Research

15 pages, 2919 KiB

Open AccessArticle

A Simulation Model of the Influence of LNG Ships on Traffic Efficiency at Tianjin Port

by Yanwei Li, Wuliu Tian, Beibei Meng, Jinfen Zhang and Ruisai Zhou

J. Mar. Sci. Eng. 2024, 12(3), 405; https://doi.org/10.3390/jmse12030405 - 26 Feb 2024

Viewed by 551

Tianjin Port is one of the largest ports in northern China. Liquefied natural gas (LNG) ships are one of the most special ship types, and their navigation safety and efficiency has become the top concern of the port authority. There are two LNG [...] Read more.

Tianjin Port is one of the largest ports in northern China. Liquefied natural gas (LNG) ships are one of the most special ship types, and their navigation safety and efficiency has become the top concern of the port authority. There are two LNG berths at the port, and the annual arrivals, which reach more than 100, increasingly influence other ships. The objective of this study is to evaluate the influence of LNG ships on other ships in a quantitative way. To realize this, a simulation system is established by analyzing the factors affecting waterway transit efficiency. The software Arena is adopted to simulate the arrival and departure of the ships at Tianjin Port and to simulate how the average waiting time and the average queue length in the port area are affected by the LNG ships. A traffic system for the two ship types is formulated, and the mutual influences between them are expressed by the inbound and outbound waterway states. The simulations are performed under both existing and new ship traffic regulations. Cases in which the number of LNG ships gradually increases are simulated comprehensively. The simulation model as well as the results can serve as a good reference for the local port authority in the formulation of traffic regulations. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

20 pages, 2333 KiB

Open AccessArticle

Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data

by João N. Ribeiro da Silva, Tiago A. Santos and Angelo P. Teixeira

J. Mar. Sci. Eng. 2024, 12(2), 320; https://doi.org/10.3390/jmse12020320 - 13 Feb 2024

Viewed by 549

Abstract

This paper develops a methodology to estimate ship emissions using Automatic Identification System data (AIS). The methodology includes methods for AIS message decoding and ship emission estimation based on the ship’s technical and operational characteristics. A novel approach for ship type identification based [...] Read more.

This paper develops a methodology to estimate ship emissions using Automatic Identification System data (AIS). The methodology includes methods for AIS message decoding and ship emission estimation based on the ship’s technical and operational characteristics. A novel approach for ship type identification based on the visited port terminal is described. The methodology is implemented in a computational tool, SEA (Ship Emission Assessment). First, the accuracy of the method for ship type identification is assessed and then the methodology is validated by comparing its predictions with those of two other methodologies. The tool is applied to three case studies using AIS data of maritime traffic along the Portuguese coast and in the port of Lisbon for one month. The first case study compares the estimated emissions of a ferry and a cruise ship, with the ferry emitting much less than the cruise ship. The second case study estimates the geographical distribution of emissions in the port of Lisbon, with terminals corresponding to areas with a heavier concentration of exhaust emissions. The third case study focuses on the emissions from a container ship sailing along the continental coast of Portugal, differing considerably from port traffic since it operates exclusively in cruising mode. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

12 pages, 2163 KiB

Open AccessArticle

Distance Estimation Approach for Maritime Traffic Surveillance Using Instance Segmentation

by Miro Petković and Igor Vujović

J. Mar. Sci. Eng. 2024, 12(1), 78; https://doi.org/10.3390/jmse12010078 - 28 Dec 2023

Viewed by 791

Abstract

Maritime traffic monitoring systems are particularly important in Mediterranean ports, as they provide more comprehensive data collection compared to traditional systems such as the Automatic Identification System (AIS), which is not mandatory for all vessels. This paper improves the existing real-time maritime traffic [...] Read more.

Maritime traffic monitoring systems are particularly important in Mediterranean ports, as they provide more comprehensive data collection compared to traditional systems such as the Automatic Identification System (AIS), which is not mandatory for all vessels. This paper improves the existing real-time maritime traffic monitoring systems by introducing a distance estimation algorithm for monocular cameras, which aims to provide high quality maritime traffic metadata collection for traffic density analysis. Two distance estimation methods based on a pinhole camera model are presented: the Vessel-Focused Distance Estimation (VFDE) and the novel Vessel Object-Focused Distance Estimation (VOFDE). While VFDE uses the predefined height of a vessel for distance estimation, VOFDE uses standardized dimensions of objects on the vessel, detected with a Convolutional Neural Network (CNN) for instance segmentation to enhance estimation accuracy. Our evaluation covers distances up to 414 m, which is significantly beyond the scope of previous studies. When compared to the distances measured with a precise instrument, VOFDE achieves a Percentage Deviation Index (PDI) of 1.34% to 9.45%. This advance holds significant potential for improving maritime surveillance with monocular cameras and is also applicable in other areas, such as low-cost maritime vehicles equipped with single cameras. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

20 pages, 2023 KiB

Open AccessArticle

Maximizing Efficiency in the Suez Canal: A New Approach to Evaluate the Impact of Optimal Time-Varying Tolls on Ship Arrival Times

by Chen-Hsiu Laih

J. Mar. Sci. Eng. 2024, 12(1), 76; https://doi.org/10.3390/jmse12010076 - 28 Dec 2023

Viewed by 580

Abstract

In the existing literature, an optimal time-varying toll scheme has been proposed for the Suez Canal to address the inefficiency of numerous ships queuing and waiting at the anchorage area to enter the canal. The primary objective of this tolling strategy is to [...] Read more.

In the existing literature, an optimal time-varying toll scheme has been proposed for the Suez Canal to address the inefficiency of numerous ships queuing and waiting at the anchorage area to enter the canal. The primary objective of this tolling strategy is to alleviate the significant issue of ships queuing at the canal’s anchorage area. This stands in contrast to the current tolling system employed by the Suez Canal, which primarily aims to recover the management and operational costs associated with ship passage through the canal. However, the existing literature has yet to explore how the arrival times of ships at the anchorage area will change after implementing the optimal time-varying toll scheme. The goal is to ensure that the equilibrium cost of each tolled ship does not result in losses and achieve maximum efficiency in eliminating queueing at the anchorage area. To address this gap, this paper adopts the principle of cost equilibrium conservation and utilizes the Point-Slope Form to derive two mathematical formulas representing all ships’ post-toll arrival times at the anchorage area of the Suez Canal. These formulas are specifically derived for two categories of tolled ships: those that enter the canal earlier than the latest entry time regulated by the canal authorities and those that enter later. The derived formulas are concise and comparative, strengthening the theoretical underpinnings of the current pricing model for a queuing canal. Furthermore, they serve as valuable references for canal authorities in devising pertinent measures, such as organizing the scheduling of canal pilots, to facilitate the implementation of the optimal time-varying toll scheme. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

21 pages, 3806 KiB

Open AccessArticle

Changes in Accessibility of Chinese Coastal Ports to Arctic Ports under Melting Ice

by Ran Zhang, Yi Zuo, Zhuo Sun and Shuang Cong

J. Mar. Sci. Eng. 2024, 12(1), 54; https://doi.org/10.3390/jmse12010054 - 25 Dec 2023

Viewed by 836

Abstract

Global warming has accelerated the melting of Arctic sea ice, providing favorable conditions for Arctic shipping. Arctic ports are gaining prominence in shipping networks and international trade. Accessibility is a key indicator of port facilitation, and identifying trends in Arctic port accessibility holds [...] Read more.

Global warming has accelerated the melting of Arctic sea ice, providing favorable conditions for Arctic shipping. Arctic ports are gaining prominence in shipping networks and international trade. Accessibility is a key indicator of port facilitation, and identifying trends in Arctic port accessibility holds significance for Arctic route planning and port development. To achieve this, this paper develops a modeling framework for assessing the accessibility of Arctic ports. First, we utilize the Coupled Model Intercomparison Project (CMIP6) model to predict sea ice conditions and quantify the navigation risk for open water (OW) vessels and Arc4 ice-class (Arc4) vessels during the summer months of 2030–2050. The A-star (A*) algorithm is then used to plan the vessel’s shortest route while avoiding high-risk waters. Finally, changes in the accessibility of Arctic ports are calculated by using an improved gravity model. The framework is applied for the quantitative analysis of the accessibility of Chinese coastal ports to Arctic ports. The results indicate that accessibility to Arctic ports will gradually increase for all Chinese ports in the future, with the port of Shanghai continuing to maintain its prominence under the trend of melting sea ice. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

27 pages, 3102 KiB

Open AccessArticle

Integrating Software FMEA and STPA to Develop a Bayesian Network-Based Software Risk Model for Autonomous Ships

by Xue Yang, Yawei Zhu, Tao Zhou, Sheng Xu, Wenjun Zhang, Xiangyu Zhou and Xiangkun Meng

J. Mar. Sci. Eng. 2024, 12(1), 4; https://doi.org/10.3390/jmse12010004 - 19 Dec 2023

Viewed by 1056

Abstract

The autonomous shipping industry is increasingly focusing on enhancing the safety and reliability of software-based systems. Conducting a risk assessment is a requirement for demonstrating the safety equivalence of autonomous ships based on such systems to conventional vessels. Traditional risk assessment models, however, [...] Read more.

The autonomous shipping industry is increasingly focusing on enhancing the safety and reliability of software-based systems. Conducting a risk assessment is a requirement for demonstrating the safety equivalence of autonomous ships based on such systems to conventional vessels. Traditional risk assessment models, however, primarily focus on hardware failures, often overlooking potential software-related failures and functional inadequacies. This study proposes a framework integrating Software Failure Mode and Effects Analysis (FMEA), System–Theoretic Process Analysis (STPA), and Bayesian Network (BN) for risk identification of autonomous ship software systems. The results of a case study reveal that the framework sufficiently addresses the multifaceted nature of risks related to software in autonomous ships. Based on the findings of this study, we suggest the need for standardization of software architecture development in the autonomous ship industry and highlight the necessity for an enhanced understanding of AI-specific risks and the development of tailored risk assessment methodologies. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

20 pages, 9989 KiB

Open AccessArticle

Changing Arctic Northern Sea Route and Transpolar Sea Route: A Prediction of Route Changes and Navigation Potential before Mid-21st Century

by Yu Zhang, Xiaopeng Sun, Yufan Zha, Kun Wang and Changsheng Chen

J. Mar. Sci. Eng. 2023, 11(12), 2340; https://doi.org/10.3390/jmse11122340 - 12 Dec 2023

Cited by 2 | Viewed by 1007

Abstract

Sea ice concentration and thickness are key parameters for Arctic shipping routes and navigable potential. This study focuses on the changes in shipping routes and the estimation of navigable potential in the Arctic Northern Sea Route and Transpolar Sea Route during 2021–2050 based [...] Read more.

Sea ice concentration and thickness are key parameters for Arctic shipping routes and navigable potential. This study focuses on the changes in shipping routes and the estimation of navigable potential in the Arctic Northern Sea Route and Transpolar Sea Route during 2021–2050 based on the sea ice data predicted by eight CMIP6 models. The Arctic sea ice concentration and thickness vary among the eight models, but all indicate a declining trend. This study indicates that, under the two scenarios, the least-cost route will migrate more rapidly from the low-latitude route to the high-latitude route in the next 30 years, showing that the Transpolar Sea Route will be navigable for Open Water (OW) and Polar Class 6 (PC6) before 2025, which is advanced by nearly 10 years compared to previous studies. The sailing time will decrease to 16 and 13 days for OW and PC6 by 2050, which saves 3 days compared to previous studies. For OW, the navigable season is mainly from August to October, and the Northern Sea Route is still the main route, while for PC6, the navigable season is mainly from July to January of the following year, and the Transpolar Sea Route will become one of the important choices. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

25 pages, 7166 KiB

Open AccessArticle

A Novel Data-Driven Prediction Framework for Ship Navigation Accidents in the Arctic Region

by Xue Yang, Jingkai Zhi, Wenjun Zhang, Sheng Xu and Xiangkun Meng

J. Mar. Sci. Eng. 2023, 11(12), 2300; https://doi.org/10.3390/jmse11122300 - 04 Dec 2023

Cited by 1 | Viewed by 1059

Abstract

Arctic navigation faces numerous challenges, including uncertain ice conditions, rapid weather changes, limited communication capabilities, and lack of search and rescue infrastructure, all of which increase the risks involved. According to an Arctic Council statistical report, a remarkable 2638 maritime accidents were recorded [...] Read more.

Arctic navigation faces numerous challenges, including uncertain ice conditions, rapid weather changes, limited communication capabilities, and lack of search and rescue infrastructure, all of which increase the risks involved. According to an Arctic Council statistical report, a remarkable 2638 maritime accidents were recorded in Arctic waters between 2005 and 2017, showing a fluctuating upward trend. This study collected and analyzed ship accident data in Arctic waters to identify the various accident scenarios and primary risk factors that impact Arctic navigation safety. By utilizing data-driven algorithms, a model for predicting ship navigation accidents in Arctic waters was constructed, providing an in-depth understanding of the risk factors that make accidents more likely. The research findings are of practical significance for enhancing quantitative risk assessment, specifically focusing on the navigational risks in Arctic waters. The results of this study can assist maritime authorities and shipping companies in conducting risk analysis and implementing accident prevention measures for safe navigation in Arctic waters. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

17 pages, 9645 KiB

Open AccessArticle

Impacts of Arctic Sea Fog on the Change of Route Planning and Navigational Efficiency in the Northeast Passage during the First Two Decades of the 21st Century

by Kun Wang, Yu Zhang, Changsheng Chen, Shutong Song and Yue Chen

J. Mar. Sci. Eng. 2023, 11(11), 2149; https://doi.org/10.3390/jmse11112149 - 11 Nov 2023

Cited by 2 | Viewed by 848

Abstract

Under the background of climate change, the Northeast Passage’s navigability is on the rise. Arctic sea fog significantly influences navigational efficiency in this region. Existing research primarily focuses on routes accumulating the lowest distance, neglecting routes with the lowest time and sea fog’s [...] Read more.

Under the background of climate change, the Northeast Passage’s navigability is on the rise. Arctic sea fog significantly influences navigational efficiency in this region. Existing research primarily focuses on routes accumulating the lowest distance, neglecting routes with the lowest time and sea fog’s influence on route planning and navigational efficiency. This study compares the fastest and shortest routes and analyzes Arctic sea fog’s impact on the Northeast Passage from June to September (2001–2020). The results show that coastal areas are covered with less sea ice under notable monthly variations. Sea fog frequency is highest near coasts, declining with latitude. September offers optimal navigation conditions due to minimal ice and fog. When only sea ice is considered, the fastest route is approximately 4 days quicker than the shortest. The shortest route has migrated towards the higher latitude over two decades, while the fastest route remains closer to the Russian coast. Adding the impact of sea fog on the fastest route, the speed decreased by 30.2%, increasing sailing time to 45.1%. The new fastest route considering both sea ice and sea fog achieved a 13.9% increase in sailing speed and an 11.5% reduction in sailing time compared to the original fastest route. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

19 pages, 7402 KiB

Open AccessArticle

Assessing the Potential for Energy Efficiency Improvement through Cold Ironing: A Monte Carlo Analysis with Real Port Data

by Daogui Tang, Tao Jiang, Chaoyuan Xu, Zhe Chen, Yupeng Yuan, Wuyou Zhao and Josep M. Guerrero

J. Mar. Sci. Eng. 2023, 11(9), 1780; https://doi.org/10.3390/jmse11091780 - 12 Sep 2023

Cited by 1 | Viewed by 1182

Abstract

Ports in China are facing significant pressure to reduce carbon emissions in alignment with carbon peak and carbon neutrality goals. Onshore power supply (OPS) is regarded as a promising approach to accomplish these targets, necessitating a thorough evaluation of its impact for port [...] Read more.

Ports in China are facing significant pressure to reduce carbon emissions in alignment with carbon peak and carbon neutrality goals. Onshore power supply (OPS) is regarded as a promising approach to accomplish these targets, necessitating a thorough evaluation of its impact for port authorities to make informed decisions regarding its adoption. This research focuses on Ningbo Zhoushan Port, the largest port globally, as a case study. Two metrics are proposed to quantify the energy efficiency of ships powered by onshore energy while berthed. The installation and connection status of OPS in the port area are analyzed. Subsequently, the energy demand of berthed ships is assessed, and the potential for energy efficiency improvement resulting from OPS implementation is evaluated using Monte Carlo methods. The findings reveal untapped potential in the studied port area, with OPS demonstrating the ability to improve energy efficiency of berthed ships at a rate parallel to the connection rate, excluding indirect emissions. However, considering indirect emissions and energy loss diminishes the effectiveness of OPS. The paper discusses practical implications for enhancing the energy efficiency of OPS, enabling port authorities to make well-informed decisions. These findings are invaluable for Chinese port authorities striving to achieve carbon reduction goals and enhance sustainability in the maritime industry. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

28 pages, 8353 KiB

Open AccessArticle

Fuel Consumption Prediction and Optimization Model for Pure Car/Truck Transport Ships

by Miao Su, Zhenqing Su, Shengli Cao, Keun-Sik Park and Sung-Hoon Bae

J. Mar. Sci. Eng. 2023, 11(6), 1231; https://doi.org/10.3390/jmse11061231 - 15 Jun 2023

Cited by 3 | Viewed by 2107

Abstract

Predicting and optimizing ship fuel use is a crucial technology for lowering greenhouse gas emissions. Unfortunately, existing research is rarely capable of developing fuel consumption forecasts and optimization models for a particular transport system. This study develops a fuel consumption prediction model based [...] Read more.

Predicting and optimizing ship fuel use is a crucial technology for lowering greenhouse gas emissions. Unfortunately, existing research is rarely capable of developing fuel consumption forecasts and optimization models for a particular transport system. This study develops a fuel consumption prediction model based on machine learning and a fuel consumption optimization model based on particle swarm optimization for ships. We studied nearly ten years of big data from a large Korean pure car and truck shipping company (PCTC), which contained 16,189 observations from 2012 to 2021. Results indicate that the XGBoost deep learning model outperforms conventional prediction models at the stage of fuel consumption prediction, with an R² of 0.97. Furthermore, in the fuel consumption optimization stage, the particle swarm optimization method can effectively reduce fuel consumption. This study helps PCTC companies control shipping costs and save energy. Insights for shipping businesses to meet environmental demands are provided as well. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

20 pages, 43947 KiB

Open AccessArticle

Sparsity Regularization-Based Real-Time Target Recognition for Side Scan Sonar with Embedded GPU

by Zhuoyi Li, Deshan Chen, Tsz Leung Yip and Jinfen Zhang

J. Mar. Sci. Eng. 2023, 11(3), 487; https://doi.org/10.3390/jmse11030487 - 24 Feb 2023

Cited by 2 | Viewed by 1684

Abstract

Side Scan Sonar (SSS) is widely used to search for seabed objects such as ships and wrecked aircraft due to its high-imaging-resolution and large planar scans. SSS requires an automatic real-time target recognition system to enhance search and rescue efficiency. In this paper, [...] Read more.

Side Scan Sonar (SSS) is widely used to search for seabed objects such as ships and wrecked aircraft due to its high-imaging-resolution and large planar scans. SSS requires an automatic real-time target recognition system to enhance search and rescue efficiency. In this paper, a novel target recognition method for SSS images in varied underwater environment, you look only once (YOLO)-slimming, based on convolutional a neural network (CNN) is proposed. The method introduces efficient feature encoders that strengthen the representation of feature maps. Channel-level sparsity regularization in model training is performed to speed up the inference performance. To overcome the scarcity of SSS images, a sonar image simulation method is proposed based on deep style transfer (ST). The performance on the SSS image dataset shows that it can reduce calculations and improves the inference speed with a mean average precision (mAP) of 95.3 and at least 45 frames per second (FPS) on an embedded Graphics Processing Unit (GPU). This proves its feasibility in practical application and has the potential to formulate an image-based real-time underwater target recognition system. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

18 pages, 6738 KiB

Open AccessArticle

Path Planning for Ferry Crossing Inland Waterways Based on Deep Reinforcement Learning

by Xiaoli Yuan, Chengji Yuan, Wuliu Tian, Gan Liu and Jinfen Zhang

J. Mar. Sci. Eng. 2023, 11(2), 337; https://doi.org/10.3390/jmse11020337 - 03 Feb 2023

Cited by 1 | Viewed by 1388

Abstract

Path planning is a key issue for safe navigation of inland ferries. With the development of ship intelligence, how to enhance the decision–support system of a ferry in a complex navigation environment is one of the key issues. The inland ferries need to [...] Read more.

Path planning is a key issue for safe navigation of inland ferries. With the development of ship intelligence, how to enhance the decision–support system of a ferry in a complex navigation environment is one of the key issues. The inland ferries need to cross the channel frequently and, thus, risky encounters with target ships in the waterway are more frequent, so they need an intelligent decision–support system that can deal with complex situations. In this study, a reinforced deep learning method is proposed for path planning of inland ferries during crossing of the waterways. In the study, the state space, action space and reward function of the Deep Q-network (DQN) model are designed and improved to establish an autonomous navigation method for ferries considering both economy and safety. The DQN model also takes into account the crossing behavior, navigation economy and safety. Finally, the model is applied to case studies to verify its effectiveness. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

25 pages, 9894 KiB

Open AccessArticle

Recognition of Unsafe Onboard Mooring and Unmooring Operation Behavior Based on Improved YOLO-v4 Algorithm

by Changjiu Zhao, Wenjun Zhang, Changyuan Chen, Xue Yang, Jingwen Yue and Bing Han

J. Mar. Sci. Eng. 2023, 11(2), 291; https://doi.org/10.3390/jmse11020291 - 30 Jan 2023

Cited by 1 | Viewed by 3874

Abstract

In the maritime industry, unsafe behaviors exhibited by crew members are a significant factor contributing to shipping and occupational accidents. Among these behaviors, unsafe operation of mooring lines is particularly prone to causing severe accidents. Video-based monitoring has been demonstrated as an effective [...] Read more.

In the maritime industry, unsafe behaviors exhibited by crew members are a significant factor contributing to shipping and occupational accidents. Among these behaviors, unsafe operation of mooring lines is particularly prone to causing severe accidents. Video-based monitoring has been demonstrated as an effective means of detecting these unsafe behaviors in real time and providing early warning to crew members. To this end, this paper presents a dataset comprising videos of unsafe mooring line operations by crew members on the M.V. YuKun. Additionally, we propose an unsafe behavior recognition model based on the improved You Only Look Once (YOLO)-v4 network. Experimental results indicate that the proposed model, when compared to other models such as the original YOLO-v4 and YOLO-v3, demonstrates a significant improvement in recognition speed by approximately 35% while maintaining accuracy. Additionally, it also results in a reduction in computation burden. Furthermore, the proposed model was successfully applied to an actual ship test, which further verifies its effectiveness in recognizing unsafe mooring operation behaviors. Results of the actual ship test highlight that the proposed model’s recognition accuracy is on par with that of the original YOLO-v4 network but shows an improvement in processing speed by 50% and a reduction in processing complexity by about 96%. Hence, this work demonstrates that the proposed dataset and improved YOLO-v4 network can effectively detect unsafe mooring operation behaviors and potentially enhance the safety of marine operations. Full article

(This article belongs to the Special Issue Safety and Efficiency of Maritime Transportation and Ship Operations)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Safety and Efficiency of Maritime Transportation and Ship Operations

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (14 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI