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Lifeboats are life-saving equipment used when it is necessary to abandon a ship or, in some ships, for man-overboard situations (to collect persons from water). Every seafarer onboard a ship has a task related to lifeboat operation in an emergency. In order to master and practise the assigned tasks, be ready to react at any moment, and efficiently use life-saving equipment and appliances, seafarers on ships perform drills at prescribed intervals. Effective drill performance is of paramount importance, as it improves safety and enables crew members to practise lifeboat operations. However, although their primary role is life-saving, lifeboat drills have resulted in numerous accidents, causing injuries and fatalities, besides equipment damage. Therefore, it is necessary to prevent such unwanted events and discover their root causes. As the human factor is considered a significant cause of marine accidents, this paper aims to quantify human error probability (HEP) during lifeboat drills. In addition, because lifeboat drill accident data are scarce, this study adopted the Success Likelihood Index Method (SLIM) for human reliability analysis (HRA). Based on expert judgments, the tasks with the highest probability of human error and factors significantly influencing human performance during lifeboat drills are identified. According to the study results, the recovery of the lifeboat is the most hazardous phase with the highest HEP. In addition, the BN-SLIM is adopted to estimate the probability of human error during the recovery of the lifeboat. The task with the largest HEP is confirming the release lever is properly rested and hooks locked (HEP = 4.5%). Furthermore, the design and condition of equipment and Crew Competence are identified as the most important Performance-Shaping Factors (PSFs) that affect crew members' performance. The BN-SLIM model was verified utilising a sensitivity analysis and validated by analysing real-life lifeboat drill accidents that occurred during lifeboat recovery. The results confirmed that the model could be used to analyse lifeboat accidents and for proactive preventive measures because most influencing factors are recognised, and acting on them can significantly reduce the HEP of the overall task, improve lifeboat safety, and save lives at sea. [ABSTRACT FROM AUTHOR]

Lifeboats are life-saving equipment used when it is necessary to abandon a ship or, in some ships, for man-overboard situations (to collect persons from water). Every seafarer onboard a ship has a task related to lifeboat operation in an emergency. In order to master and practise the assigned tasks, be ready to react at any moment, and efficiently use life-saving equipment and appliances, seafarers on ships perform drills at prescribed intervals. Effective drill performance is of paramount importance, as it improves safety and enables crew members to practise lifeboat operations. However, although their primary role is life-saving, lifeboat drills have resulted in numerous accidents, causing injuries and fatalities, besides equipment damage. Therefore, it is necessary to prevent such unwanted events and discover their root causes. As the human factor is considered a significant cause of marine accidents, this paper aims to quantify human error probability (HEP) during lifeboat drills. In addition, because lifeboat drill accident data are scarce, this study adopted the Success Likelihood Index Method (SLIM) for human reliability analysis (HRA). Based on expert judgments, the tasks with the highest probability of human error and factors significantly influencing human performance during lifeboat drills are identified. According to the study results, the recovery of the lifeboat is the most hazardous phase with the highest HEP. In addition, the BN-SLIM is adopted to estimate the probability of human error during the recovery of the lifeboat. The task with the largest HEP is confirming the release lever is properly rested and hooks locked (HEP = 4.5%). Furthermore, the design and condition of equipment and Crew Competence are identified as the most important Performance-Shaping Factors (PSFs) that affect crew members’ performance. The BN-SLIM model was verified utilising a sensitivity analysis and validated by analysing real-life lifeboat drill accidents that occurred during lifeboat recovery. The results confirmed that the model could be used to analyse lifeboat accidents and for proactive preventive measures because most influencing factors are recognised, and acting on them can significantly reduce the HEP of the overall task, improve lifeboat safety, and save lives at sea.

Marine accidents can result in severe economic losses and casualties, underscoring the critical need for effective risk assessment.. In this study, quantitative marine accident reports from Korea that objectively describe accident variables were collected and classified to analyze marine accidents of fishing ships To analyze the causes of accidents involving different types of fishing ships, a survey with subject matter experts (SMEs) was conducted. A fishing ship accident Bayesian network (FABN) scenario was then developed by integrating fishing ship accident data with SME insights. The FABN was comprehensively modeled based on the scenario, with marine accidents being modeled based on causal variables each marine accident. Changes in the output value of the FABN were verified via a sensitivity analysis, and the independence and statistical significance of the model were confirmed using a statistical analysis of the collected data. FABN allows for the immediate assessment of the probability of marine accidents related to fishing ships by utilizing network structures, and provides the advantage of structurally assessing ship accident risks

Although the Brazilian Amazon is still one of the most well-conserved environments in the world, it contains an extensive network of waterways that are used by a wide range of vessels that transport both people and cargo, as well as undertaking other activities. To plan environmental risk disaster strategies here, the potential effects of technological disasters, including marine accidents, must be taken into consideration. This paper seeks to redress this by providing a review of the possible risks to the Amazon aquatic environment that could result from various types of marine accidents. While the Amazon region has been researched worldwide, both extensively and intensively, regarding land use, climate, and environmental characterization, work in this field is scarce. A review of the main environmental characteristics of the Amazon is provided, including a description of common marine accidents that have occurred in this region. The environmental impacts experienced by the aquatic environment due to marine accidents worldwide were reviewed from the scientific literature to examine potential risks to the Amazon waterways. It was found that marine accidents, such as fire/explosions and the sinking of ships with different types of cargo, can cause the spillage of oil and other hazardous materials, causing catastrophic damage to the aquatic environment. Changes in the hydrological characteristics of rivers, including unexpected changes in the weather, such as heavy rain and winds, may also influence pollutant dispersion. Initiatives to deal with these technological hazards in the Amazon basin should also consider the potential social and environmental impacts in the protected areas of this region. It is hoped that this paper can serve as a starting point toward the governance and planning of risk disaster management actions, which are aimed at reducing the negative environmental impacts caused by marine accidents in the region. [ABSTRACT FROM AUTHOR]

Jinhae Bay in South Korea is a common typhoon shelter, but there are no established criteria for the area or vessel capacity. The aim of this study was to determine the optimal capacity and arrangement of typhoon shelters for vessels in the sea area surrounding Jinhae Bay. The study identified several areas that could serve as typhoon shelters and conducted a survey with experienced VTS operators and ship operators to identify the best typhoon avoidance areas. The study found that the Japanese and Spanish design criteria for anchoring in strong winds were useful in computing the optimal capacity of typhoon shelters. A nesting algorithm based on the genetic algorithm and the No-Fit-Polygon theory was used to optimize the arrangement of shelters. The study found that the Jinhae Bay typhoon shelter can be effectively managed by arranging shelter-seeking vessels based on the nesting algorithm. The study contributes to supporting quantitative methodology-based decision-making and has practical significance for managing typhoon shelters in the Jinhae Bay area. Further research is needed to evaluate the proposed arrangement plan for typhoon shelters and confirm the validity of the results through simulation and practical implementation. Additionally, the time complexity for vessels to approach the anchorage should be considered in future studies. [ABSTRACT FROM AUTHOR]

Fishing boats are equipped to quickly rescue ships and save lives in the event of an incident at sea; therefore, determination of the incident location is imperative for a swift response. According to the 2021 marine accidents by ship use statistics, fishing and non-fishing boats accounted for 64.6 and 35.4%, respectively, of the total 3053 ships involved in an accident. In addition to V-pass and the Automatic Identification System (AIS), several other types of terminals exist; however, approximately 91% of all registered fishing boats use V-pass terminals. Therefore, it is essential to know the exact location of fishing boats. However, little research has been conducted on V-pass equipment. Therefore, in this study, marine experiments were conducted using V-pass and AIS terminals that are mainly used in fishing boats. To determine the exact location of an incident and rapidly respond and rescue, this study compared the data saved in the terminals with the data received by the Vessel Traffic Service center. In the event of a maritime incident, the radio shadow areas and causes of the error in the location transmitter must be investigated to quickly rescue the fishing boat and to determine the root cause of the incident, respectively. [ABSTRACT FROM AUTHOR]

Despite the development of advanced technology, marine accidents have not decreased. To prevent marine accidents, it is necessary to predict accidents in advance. With the recent development of artificial intelligence (AI), AI technologies such as deep learning have been applied to create and analyze predictive models in various fields. The purpose of this study is to develop a model for predicting the frequency of marine accidents using a long-short term memory (LSTM) network. In this study, a prediction model was developed using marine accidents from 1981 to 2019, and the proposed model was evaluated by predicting the accidents in 2020. As a result, we found that marine accidents mainly occurred during the third officer's duty time, representing that the accidents are highly related to the navigator's experience. In addition, the proposed LSTM model performed reliably to predict the frequency of marine accidents with a small mean absolute percentage error (best MAPE: 0.059) that outperformed a traditional statistical method (i.e, ARIMA). This study could help us build LSTM structures for marine accident prediction and could be used as primary data to prevent the accidents by predicting the number of marine accidents by the navigator's watch duty time. [ABSTRACT FROM AUTHOR]

Fishing boats are equipped to quickly rescue ships and save lives in the event of an incident at sea; therefore, determination of the incident location is imperative for a swift response. According to the 2021 marine accidents by ship use statistics, fishing and non-fishing boats accounted for 64.6 and 35.4%, respectively, of the total 3053 ships involved in an accident. In addition to V-pass and the Automatic Identification System (AIS), several other types of terminals exist; however, approximately 91% of all registered fishing boats use V-pass terminals. Therefore, it is essential to know the exact location of fishing boats. However, little research has been conducted on V-pass equipment. Therefore, in this study, marine experiments were conducted using V-pass and AIS terminals that are mainly used in fishing boats. To determine the exact location of an incident and rapidly respond and rescue, this study compared the data saved in the terminals with the data received by the Vessel Traffic Service center. In the event of a maritime incident, the radio shadow areas and causes of the error in the location transmitter must be investigated to quickly rescue the fishing boat and to determine the root cause of the incident, respectively.

Jinhae Bay in South Korea is a common typhoon shelter, but there are no established criteria for the area or vessel capacity. The aim of this study was to determine the optimal capacity and arrangement of typhoon shelters for vessels in the sea area surrounding Jinhae Bay. The study identified several areas that could serve as typhoon shelters and conducted a survey with experienced VTS operators and ship operators to identify the best typhoon avoidance areas. The study found that the Japanese and Spanish design criteria for anchoring in strong winds were useful in computing the optimal capacity of typhoon shelters. A nesting algorithm based on the genetic algorithm and the No-Fit-Polygon theory was used to optimize the arrangement of shelters. The study found that the Jinhae Bay typhoon shelter can be effectively managed by arranging shelter-seeking vessels based on the nesting algorithm. The study contributes to supporting quantitative methodology-based decision-making and has practical significance for managing typhoon shelters in the Jinhae Bay area. Further research is needed to evaluate the proposed arrangement plan for typhoon shelters and confirm the validity of the results through simulation and practical implementation. Additionally, the time complexity for vessels to approach the anchorage should be considered in future studies.

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This article explores the use of ontology for semi-automatic marine vessel navigation and ship-to-ship communication to mitigate collision risk. Semi-automatic vessel communication is a step towards automatic communication for autonomous ships. Examples of how such communication can be used is discussed, based on a comprehensive analysis of selected marine collisions, with particular attention to the communication conducted on ships. The effectiveness of such communication was assessed and compared. The suggested solutions are based on the review of official reports from accident investigations. The novelties of this work include original ontologies and interfaces. Through this work, it could be possible to fully automate communication processes between ships. In future work, the research results in this work will be used to create a system of automatic communications for manned and autonomous vessels. [ABSTRACT FROM AUTHOR]

The International Maritime Dangerous Goods (IMDG) Code training is mandatory for all shoreside personnel involved in the handling and transport of dangerous cargoes by sea. This study aims to measure and evaluate the port workers’ dangerous cargo transport general awareness level. For this purpose, the “Dangerous Cargo Transport General Awareness Questionnaire” was developed and applied to trained 100 port workers face-to-face. The questionnaire was proven to be valid and reliable by content validity, construct validity, internal consistency reliability, and testretest reliability analyses. Four factors were determined as a result of Explanatory Factor Analysis. Discriminant analyses were performed using the Student’s t-test and One Way ANOVA test. Pearson correlation analysis was carried out to determine the relationship between factors. Simple linear regression analysis was used for modeling the relationship between factors. SPSS 24.0 was utilized to conduct the analyses. According to analysis results, port workers’ dangerous cargo transport general awareness does not differ depending on age, position, and education. There is a weak positive or a moderate positive correlation between factors. Port workers have an average and above-average level of general awareness. It is highlighted that increasing this level is possible by increasing the frequency of dangerous cargo transport training. Suggestions are offered for more effective training. [ABSTRACT FROM AUTHOR]

Despite the development of advanced technology, marine accidents have not decreased. To prevent marine accidents, it is necessary to predict accidents in advance. With the recent development of artificial intelligence (AI), AI technologies such as deep learning have been applied to create and analyze predictive models in various fields. The purpose of this study is to develop a model for predicting the frequency of marine accidents using a long-short term memory (LSTM) network. In this study, a prediction model was developed using marine accidents from 1981 to 2019, and the proposed model was evaluated by predicting the accidents in 2020. As a result, we found that marine accidents mainly occurred during the third officer’s duty time, representing that the accidents are highly related to the navigator’s experience. In addition, the proposed LSTM model performed reliably to predict the frequency of marine accidents with a small mean absolute percentage error (best MAPE: 0.059) that outperformed a traditional statistical method (i.e, ARIMA). This study could help us build LSTM structures for marine accident prediction and could be used as primary data to prevent the accidents by predicting the number of marine accidents by the navigator’s watch duty time.

Detecting the risk of collision is a very important step to prevent marine accidents. For detecting the risk of collision, radar plotting is often used. Based on therelative position and motion of two ships, the risk of collision between them can be evaluated. However, the present radar equipmentis not supported to detect the risk of collision between two target ships from the observation data measured by a third party. This causes difficulties for officers of shore stations, when evaluating the marine traffic situation to maintain the safety of navigation. To solve this problem, it is necessary to develop a method to evaluate the risk of collision between two target ships from the observation data measured by the shore station radar (the third party). In this article, the development of such method is introduced.. [ABSTRACT FROM AUTHOR]

This study discusses the marine accident involving the Cosco Busan, the container ship that hit the base of the Delta Tower of the San Francisco-Oakland Bay Bridge in November 2007. An analysis of the elements resulting in the accident and its consequences has been carried out, followed by an analysis of the navigational risk using mathematical and tabular values. Mathematical values refer to the navigational risk in a specific sailing area, while tabular values refer to the navigational risk using a risk assessment. The main goal of this research was to identify and propose new measures that are correlated with a risk assessment. These measures should be applied in areas where an accident takes place so that future marine accidents can be reduced. [ABSTRACT FROM AUTHOR]

This paper analyses the marine accident reports published by the USA National Transportation Safety Board (NTSB) between June 1975 and September 2017, in order to ascertain the exact influence of the crew and/or other people involved (pilots, company, etc.) on the cause of the incident and to find out the types of errors made by them. Additionally, the mistakes and those involved are analysed together to verify the correct implementation of international regulations concerning seafarers. The results suggest that crew error is relatively uncommon in cargo and passenger fleets. This points to the effectiveness of the International Convention on Standards of Training, Certification and Watchkeeping (STCW convention). However, taking into consideration the high percentage of human error due to failure in communication and misjudgements during navigation in pilot waters, it may be deduced that the coordination among those on the bridge may be improved. On the other hand, crew error on board tugs exceeds 50%. This increase seems to be due to the difficulties of navigation in narrow waterways.

This study used a spatial distribution analysis to identify the risky areas in the Çanakkale Strait - one of the narrowest waterways with high marine traffic - in terms of ship accidents. To accomplish this, a point density analysis, as part of the geographic information systems (GIS) methodology, was used to create accident density distributions and thematic maps. A total of 162 marine accidents in the Çanakkale Strait between 2007 and 2018 were taken into account. Detailed technical data of accidents were obtained from accident reports provided by the Turkish Maritime Search and Rescue Coordination Center (TMSRCC). The results showed that, among the 162 cases, bulk carriers have the highest accident rate, and most accidents at the Nara Turn were caused by engine failure. In addition, accidents due to navigational failure occurred in every region of the strait. Remarkably, factors directly and indirectly related to human error were still the determining factors in marine accidents. As a result, the risk of marine accidents was higher in the narrow portions of the waterway, and navigation was difficult, especially in areas such as the Nara Turn Point. In future research, it is recommended to consider a wider period of activities using different methods to provide more comprehensive results. [ABSTRACT FROM AUTHOR]

The purpose and scope of this paper is to describe anchoring procedures and typical human errors that are the cause of many marine accidents related to the anchoring of vessels and their manoeuvring in anchorage areas. In this paper the author focuses on typical marine accidents recorded for very large crude carriers (VLCC). As a result of the analyses, it can be seen that in the vast majority of cases these accidents are caused by human error and are related to the violation of accepted maritime anchor practices and a failure to observe the relevant safety and security procedures. The consequences of the accidents vary from the minor (e.g. slight structural damage to the anchor winches or other marine equipment) to the serious, which result in dry dock repairs due to hull damage, loss of stability and/or loss of navigability. The described cases refer to both favourable and extremely unfavourable hydro meteorological conditions, the latter including strong winds, currents and waves within the confined anchorage area.

The law of general average is one of the oldest institutions in maritime law, which is still applicable in contemporary shipping. Although the role and function of general average have naturally changed throughout centuries of its history (the main reasons therefor being the popularization of maritime insurance, which evolved much later than the general average) and general average has been and is subject to criticism pointing to its anachronistic nature and redundancy in today’s maritime economic realities. However practice shows that general average continues to resist these accusations and is commonly used in the practice of maritime commercial trade. This article deals with the issue of general average in light of Polish maritime law regulations, the essence and specificity of these legislative solutions concerning the safety of shipping in Poland, and also gives examples of events that occurred at sea that permit the announcement of an act of the general average. This article also presents considerations with regard to arguments in favour of maintaining the institution of general average as a legal instrument used in shipping, as well as critical voices emphasizing the need to eliminate general average as an institution of maritime law aimed at distributing losses, incurred to avoid a common peril, to the participants of a maritime adventure. [ABSTRACT FROM AUTHOR]

Abstract Concerns have been raised around pilotage in Korea due to a rise in marine accidents in the 2010s. Since the late 2000s, a debate has been sparked on the most suitable age of retirement for Korean pilots. The debate has focused on the extension of retirement age of pilots from 65 to 68 and whether this will affect the probability of marine accidents. Therefore, it is crucial to calculate the probability of marine accidents in relation to different age groups of pilots. After collecting the data of marine accidents caused by pilot's negligence, the study suggests two measurements of probability of marine accidents during pilotage: on the basis of the number of pilotage services and the hours of pilotage services. The analysis finds that age is not the exclusive cause of pilotage marine accidents by the age group over 65. [ABSTRACT FROM AUTHOR]

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

This paper investigates the process of marine accident analysis for the official interpretation to define the rate of defects of vessels in the intended case and proposes the pairwise comparison approach which is frequently used in AHP method. The assessment of marine accidents is a complicated and sophisticated problem which needs a professional and fair judgment based on the existing evidences and navigational specs. However, human judgment is limited and it is usually problematic to evaluate several aspects of a case. The pairwise comparison method is first suggested to simplify decision making process for ranking or selecting an item among the alternatives and it is an essential part of analytic hierarchy process. By utilizing the pairwise comparison, the defect rate of a snapshot of marine accident is calculated in a stepwise approach.

Many causal factors to marine traffic accidents (MTAs) influence each other and have associated effects. It is necessary to quantify the correlation path mode of these factors to improve accident prevention measures and their effects. In the application of human factors to accident mechanisms, the complex structural chains on causes to MTA systems were analyzed by combining the human failure analysis and classification system (HFACS) with theoretical structural equation modeling (SEM). First, the accident causation model was established as a human error analysis classification in sight of a MTA, and the constituent elements of the causes of the accident were conducted. Second, a hypothetical model of human factors classification was proposed by applying the practice of the structural model. Third, with the data resources from ship accident cases, this hypothetical model was discussed and simulated, and as a result, the relationship path dependency mode between the latent independent variable of the accident was quantitatively analyzed based on the observed dependent variable of human behavior. Application examples show that relationships in the HFACS are verified and in line with the path developing mode, and resource management factors have a pronounced influence and a strong relevance to the causal chain of the accidents. Appropriate algorithms for the theoretical model can be used to numerically understand the safety performance of marine traffic systems under different parameters through mathematical analysis. Hierarchical assumptions in the HFACS model are quantitatively verified.

Hong, D.-B. and Yang, C.-S., 2017. Designing an algorithm to generate dynamic intentional grounding zones (DIGOs) for distressed passenger ships in coastal regions. In: Lee, J.L.; Griffiths, T.; Lotan, A.; Suh, K.-S., and Lee, J. (eds.), The 2nd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 79, pp. 134-138. Coconut Creek (Florida), ISSN 0749-0208. In an emergency case, a passenger ship can be grounded on coastal zone in order to prevent sinking of the vessel and to minimize the injuries and casualties. For the safe and efficient mustering and evacuation of cruise ships, the innovative and reliable systems are needed and discussed in the International Maritime Organization (IMO) for several decadal years. In this paper a novel method is suggested for designating a safe grounding zone, here Dynamic Intentional Grounding Zones (DIGOs), in real-time situation. Thus, DIGO will be a place around passenger ship for effective emergency evacuation in case of uncontrolled marine accident. The research area is the southwest coastal region of Korea including Jindo Island. In this region, there are many passenger ships regularly travelling between islands, large intertidal areas, and eddies caused by rapid changes in currents. DIGOs are automatically calculated in three-dimensional space by combining shipping information (position, draft, etc.) and marine environments (water depth, sea-bottom sediments, and tide level) in real-time. The results of this study can be used to support captains' decision-making during maritime accidents. [ABSTRACT FROM AUTHOR]

Currently, globalization of the world economy has also resulted in a shipping volume increase. However, this growth in maritime traffic has led to increased risk of marine accidents. These accidents have a higher probability of occurring in regions where geographical features such as islands are present. Further, the positioning of rescue ships in a particular ocean region with a high level of maritime activity is critical for rescue operations. This paper proposes a method for determining an optimal set of locations for stationing rescue ships in an ocean region with numerous accident sites, such as in the Wando islands of South Korea. The computational challenge in this problem is identified as the positioning of numerous islands of varying sizes located in the region. Thus, the proposed method combines a clustering-based optimization method and an image processing approach that incorporates flood filling to calculate the shortest pixel value between two points in the ocean that detours around the islands. Experimental results indicate that the proposed method reduces the distance between rescue ships and each accident site by 5.0 km compared to the original rescue ship locations. Thus, rescue time is reduced.

Šibenik is a large and one of the oldest and best protected natural harbor on the Croatian Adriatic coast. The Old Port is located in the submerged estuary of the river Krka. Limited available room for maneuvring within the harbour, new passenger terminal and part of the port for handling different types of cargo reduce the space for safe navigation and mooring / unmooring of merchant and cruise ships. Approach to the port of Šibenik from the open sea, especially the navigation through St. Anthony channel and maneuvering inside the waters of the city port present a particular challenge to each seafarer. As far as safety is concerned, the mentioned circumstances significantly contribute to increasing the threat of possible maritime accidents. Therefore, there is a need to evaluate the potential threats of maritime accidents in the Šibenik St. Anthony channel. To determine the threat of maritime accidents a qualitative method was used: ranking of threats. Each maritime accident in the narrow area of the St. Anthony channel and the port of Šibenik could result in severe consequences on the overall economic and other activities of the port of Šibenik. St. Anthony channel is the only entrance into the central Dalmatian town of Šibenik and international port of Šibenik. Because of its characteristics, the length which is not in a straight line, it is necessary to frequently change course at shorter intervals. Channel width in some places is reduced and causes problems, and due to sea currents and occasional strong winds, the channel is from the point of safe navigation very difficult for navigation. Moreover, passing ships over 50 GT within the channel is dangerous. The possibility of a collision, grounding and / or sinking of large ships during transit through the St. Anthony channel may eventually lead to a complete closure of maritime passenger and freight traffic to the port of Šibenik. It is therefore of utmost importance to assess the threat of a collision, grounding and / or sinking of ships in the waters of the port of Šibenik. [ABSTRACT FROM AUTHOR]

Human factors play an important role in the origin of accidents,and it is commonly claimed that between seventy andninety-five percent of industrial and transport accidents involvehuman factors, see Figure 1.Some authorities, however, claim that ultimately, all accidentsinvolve human factors.

A vessel must navigate along designated routes within a harbor area to ensure navigation safety. The impact of strong currents is one of the most dangerous factors in coastal navigation. However, it is challenging to determine the deviation of a ship in advance from the ship's position data in the case of a marine accident. In this study, to support the decision-making of ship navigators and vessel traffic service (VTS) operators in track monitoring tasks, tracks were classified according to the tidal stream, and the track distribution was analyzed according to the tidal current situations. Marine accident analysis was performed to investigate the tidal influence on ship tracks. Track data were collected for 12 months from a VTS center in Korea, and tidal information was collected through a meteorological observation buoy. Representative tracks were extracted from the track data using the support vector regression (SVR) seaway model. K-fold cross-validation and a grid search were performed to determine the optimal parameters. The ship tracks appeared in specific patterns according to the forces and directions of tidal currents, and specific deviation patterns were observed. This study is expected to contribute to the reduction of marine accidents by predicting ship trajectories according to the tidal situations in advance. [ABSTRACT FROM AUTHOR]

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

Many causal factors to marine traffic accidents (MTAs) influence each other and have associated effects. It is necessary to quantify the correlation path mode of these factors to improve accident prevention measures and their effects. In the application of human factors to accident mechanisms, the complex structural chains on causes to MTA systems were analyzed by combining the human failure analysis and classification system (HFACS) with theoretical structural equation modeling (SEM). First, the accident causation model was established as a human error analysis classification in sight of a MTA, and the constituent elements of the causes of the accident were conducted. Second, a hypothetical model of human factors classification was proposed by applying the practice of the structural model. Third, with the data resources from ship accident cases, this hypothetical model was discussed and simulated, and as a result, the relationship path dependency mode between the latent independent variable of the accident was quantitatively analyzed based on the observed dependent variable of human behavior. Application examples show that relationships in the HFACS are verified and in line with the path developing mode, and resource management factors have a pronounced influence and a strong relevance to the causal chain of the accidents. Appropriate algorithms for the theoretical model can be used to numerically understand the safety performance of marine traffic systems under different parameters through mathematical analysis. Hierarchical assumptions in the HFACS model are quantitatively verified. [ABSTRACT FROM AUTHOR]

Currently, globalization of the world economy has also resulted in a shipping volume increase. However, this growth in maritime traffic has led to increased risk of marine accidents. These accidents have a higher probability of occurring in regions where geographical features such as islands are present. Further, the positioning of rescue ships in a particular ocean region with a high level of maritime activity is critical for rescue operations. This paper proposes a method for determining an optimal set of locations for stationing rescue ships in an ocean region with numerous accident sites, such as in the Wando islands of South Korea. The computational challenge in this problem is identified as the positioning of numerous islands of varying sizes located in the region. Thus, the proposed method combines a clustering-based optimization method and an image processing approach that incorporates flood filling to calculate the shortest pixel value between two points in the ocean that detours around the islands. Experimental results indicate that the proposed method reduces the distance between rescue ships and each accident site by 5.0 km compared to the original rescue ship locations. Thus, rescue time is reduced. [ABSTRACT FROM AUTHOR]