorings and anchorages for vessels have recently become an important factor in nautical tourism, the selection of their locations is a complex and demanding process. This paper examines numerous criteria from different perspectives to determine the most favourable/optimal locations for nautical [...] Read more.
Considering that moorings and anchorages for vessels have recently become an important factor in nautical tourism, the selection of their locations is a complex and demanding process. This paper examines numerous criteria from different perspectives to determine the most favourable/optimal locations for nautical anchorages, meeting the conditions and recommendations of professionals from several domains, by applying the methods of multi-criteria analysis. The goal of solving the problem this way is to meet the expectations of future users, spatial planners, possible investors, and concessionaires interested in doing business in these areas, as well as entities that strive to preserve and protect marine and underwater animal life and the environment by preventing their degradation and pollution. However, since there are no precisely defined recommendations for the establishment of nautical anchorages, in the procedures for determining the locations of nautical anchorages, it is possible to use general criteria they must fulfil. The best locations for nautical anchorages may be found, and this research represents a transparent, repeatable, and well-documented approach for methodically solving the problem. This is demonstrated by a comparison of many methods of multi-criteria analysis, utilizing a variety of parameters. On the other side, this calls for proficiency in a wide range of disciplines, including architecture, geodesy, marine safety and transport, architecture, biology, ecology, mathematical programming, operational research, information technology, environmental protection, and others. The best locations for nautical anchorages should be chosen based on the size and number of vessels, available space, depth, distance from the coast, level of protection of the anchorage waters, and many other limiting factors, keeping in mind that the spots which simultaneously satisfy a greater number of significant criteria are preferable. Using multi-criteria analysis methods (AHP (Analytical Hierarchy Process) and TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution)), evaluating and classifying criteria as well as assigning weight values to selected criteria, this paper investigates the possibility of obtaining the best locations from a group of possible ones. The most important factor when applying multi-criteria analysis methods refer to the following: vessel safety (navigation), hydrometeorological, spatial, economic, and environmental criteria. The main contribution of the paper displays in the proposal to optimize the decision-making process, when determining the optimal locations of nautical anchorages, in accordance with previously defined criteria. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

16 pages, 7760 KiB  
Article
Container Ship Fleet Route Evaluation and Similarity Measurement between Two Shipping Line Ports
by Davor Šakan, Srđan Žuškin, Igor Rudan and David Brčić
J. Mar. Sci. Eng. 2023, 11(2), 400; https://doi.org/10.3390/jmse11020400 - 11 Feb 2023
Cited by 1 | Viewed by 1937
Abstract
The characterization of ship routes and route similarity measurement based on Automatic Identification System (AIS) data are topics of various scientific interests. Common route research approaches use available AIS identifiers of ship types. However, assessing route and similarity profiles for individual fleets requires [...] Read more.
The characterization of ship routes and route similarity measurement based on Automatic Identification System (AIS) data are topics of various scientific interests. Common route research approaches use available AIS identifiers of ship types. However, assessing route and similarity profiles for individual fleets requires collecting data from secondary sources, dedicated software libraries or the creation of specific methods. Using an open-source approach, public AIS and ship data, we evaluate route characteristics for the container ships of a single fleet in a six-month period, calling on two selected ports of the shipping line on the USA East Coast. We evaluate the routes in terms of length, duration and speed, whereas for the similarity measurement we employ the discrete Fréchet distance (DFD). The voyage length, duration and average speed distributions were observed to be moderately positive (0.77), negative (−0.62), and highly positively skewed based on the adjusted Fisher–Pearson coefficient of skewness (1.23). The most similar voyages were from the same ships, with the lowest discrete Fréchet distance similarity value (0.9 NM), whereas 2 different ships had the most dissimilar voyages, with the highest DFD value (14.1 NM). The proposed methodology enables assessment of similarities between individual ships, or between fleets. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

14 pages, 952 KiB  
Article
Identifying the Most Probable Human Errors Influencing Maritime Safety
by Xiaofei Ma, Guoyou Shi, Weifeng Li and Jiahui Shi
J. Mar. Sci. Eng. 2023, 11(1), 14; https://doi.org/10.3390/jmse11010014 - 22 Dec 2022
Cited by 1 | Viewed by 1932
Abstract
In the traditional and extended shipboard operation human reliability analysis (SOHRA) model, the error-producing condition (EPC) is critical. The weight and proportion of each EPC in one specific task are often determined by the experts’ judgments, including most of the modified versions. Due [...] Read more.
In the traditional and extended shipboard operation human reliability analysis (SOHRA) model, the error-producing condition (EPC) is critical. The weight and proportion of each EPC in one specific task are often determined by the experts’ judgments, including most of the modified versions. Due to this subjectivity, the result and recommended safety measures may not be as accurate as they should be. This study attempts to narrow the gap by proposing a novel approach, a combination of SOHRA, entropy weight method, and the TOPSIS model. The entropy weight and TOPSIS method are employed to decide the weight of each EPC based on the foundation of the SOHRA model. A cargo-loading operation from a container ship is analyzed to verify this model. The results suggest that the entropy-weighted TOPSIS method can effectively determine the weights of EPCs, and the eight most probable human errors are identified. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

23 pages, 4137 KiB  
Article
Decentralized Documentation of Maritime Traffic Incidents to Support Conflict Resolution
by Dennis Jankowski, Julius Möller, Hilko Wiards and Axel Hahn
J. Mar. Sci. Eng. 2022, 10(12), 2011; https://doi.org/10.3390/jmse10122011 - 16 Dec 2022
Viewed by 1112
Abstract
For the investigation of major traffic accidents, larger vessels are obliged to install a voyage data recorder (VDR). However, not every vessel is equipped with a VDR, and the readout is often a manual process that is costly. In addition, not only ship-related [...] Read more.
For the investigation of major traffic accidents, larger vessels are obliged to install a voyage data recorder (VDR). However, not every vessel is equipped with a VDR, and the readout is often a manual process that is costly. In addition, not only ship-related information can be relevant for reconstructing traffic accidents, but also information from other entities such as meteorological services or port operators. Moreover, another major challenge is that entities tend to trust only their records, and not those of others as these could be manipulated in favor of the particular recording entity (e.g., to disguise any damage caused). This paper presents an approach to documenting arbitrary data from different entities in a trustworthy, decentralized, and tamper-proof manner to support the conflict resolution process. For this purpose, all involved entities in a traffic situation can contribute to the documentation by persisting their available data. Since maritime stakeholders are equipped with various sensors, a diverse and meaningful data foundation can be aggregated. The data is then signed by a mutually agreed upon timestamping authority (TSA). In this way, everyone can cryptographically verify whether the data has been subsequently changed. This approach was successfully applied in practice by documenting a vessel’s mooring maneuver. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

25 pages, 3726 KiB  
Article
A Molecular Dynamics Approach to Identify the Marine Traffic Complexity in a Waterway
by Zihao Liu, Zhaolin Wu, Zhongyi Zheng and Xianda Yu
J. Mar. Sci. Eng. 2022, 10(11), 1678; https://doi.org/10.3390/jmse10111678 - 07 Nov 2022
Cited by 2 | Viewed by 1192
Abstract
With the rapid development of the shipping industry in recent years, the increasing volume of ship traffic makes marine traffic much busier and more crowded, especially in the waterway off the coast. This leads to the increment of the complexity level of marine [...] Read more.
With the rapid development of the shipping industry in recent years, the increasing volume of ship traffic makes marine traffic much busier and more crowded, especially in the waterway off the coast. This leads to the increment of the complexity level of marine traffic and poses more threats to marine traffic safety. In order to study marine traffic safety under the conditions of increasing complexity, this article proposed a marine traffic complexity model based on the method in molecular dynamics. The model converted ship traffic to a particle system and identified the traffic complexity by analyzing the radial distribution of dynamic and spatial parameters of ships in a Euclid plane. The effectiveness of the proposed model had been validated by the case studies in the waters of Bohai Strait with real AIS (Automatic Identification System) data and simulated data. The results show that the proposed model can evaluate the marine traffic complexity more sufficiently and accurately. The proposed model is helpful for marine surveillance operators to monitor and organize marine traffic under complex situations so as to improve marine traffic safety. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

Review

Jump to: Research, Other

19 pages, 758 KiB  
Review
Maritime Anomaly Detection for Vessel Traffic Services: A Survey
by Thomas Stach, Yann Kinkel, Manfred Constapel and Hans-Christoph Burmeister
J. Mar. Sci. Eng. 2023, 11(6), 1174; https://doi.org/10.3390/jmse11061174 - 03 Jun 2023
Cited by 5 | Viewed by 2078
Abstract
A Vessel Traffic Service (VTS) plays a central role in maritime traffic safety. Regulations are given by the International Maritime Organization (IMO) and Guidelines by the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA). Accordingly, VTS facilities utilize communication and [...] Read more.
A Vessel Traffic Service (VTS) plays a central role in maritime traffic safety. Regulations are given by the International Maritime Organization (IMO) and Guidelines by the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA). Accordingly, VTS facilities utilize communication and sensor technologies such as an Automatic Identification System (AIS), radar, radio communication and others. Furthermore, VTS operators are motivated to apply Decision Support Tools (DST), since these can reduce workloads and increase safety. A promising type of DST is anomaly detection. This survey presents an overview of state-of-the-art approaches of anomaly detection for the surveillance of maritime traffic. The approaches are characterized in the context of VTS and, thus, most notably, sorted according to utilized communication and sensor technologies, addressed anomaly types and underlying detection techniques. On this basis, current trends as well as open research questions are deduced. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

Other

Jump to: Research, Review

15 pages, 8191 KiB  
Brief Report
Improving Maritime Domain Awareness in Brazil through Computer Vision Technology
by Matheus Emerick de Magalhães, Carlos Eduardo Barbosa, Kelli de Faria Cordeiro, Daysianne Kessy Mendes Isidorio and Jano Moreira de Souza
J. Mar. Sci. Eng. 2023, 11(7), 1272; https://doi.org/10.3390/jmse11071272 - 23 Jun 2023
Cited by 1 | Viewed by 1255
Abstract
This article discusses the Brazilian maritime authority’s efforts to monitor and control vessels in specific maritime areas using data from the naval traffic control system. Anomalies in vessel locations can signal security threats or illegal activities, such as drug trafficking and illegal fishing. [...] Read more.
This article discusses the Brazilian maritime authority’s efforts to monitor and control vessels in specific maritime areas using data from the naval traffic control system. Anomalies in vessel locations can signal security threats or illegal activities, such as drug trafficking and illegal fishing. A reliable Maritime Domain Awareness (MDA) is necessary to reduce such occurrences. This study proposes a data-driven framework, CV-MDA, which uses computer vision to enhance MDA. The approach integrates vessel records and camera images to create an annotated dataset for a Convolutional Neural Network (CNN) model. This solution supports detecting, classifying, and identifying small vessels without trackers or that have deliberately shut down their tracking systems in order to engage in illegal activities. Improving MDA could enhance maritime security, including identifying warships invading territorial waters and preventing illegal activities. Full article
(This article belongs to the Special Issue Maritime Security and Risk Assessments)
Show Figures

Figure 1

Back to TopTop