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Maritime Security and Risk Assessments—2nd Edition

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A Special Issue of Journal of Marine Science and Engineering (ISSN 2077-1312) belonging to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (5 May 2026) | Viewed by 21118

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Editors

Dr. Marko Perkovic

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Faculty of Maritime Studies and Transport, University of Ljubljana, 6320 Portorož, Slovenia
Interests: safety and security at sea; port and waterway design; VTS and remote sensing; ship handling and pilotage; MASS; maritime simulations
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Dr. Ivica Pavic

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Guest Editor

Faculty of Maritime Studies, University of Split, Split, Croatia
Interests: navigation; maritime safety; security; hydrographic engineering; naval science
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Dr. Andrej Androjna

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Guest Editor

Faculty of Maritime Studies and Transport, University of Ljubljana, 6320 Portorož, Slovenia
Interests: maritime policy; maritime security and safety; maritime cyber security; naval science
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Prof. Dr. Maciej Gucma

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Guest Editor

Navigation Department, Maritime University of Szczecin, Szczecin, Poland
Interests: sea navigation; risk; security; reliability; safety; marine operations; ocean engineering; process safety; LNG transport; gas handling; port design
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Dr. Sebastian Feuerstack

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Guest Editor

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
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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. A particularly topical issue recently has been the navigation of ships through hazardous areas where AIS systems and navigation radars are switched off for safety reasons and where electromagnetic radiation may be visible to missiles and drones.

With this Special Issue, we are seeking 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 the submission of high-quality papers presenting new research and case studies in the field of maritime safety, security, and risk in general.

Dr. Marko Perkovič
Prof. Dr. Ivica Pavić
Dr. Andrej Androjna
Prof. Dr. Maciej 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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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 semimonthly 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

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Published Papers (12 papers)

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Research

29 pages, 3006 KB

Open AccessFeature PaperArticle

An Integrated Framework of Association Rules and Social Network Analysis for Exploring Co-Occurrence Patterns of Waterborne Accident Causes

by Luqian Zhang, Ruiwen Zhang, Weiliang Qiao, Bing Han and Xiaoxue Ma

J. Mar. Sci. Eng. 2026, 14(15), 1410; https://doi.org/10.3390/jmse14151410 - 31 Jul 2026

Viewed by 451

Abstract

Accident cause analysis is widely valued by the International Maritime Organization (IMO) and many maritime authorities to prevent waterborne transportation accidents. In this study, 886 waterborne transportation accident investigation reports from China MSA are collected. Contributing factor analysis sections are extracted and imported into NVIVO for directed content coding, which combines the HFACS framework and grounded theory coding. In total, all contributing factors are identified, conceptualized, and categorized into 76 sub-categories across five dimensions. Based on these, association rule analysis is conducted separately for seven accident types to mine corresponding strong association rules. Meanwhile, an undirected co-occurrence social network is constructed with all accident samples and analyzed from three dimensions: connection strength, criticality, and activeness. Multi-dimensional network structure analysis shows that external influence accident causes do not rank among the top nodes across all indicators. Within the scope of this study, the contributing factor co-occurrence network presents a closed-like structural feature dominated by internal factors. “Failure to identify risks timely and take effective measures” and “Incompetent crew” are identified as two core nodes with outstanding comprehensive performance across multiple indicators. In addition, nodes with prominent local co-occurrence aggregation characteristics are also identified through clustering coefficient analysis. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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39 pages, 3635 KB

Open AccessArticle

Toward Standardized Benchmarking of Search-Based Scenario Selection Methods in Autonomous System Validation

by Daniel Autenrieth, Daniel Paland, Jan Mentjes and Adrian Zlocki

J. Mar. Sci. Eng. 2026, 14(15), 1386; https://doi.org/10.3390/jmse14151386 - 29 Jul 2026

Viewed by 491

Abstract

Autonomous systems must demonstrate reliable safety and robustness even under rare, safety-critical conditions. Because the vast range of possible operating situations cannot be exhaustively tested, scenario-based testing has emerged as a structured approach to expose systems to representative and challenging situations. Search-based scenario selection methods (SBSSMs) algorithmically explore the scenario space to identify critical and informative cases. Yet, existing implementations are often tightly coupled to specific domains and simulation environments, hindering reproducibility, comparability, and generalizability across application areas. This paper introduces a benchmarking framework that addresses these limitations by providing a domain-independent environment for the systematic evaluation of SBSSMs. Building on empirical observations from maritime simulation studies and the literature, the framework generates synthetic test instances that mimic the structural patterns found there while abstracting away application-specific semantics. It supplies standardized performance metrics and reference implementations of key method classes, enabling direct comparison of new approaches with established ones under controlled, repeatable conditions. Illustrative demonstrations show how the benchmark reveals characteristic strengths and weaknesses of different methods across diverse structural settings. As a reproducible and extensible baseline, the framework promotes standardized performance assessment and the transfer of methodological advances from maritime navigation to domains such as automotive safety. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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25 pages, 2209 KB

Open AccessArticle

Optimisation of Nautical Anchorages: A Six-Method Hybrid Approach

by Danijel Pušić, Zvonimir Lušić and Mario Bakota

J. Mar. Sci. Eng. 2026, 14(14), 1267; https://doi.org/10.3390/jmse14141267 - 9 Jul 2026

Viewed by 387

Abstract

The increasing complexity of marine spatial management and the rapid growth of nautical tourism require the use of formal and transparent decision-making models. Identifying optimal locations for nautical anchorages is a multi-criteria decision problem (MCDP) in which navigation safety, spatial constraints, and environmental protection often conflict. This study presents an integrated framework combining Geographic Information Systems (GIS) and multi-criteria decision-making (MCDM) methods for the systematic evaluation and ranking of nautical anchorages. As a case study, 86 potential locations in Split-Dalmatia County, Croatia, were analysed based on 18 criteria encompassing hydrological, meteorological, and spatial factors, as well as risk factors relevant to navigation safety. The methodological approach applies six MCDM methods implemented in the R programming language: Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), ViseKriterijska Optimizacija I Kompromisno Rjesenje (VIKOR), Multi-Objective Optimisation on the Basis of Ratio Analysis (MOORA), Complex Proportional Assessment (COPRAS), Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS), and Evaluation Based on Distance from Average Solution (EDAS). To reduce methodological bias, a final Consensus rank was calculated to synthesise the results of all applied methods. The stability of the obtained ranking was examined through an analysis of rank agreement between methods, using a diagonal matrix of rank overlaps and the corresponding heatmap visualisation. The results indicate a high level of consistency among individual MCDM methods and strong stability of the final consensus ranking. The proposed model ranks locations from best to worst based on how well they meet the established criteria, while ensuring strict navigational safety and compliance with environmental constraints. These findings confirm that the integrated GIS–MCDM approach is a reliable, repeatable, and scientifically grounded tool for supporting spatial planning and concession allocation in the development of nautical infrastructure. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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32 pages, 1937 KB

Open AccessArticle

An Integrated MMEM-FTA Approach for Causal Analysis of Ship Collisions: A Case Study of Taizhou Coastal Waters

by Yanfei Tian, Qi He, Ke Zhang and Wuliu Tian

J. Mar. Sci. Eng. 2026, 14(13), 1146; https://doi.org/10.3390/jmse14131146 - 23 Jun 2026

Viewed by 420

Abstract

It is of great significance for accident prevention to explore the causes and evolution laws of ship collisions at sea. The paper aims to constructs a systematic MMEM-FTA integrated analysis framework and applies the framework to analyze the causes of ship collisions in Taizhou coastal waters. Ship collision cases in Taizhou coastal waters from 2017 to 2025 are collected, and a statistical analysis is conducted on the characteristics of collision accidents. Under the MMEM frame, 16 accident influencing factors are identified from four aspects: personnel negligence, ship failure, management failure and environmental degradation. Based on FTA, a fault tree diagram of ship collision accidents in Taizhou coastal waters is constructed. Results of both quantitative and quantitative analysis show that the structural importance of ship failure, management failure and complex environment is the largest and an event with higher probabilistic and critical importance is “Unseaworthiness.” These mentioned events are main reasons for ship collision accidents. Suggestions on risk control options (RCOs) for accident prevention are put forward under the MMEM frame. The proposed MMEM-FTA integrated analysis framework is feasible for accident causation analysis. This research can provide theoretical and practical supports for identifying causes of ship collisions, for elucidating the evolution mechanism of accidents and for taking targeted measures to prevent accidental risks. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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27 pages, 1532 KB

Open AccessArticle

Assessing the Resilience of Specialized Terminals Within Coastal Port Transportation Systems: An Improved RBOP Method

by Qi Tian, Kun Du and Yumei Liang

J. Mar. Sci. Eng. 2025, 13(12), 2382; https://doi.org/10.3390/jmse13122382 - 16 Dec 2025

Viewed by 633

Abstract

Specialized terminals in coastal ports play an increasingly important role in maritime transport. To enhance the resilience of specialized terminals, it is vital to increase their ability to maintain a certain level of function under various emergencies. This effort is fundamental to ensuring the handling efficiency of coastal ports and the stability of the shipping network. In this paper, from the perspective of the coastal port transportation system, we developed a resilience evaluation framework considering micro-level, meso-level, and macro-level influencing factors on specialized terminals. To evaluate the comprehensive resilience of the specialized terminal, we quantitatively calculated each evaluation indicator and proposed an improved Ranking Based on Optimal Points (RBOP) method. The application results were obtained from a study on specialized container terminals at eight hub ports in coastal China. The improved RBOP method takes into account both the current status and future development trends of specialized terminals. As a result, compared with TOPSIS, VIKOR, Multi-MOORA, and WASPAS, the ranking results of the improved RBOP and the latest method (i.e., WASPAS) are the closest, which only differ in the seventh and eighth ranking, while the outcomes of the improved RBOP align more closely with expert expectations. The proposed method enables the resilience evaluation of specialized terminals from a holistic perspective of the coastal port transportation system. This helps port managers identify bottlenecks in the resilience of specialized terminals and can enhance the efficiency and stability of port operations. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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31 pages, 11336 KB

Open AccessArticle

Collision Avoidance Pattern with Collective Wisdom: Ship Action Decision-Making Azimuth Map Construction Based on COLREGs

by Ziwei Wang, Fei Shao, Chong Zhang, Hongchu Yu, Shuzhe Chen and Lei Wu

J. Mar. Sci. Eng. 2025, 13(12), 2240; https://doi.org/10.3390/jmse13122240 - 24 Nov 2025

Cited by 3 | Viewed by 1303

Abstract

Ship collision avoidance decision-making is a core determinant of navigational safety, and its effectiveness directly governs a ship’s ability to operate safely in a complex environment. Although successive editions of the COLREGs have provided a relatively systematic qualitative description of the principal encounter state and corresponding handling principles, they still lack a quantitative specification of collision avoidance actions. As a result, ship officers must rely heavily on experiential judgment for state recognition and decision-making in real operations, which in turn increases the likelihood of human error-induced failures in avoidance. To address this problem, this study constructs a COLREG-compliant collision avoidance decision azimuth map derived from the collective wisdom of ship officers. Specifically, a two-stage mining process tailored to large-scale AIS data is designed: in the first stage, ship–ship encounter cases are extracted from the full dataset, and, in the second stage, collision avoidance actions are mined from these encounter cases. Subsequently, a decision tree classification model is employed to partition the latent relationships between the relative motion features of two ships and their collision avoidance actions under different encounter scenarios, thereby constructing a data-driven ship collision avoidance decision azimuth map. Finally, taking the eastern coastal waters of China as a case study, the constructed ship collision avoidance action azimuth map is shown to provide scenario-specific guidance for two-ship encounters, offer an objective basis for the quantitative enrichment of COLREGs, and supply a methodological reference for future autonomous ship collision avoidance systems. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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32 pages, 12619 KB

Open AccessArticle

Investigating Impacts of Risk Influence Factors on the Consequences of Marine Accidents in China by SE-CNN-GRU Algorithm

by Xiaofeng Wang, Enze Huang and Weiliang Qiao

J. Mar. Sci. Eng. 2025, 13(11), 2169; https://doi.org/10.3390/jmse13112169 - 17 Nov 2025

Cited by 1 | Viewed by 986

Abstract

Marine shipping safety is of great concern to many stakeholders, especially maritime authorities, and the consequences of marine accidents, linked to the accident severity and type, are intrinsically impacted by various risk influence factors (RIFs). To investigate the impacts of RIFs on marine accidents and the consequences thereof within Chinese waters, in this study, 1106 marine accident investigation reports issued by China’s MSA during the 2013–2024 period were collected, and a database of marine shipping RIFs was developed based on these data. As a result, 14 typical features were extracted, and the accident severity level and accident type were set as the output features. Then, a comprehensive machine learning algorithm integrating squeeze-and-excitation (SE), a convolutional neural network (CNN), and a gated recurrent unit (GRU) was proposed to process the extracted marine RIFs. Finally, these features were analyzed in terms of importance, correlation, and partial dependence plots (PDPs), and the performance of the SE-CNN-GRU algorithm, especially the prediction accuracy, was verified. The findings and results obtained from this study are valuable for improving shipping safety in Chinese waters; managerial implications are additionally proposed. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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30 pages, 1809 KB

Open AccessArticle

Safety of LNG-Fuelled Cruise Ships in Comparative Risk Assessment

by Elvis Čapalija, Peter Vidmar and Marko Perkovič

J. Mar. Sci. Eng. 2025, 13(10), 1896; https://doi.org/10.3390/jmse13101896 - 2 Oct 2025

Cited by 6 | Viewed by 4335

Abstract

Although liquefied natural gas (LNG) is already widely used as a marine fuel, its use on large cruise ships is a relatively new development. By the end of 2024, twenty-four LNG-fuelled cruise ships were in operation, each carrying several thousand passengers and making frequent port calls. These operational characteristics increase the potential risks compared to conventional cargo ships and require a rigorous safety assessment. In this study, the safety of LNG-fuelled cruise ships is assessed using the Formal Safety Assessment (FSA) framework prescribed by the International Maritime Organization (IMO). The assessment includes a hazard identification (HAZID), a risk analysis, an evaluation of risk control options, a cost–benefit analysis and recommendations for decision-making. Given the limited operational data on LNG-fuelled cruise ships, event trees are developed on the basis of LNG tanker incidents, adjusted to reflect passenger-related risks and cruise-specific operating conditions. A statistical overview of marine casualties involving cruise ships and LNG carriers of more than 20,000 GT over the last 35 years provides a further basis for the analysis. To ensure compliance, the study also analyses class requirements and regulatory frameworks, including risk assessments for ship design, bunker operations and emergency preparedness. These assessments, which are carried out at component, ship and process level, remain essential for safety validation and regulatory approval. The results provide a comprehensive framework for assessing LNG safety in the cruise sector by combining existing safety data, regulatory standards and probabilistic risk modelling. Recent work also confirms that event tree modelling identifies critical accident escalation pathways, particularly in scenarios involving passenger evacuation and port operations, which are under-researched in current practice. The results contribute to the wider debate on alternative fuels and support evidence-based decision-making by ship operators, regulators and industry stakeholders. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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36 pages, 7335 KB

Open AccessArticle

COLREGs-Compliant Distributed Stochastic Search Algorithm for Multi-Ship Collision Avoidance

by Bohan Zhang, Jinichi Koue, Tenda Okimoto and Katsutoshi Hirayama

J. Mar. Sci. Eng. 2025, 13(8), 1402; https://doi.org/10.3390/jmse13081402 - 23 Jul 2025

Cited by 3 | Viewed by 2179

Abstract

The increasing complexity of maritime traffic imposes growing demands on the safety and rationality of ship-collision-avoidance decisions. While most existing research focuses on simple encounter scenarios, autonomous collision-avoidance strategies that comply with the International Regulations for Preventing Collisions at Sea (COLREGs) in complex multi-ship environments remain insufficiently investigated. To address this gap, this study proposes a novel collision-avoidance framework that integrates a quantitative COLREGs analysis with a distributed stochastic search mechanism. The framework consists of three core components: encounter identification, safety assessment, and stage classification. A cost function is employed to balance safety, COLREGs compliance, and navigational efficiency, incorporating a distance-based weighting factor to modulate the influence of each target vessel. The use of a distributed stochastic search algorithm enables decentralized decision-making through localized information sharing and probabilistic updates. Extensive simulations conducted across a variety of scenarios demonstrate that the proposed method can rapidly generate effective collision-avoidance strategies that fully comply with COLREGs. Comprehensive evaluations in terms of safety, navigational efficiency, COLREGs adherence, and real-time computational performance further validate the method’s strong adaptability and its promising potential for practical application in complex multi-ship environments. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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40 pages, 13106 KB

Open AccessArticle

A Novel Time-Frame Regional Collision Risk Model Based on Dynamic Time Warping

by Zihao Liu and Peijun Yu

J. Mar. Sci. Eng. 2025, 13(2), 263; https://doi.org/10.3390/jmse13020263 - 30 Jan 2025

Cited by 3 | Viewed by 1697

Abstract

The quantification of collision risk in the water area is crucial for marine traffic safety. However, most existing studies primarily adopt a statistical perspective or only consider collision risks at discrete time points, neglecting the dynamic nature and temporal characteristics of collision risk. To overcome the problem, this paper proposed a novel time-frame regional collision risk model based on dynamic time warping (DTW). The time series of the ships in the water area were generated by modeling the collision risk from the perspectives of geometric encounters and traffic situation pressure. Dynamic time warping was used to mine the eigenvalue of each sequence in representing collision risk. The time-frame regional collision risk can be obtained by synthesizing the collision risk eigenvalues through considering the contribution of each ship to the entire collision risk. To validate the proposed model, some experiments were carried out by using the real AIS data in the Bohai Strait. The results show the capability of the proposed model in reasonably and effectively identifying the time-frame regional collision risk and prove its merits compared with the traditional methods. Therefore, it can better assist the supervision and analysis of regional collision risk so as to further enhance marine traffic safety. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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16 pages, 4610 KB

Open AccessArticle

Using the Bayes Probability Model to Evaluate the Risk of Accidents Caused by the Electronic Chart Display and Information System

by Lea Vojković, Mario Bakota and Ana Kuzmanić Skelin

J. Mar. Sci. Eng. 2024, 12(8), 1391; https://doi.org/10.3390/jmse12081391 - 14 Aug 2024

Cited by 2 | Viewed by 2230

Abstract

The obligated implementation of the Electronic Chart Display and Information System (ECDIS) began ten years ago, and during this time, we could observe different types of familiarization with the system through its users. The incorrect use of the ECDIS is a problem recognized by the International Hydrographic Organization (IHO), and it is caused by disparate levels of education and the quality of courses. Another aspect of the recognized problem is the unequal length of the ECDIS specific course training period through which users acquire type-specific familiarization with the system. Switching between different types of ECDISs makes users more prone to errors until they become fully familiar with the new product system. This paper analyzes seafarers’ knowledge and ECDIS usage over a 6-year period. Based on obtained data, models that enable risk analysis based on conditional probability were created. This paper presents the use of Bayesian modeling to reduce errors in maritime accidents caused by inadequate use of the ECDIS. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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20 pages, 9503 KB

Open AccessArticle

Manipulation-Compliant Artificial Potential Field and Deep Q-Network: Large Ships Path Planning Based on Deep Reinforcement Learning and Artificial Potential Field

by Weifeng Xu, Xiang Zhu, Xiaori Gao, Xiaoyong Li, Jianping Cao, Xiaoli Ren and Chengcheng Shao

J. Mar. Sci. Eng. 2024, 12(8), 1334; https://doi.org/10.3390/jmse12081334 - 6 Aug 2024

Cited by 15 | Viewed by 3221

Abstract

Enhancing the path planning capabilities of ships is crucial for ensuring navigation safety, saving time, and reducing energy consumption in complex maritime environments. Traditional methods, reliant on static algorithms and singular models, are frequently limited by the physical constraints of ships, such as turning radius, and struggle to adapt to the maritime environment’s variability and emergencies. The development of reinforcement learning has introduced new methods and perspectives to path planning by addressing complex environments, achieving multi-objective optimization, and enhancing autonomous learning and adaptability, significantly improving the performance and application scope. In this study, we introduce a two-stage path planning approach for large ships named MAPF–DQN, combining Manipulation-Compliant Artificial Potential Field (MAPF) with Deep Q-Network (DQN). In the first stage, we improve the reward function in DQN by integrating the artificial potential field method and use a time-varying greedy algorithm to search for paths. In the second stage, we use the nonlinear Nomoto model for path smoothing to enhance maneuverability. To validate the performance and effectiveness of the algorithm, we conducted extensive experiments using the model of “Yupeng” ship. Case studies and experimental results demonstrate that the MAPF–DQN algorithm can find paths that closely match the actual trajectory under normal environmental conditions and U-shaped obstacles. In summary, the MAPF–DQN algorithm not only enhances the efficiency of path planning for large ships, but also finds relatively safe and maneuverable routes, which are of great significance for maritime activities. Full article

(This article belongs to the Special Issue Maritime Security and Risk Assessments—2nd Edition)

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