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Recent Advances in Maritime Safety and Ship Collision Avoidance
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Recent Advances in Maritime Safety and Ship Collision Avoidance

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: 20 September 2025 | Viewed by 773

Special Issue Editors

Prof. Dr. Pengfei Chen

E-Mail Website
Guest Editor
School of Navigation, Wuhan University of Technology, Wuhan 430063, China
Interests: maritime safety; ship collision risk; risk analysis; autonomous ship; AIS; big data
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Junmin Mou

E-Mail Website
Guest Editor
Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology, Wuhan 430063, China
Interests: ocean engineering; AIS
Special Issues, Collections and Topics in MDPI journals
Dr. Lei Du

E-Mail Website
Guest Editor
School of Navigation, Wuhan University of Technology, Wuhan 430063, China
Interests: maritime traffic risk; evaluation of risk and safety of maritime transportation with respect to manned and unmanned vessels
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Safety is a continuous focus for the maritime transportation industry. With the recent development and recovery of the global economy, maritime transportation has been playing an increasingly crucial role in the global logistical network. In the meantime, maintaining the safety of maritime transportation and reducing the potential for accidents, are concerns that have seen increased attention from both industry and academia, especially with the occurrence of autonomous shipping and artificial intelligence.

The main goal of this Special Issue is to address the state-of-the-art development of the research on maritime safety and ship collision avoidance on various aspects: new concepts, methodologies, methods, models, and applications, etc. The topic of interest for this Special Issue includes, but is not limited to, the following aspects:

  • Literature review, bibliometric analysis, etc. on the research of maritime safety and ship collision avoidance.
  • New methods for ship collision risk modeling for the individual ship.
  • Risk-based decision-making, path planning, and collision avoidance for the individual ship.
  • Risk modeling and collision avoidance in complicated scenarios, e.g., inland navigation, multi-ship encounters, etc.
  • New methods and insights on regional ship collision risk analysis, modeling, and management.
  • The new method, insights, and models on causation analysis of ship collision accidents.
  • Ship collision avoidance research related to autonomous ships, e.g., autonomous collision avoidance, cooperative collision avoidance decision-making and control, etc.

Prof. Dr. Pengfei Chen
Prof. Dr. Junmin Mou
Dr. Lei Du
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 safety
  • risk analysis
  • collision avoidance
  • decision making
  • AIS
  • artificial intelligence
  • autonomous ship

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Published Papers (1 paper)

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Research

55 pages, 18379 KiB  
Article
Maritime Risk Assessment: A Cutting-Edge Hybrid Model Integrating Automated Machine Learning and Deep Learning with Hydrodynamic and Monte Carlo Simulations
by Egemen Ander Balas and Can Elmar Balas
J. Mar. Sci. Eng. 2025, 13(5), 939; https://doi.org/10.3390/jmse13050939 - 11 May 2025
Viewed by 327
Abstract
In this study, a Hybrid Maritime Risk Assessment Model (HMRA) integrating automated machine learning (AML) and deep learning (DL) with hydrodynamic and Monte Carlo simulations (MCS) was developed to assess maritime accident probabilities and risks. The machine learning models of Light Gradient Boosting [...] Read more.
In this study, a Hybrid Maritime Risk Assessment Model (HMRA) integrating automated machine learning (AML) and deep learning (DL) with hydrodynamic and Monte Carlo simulations (MCS) was developed to assess maritime accident probabilities and risks. The machine learning models of Light Gradient Boosting (LightGBM), XGBoost, Random Forest, and Multilayer Perceptron (MLP) were employed. Cross-validation of model architectures, calibrated baseline configurations, and hyperparameter optimization enabled predictive precision, producing generalizability. This hybrid model establishes a robust maritime accident probability prediction framework through a multi-stage methodology that ensembles learning architecture. The model was applied to İzmit Bay (in Türkiye), a highly jammed maritime area with dense traffic patterns, providing a complete methodology to evaluate and rank risk factors. This research improves maritime safety studies by developing an integrated, simulation-based decision-making model that supports risk assessment actions for policymakers and stakeholders in marine spatial planning (MSP). The potential spill of 20 barrels (bbl) from an accident between two tankers was simulated using the developed model, which interconnects HYDROTAM-3D and the MCS. The average accident probability in İzmit Bay was estimated to be 5.5 × 10−4 in the AML based MCS, with a probability range between 2.15 × 10−4 and 7.93 × 10−4. The order of the predictions’ magnitude was consistent with the Undersecretariat of the Maritime Affairs Search and Rescue Department accident data for İzmit Bay. The spill reaches the narrow strait of the inner basin in the first six hours. This study determines areas within the bay at high risk of accidents and advocates for establishing emergency response centers in these critical areas. Full article
(This article belongs to the Special Issue Recent Advances in Maritime Safety and Ship Collision Avoidance)
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