Ship Collision Risk Research Articles

An Improved Danger Sector Model for Identifying the Collision Risk of Encountering Ships

In order to avoid collision, ships usually take collision avoidance manoeuvres, such as course alteration. However, the effect of such a manoeuvre is influenced by ship manoeuvrability. This paper proposed an improved danger sector model to identify the collision risk between two encountering ships. The proposed model is improved from the danger sector model, which is based on a course alteration manoeuvre by taking ship manoeuvrability into consideration. To involve ship manoeuvrability in the proposed model, the turning circle of a ship is determined when it calculates the size of the danger sector. For validating the proposed model, the Automatic Identification System (AIS) data in the northern Yellow Sea of China were used to carry out some experiments of different encountering scenarios. The results show that the proposed improved danger sector model can identify the collision risk between two encountering ships effectively and has advantages compared with the original danger sector model. The proposed model can help mariners and maritime surveillance operators have a more accurate and effective assessment of ship collision risk in the water area, which can contribute to the improvement of navigational safety.

Application of Formal Safety Assessment for Ship Collision Risk Analysis in Surabaya West Access Channel

In 2019, ship density of Surabaya West Access Channel reached 28,112 ships. The high number of vessel densities that exist in Surabaya West Access Channel (APBS), it is possible for ship collisions to occur. In this study, Formal Safety Assessment used for ship collision Risk Analysis in Surabaya West Access Channel (APBS). Formal Safety Assessment is a structured and systematic methodology developed by the International Maritime Organization (IMO) used to conduct risk assessments and also evaluates cost-benefit assessments to get some recommendations to improve safety in the maritime world, including protection of life, health, the marine environment, and property. To achieve the above objectives, IMO’s guidelines on the application should comprise the following steps; First step, Hazard Identification using Event Tree Analysis based on historical accident data. The second step, risk analysis is composed of two main activities: frequency calculating and consequence modeling. The frequency of ship collision was calculated using Traffic Based Model and for the consequence, Ansys software was used to model the structural damage of hull caused by the incident. The third step, Risk Control Option is used to get some options to prevent collisions. The fourth step, Cost-Benefit Assessment is used to identify and compare benefits and costs associated with the implementation of each RCO using Net Cost of Averting a Fatality (NCAF) and Gross Cost of Averting a Fatality (GCAF) Criteria. The last step of Formal Safety Assessment (FSA) is Recommendations for Decision-Making to get some options for mitigation.

Towards a Convolutional Neural Network model for classifying regional ship collision risk levels for waterway risk analysis

Estimating the navigational risk of vessels operating in sea and waterway areas is important for waterway risk management and pollution preparedness and response planning. Existing methods relying on a model-informed expert judgment of ship-ship collision risk are of limited practical use because periodic risk monitoring is feasible only when this can be done without extensive use of organizational resources. To alleviate such limitations, this article presents a new approach based Convolutional Neural Networks (CNNs) and image recognition to interpret and classify ship-ship collision risks in encounter scenarios. The specific aim of the article is to investigate whether a CNN-based model can quickly and accurately interpret images constructed based on data from the Automatic Identification System (AIS) in terms of collision risk. To test this, estimates derived from training data are compared to validation data. It is also investigated whether adding additional navigational information based on AIS data improves the model's predictive accuracy. A case study with data from the Baltic Sea area is implemented, where various model design alternatives are tested as a proof-of-concept. The main finding of this work is that a CNN-based approach can indeed meet the specified design requirements, suggesting that this is a fruitful direction for future work. Several issues requiring further research and developed are discussed, with the validity of the risk ratings underlying the image classification seen as the most significant conceptual challenge before a CNN-model can be put to practical use.

Early Warning Method and Model of Inland Ship Collision Risk Based on Coordinated Collision-Avoidance Actions

To reduce the occurrence of ship collisions, immediate danger, and close-quarters situations in narrow inland waterways, a step-by-step early warning system for ship collision-avoidance actions was developed, along with an early warning method and model of collision risk based on coordinated collision-avoidance actions. This study first analyzed the importance of coordinated collision-avoidance actions in inland waterways, and the process and key components of coordinated collision-avoidance actions were studied. Then, the early warning method of inland ship collision risk based on coordinated collision-avoidance actions was introduced; the effectiveness of the early warning method was comparatively analyzed via experimental observations. A framework of early warning model of inland ship collision risk was created based on the early warning method; a collision risk early warning model for inland ships based on coordinated collision-avoidance actions was proposed according to the relationship between the distance/time to the closest point of approach (DCPA, TCPA), coordination degree of collision-avoidance actions of the two considered ships and collision risk; moreover, the early warning model of inland ship collision risk was further considered for quantitative calculation. Finally, the application of the early warning method and model was demonstrated using a case study. The results indicate that the early warning method of inland ship collision risk based on coordinated collision-avoidance actions could effectively reduce the emergence of close-quarters situations and immediate danger, and the early warning model could quantitatively show the evolution of collision risk of two ships along with the process of coordinated collision-avoidance actions.

On the Use of the Hybrid Causal Logic Methodology in Ship Collision Risk Assessment

A ship collision accident is one of the most dangerous and common types of maritime accidents. Traditional probabilistic risk assessment (PRA) of ship collision accidents is a methodology that can be adopted to ensure maritime safety. Nevertheless, a need for better approaches to model human behavior, such as risk identification, communication, and decision-making, has been identified. Such advanced PRA methods require a more explicit way of taking human factors into consideration than the traditional risk assessment methods. Hybrid causal logic (HCL) is an advanced PRA method due to its unique three-level framework that includes event sequence diagrams, fault trees, and Bayesian networks, which makes it suitable for modeling human behavior that is important to ship collision accidents. This paper discusses the applicability of the HCL methodology for the ship collision accident. Firstly, the event sequences of typical ship collision accidents are summarized based on the study of 50 accident investigation reports. Then, fault trees for mechanical failure events and the Bayesian networks for human error events are constructed to analyze the events in a structured way at a more detailed level. Finally, the three main end-state types of ship collision avoidance scenario have been quantified. The result of the probability of a ship collision accident is verified by estimating the annual frequency of collision accidents in the Singapore Strait. Comparing with the historical data, the estimation results are quite near to the real case. By taking advantage of the HCL methodology, the modeling of ship collision scenarios can be carried out at a deep logical level. At the same time, it is possible to combine a detailed analysis of various primary events with a comprehensive analysis at the system level.

Discussion on the article by Zhang & Meng entitled “Probabilistic ship domain with applications to ship collision risk assessmentˮ [Ocean Eng. 186 (2019) 106130

Discussion on the article by Zhang & Meng entitled “Probabilistic ship domain with applications to ship collision risk assessmentˮ [Ocean Eng. 186 (2019) 106130

Response to the discussion by Montewka Jaku, Gil Mateusz and Wróbel Krzysztof on the article by Zhang & Meng entitled “Probabilistic ship domain with applications to ship collision risk assessment [Ocean Eng. 186 (2019) 106130

This note aims to address the concerns and confusions raised by Jakub et al. (2020) on the article of Zhang and Meng published in Ocean Engineering in 2019. Zhang and Meng (2019) mainly proposed the probabilistic ship domain to capture the diverse navigational behaviors of captains based on the big AIS data with less emphasies on how to assess ship collision risk using the probabilistic ship domain. To achieve of the aim, we first examine two concepts of ideal ship domain and practical ship domain. We proceed to investigate the relationship between ship domain and ship collision risk using field data from restricted water in both Singapore strait and fairway. We finally discuss the onboard collision detection by using the probabilistic ship domain incorporating with the Closest Point of Approach (CPA). This note not only clarifies some confusions or misunderstandings of the applicaion of probabilistic ship domain for ship collision risk assessment bust also exhibits the values and merits of the probabilistic ship domain.

Key technologies of 3D scene construction for remote assisted driving of intelligent ships

Objectives In order to realize the shore-based remote monitoring and management of the whole life cycle of intelligent ship navigation, this paper studies a virtual reality (VR)-based remote assisted driving support system for ships. Methods Through the real-time acquisition and fusion of ship situation information regarding navigation, and the dynamic and static target information of the ship, VR technology is used to reconstruct and present a navigation scene in way of omni-direction and multiple angle of view, a ship collision risk prediction model is established and the three-dimensional dynamic display of the navigation risk relationship between surrounding ships is created. Results The system can accurately display the real scene and state information of the ships during voyage, and provide a three-dimensional and multi-perspective look-out function. It not only provides comprehensive navigation information for ship pilots, but also achieves shore-based remote assistance driving support. Conclusions The results of this study can provide technical support and guarantees for the construction of integrated ship-shore intelligent systems.

Spatial topological analysis model of ship encounter space

This paper proposes a topological analysis model of ship encounter space using a geographic information system (GIS) spatial analysis technology. Herein, the characteristics of the elements, organization, and structure of the ship encountered in the sea were studied to solve problems of ship collision risk analysis. In this model, it is necessary to construct the topological structure of the ship-encounter space based on the risk situation of the ship. The topological points and connection lines established in the encounter space were analyzed using the shape and geometric relationship of the ship's space topology, and the collision danger in the ship's navigation is, thus, analyzed. Moreover, information regarding the dangerous ship target and encounter characteristics were calculated and extracted. This study uses the model to conduct a simulation based on data from the collision between M/T Sanchi and M/V CF Crystal on January 06, 2018, and analyzes the collision risk characteristics during the two periods prior to the collision. Results show that the proposed model is effective and feasible for marine vessel safety analysis.

A SVM based ship collision risk assessment algorithm

Ship collision is one of the important causes of maritime accidents. Collision risk assessment is necessary for navigator or automatic navigating system to recognize the risk when facing a specific encounter situation and make the proper decision for the following collision avoidance. This paper proposes a quantitative ship collision risk assessment algorithm that is based on support vector machine (SVM) technology. The algorithm reconsiders the margin between ship domains of own ship (OS) and the target ship (TS) that is used to model the probability of collision. Moreover, the consequence of the assumed collision is also considered in the algorithm, which is modeled by the interaction force. Thus, the continuous and quantitative collision risk can be obtained by using the states of ships so that some weaknesses of the conventional risk assessment methods such as the ship domain (SD) methods and the closest point of approach (CPA) based methods can be overcome. The effectiveness of this approach is examined by simulation studies which show the advantages of the new risk assessment algorithm.

Visualization of Ship Collision Risk in the Inland Bridge Waterway Based on the Maritime Traffic Simulation

The collision risk is increasing in inland bridge waterways given that the restrictive waterway and many of obstructions. It is crucial for seafarers and supervisors to identify the high-risk areas in a bridge waterway. This paper takes the Wuhan Bridge Waterway in the Yangtze River as a case. In accordance with the maritime traffic simulation, the potential collision frequency and its distribution are obtained in order to evaluate the risk in different areas of the case waterway. The nautical routes with respect to the ships passing the waterway and ferryboats crossing over the waterway are then modeled. A collision detecting method is proposed to obtain the collision information extracted from the simulation data. This collision information is visualized in order to illustrate the collision risk in each area. The high risk sites can be illustrated by the proposed method in order to assist the maritime supervisors in paying pointed attentions to the identified sensitive areas.

Identification of collision risk factors perceived by ship operators in a vessel encounter situation

This study aims to elucidate the possible risk factors considering the point of view of a ship operator by identifying the maximum collision risk-bearing angle (MCRBA) and the distance at which the collision risk begins to increase significantly (DCRBIS), which are key factors affecting navigation safety in real maritime environments. Using two ships at sea in various vessel encounter situations (relative bearing angles of 000°, 045°, 090°, and 135°), the perceived ship collision risk (PSCR) was estimated by the ship operators. Then, the mean values of all the measured parameters were used to identify the bearing angle corresponding to the highest PSCR. The MCRBA was compared to the maximum frequency collision bearing angle (MFCBA) derived by investigating 200 reported ship collision cases in Korean waters. The highest experimental PSCR values were observed at a relative bearing angle of 135°, which corresponded to the results of collision case analyses stating that the MFCBA was equal to 112.5°–135°. Notably, the PSCR magnitude increased most significantly at a distance of 1.25–1 NM in experiments involving various vessel encounter situations. Collision risk factors such as the MCRBA and DCRBIS can thus be used in the development of collision prevention protocols for ship operators.

Research and Application of Real-time Ship Traffic Intelligent Analysis and Calculation Platform under 5G Background

In the current navigation process, ships often encounter ship collision risk due to the lack of real-time channel information. In order to effectively avoid the collision risk of the ship, relevant researchers conduct research and development through VHF communication technology, satellite communication and GPS navigation and other mature technologies, aiming to build a complete marine ship navigation system. Although the application of this technology improves the disadvantageous situation of ship navigation to a certain extent, while it cannot accurately predict the route risk and real-time information about the ship.With the commercial promotion of 5G network technology, by integrating 5G network technology into the process of ship navigation. On this basis, a special 5G communication ship traffic intelligent analysis platform is built, which can fundamentally strengthen the intelligence of ship navigation information collection and information collection. Through the content and construction of the 5G network, the information within the industry and between socially relevant departments can be exchanged and closely connected to avoid the generation of isolated information islands; and the scientific construction of information management can be achieved to effectively avert the risks of maritime navigation and practical to make sure the safety of ships sailing in dangerous waters has been strengthened.

Modelling ship collision risk based on the statistical analysis of historical data: A case study in Hong Kong waters

Collision, as a common type of ship accidents, leads to serious property loss and personal injury. In this paper, a new framework of quantitative risk assessment is proposed by quantifying the probability and the corresponding consequence based on the historical accident data. Firstly, the consequences of ship collisions are quantified and classified using an equivalent consequence method. Secondly, a decision tree model is established to analyse the impact of ship attributes on the collision consequences. The main ship attributes contributing to collision are determined, based on which, a BP neural network model is developed to estimate the probabilities of the different consequences. Thirdly, the collision risk is predicted by integrating the collision probabilities with the corresponding consequences. Fourthly, a case study in Hong Kong waters is investigated and the results are compared with the available references to validate the proposed framework. The new model can be used to assess present risks to plan preventive measures for the potential collision accidents.

Modeling of Ship Collision Risk Based on Cloud Model

Existing models for assessing ship collision risk involve complex calculations that complicate the simultaneous qualitative and quantitative analysis of the factors affecting ship navigation safety. Therefore, these models often exhibit slow generation of the risk index and evaluation results with reduced accuracy. To resolve these issues, we model the ship collision risk based on the cloud model theory. Specifically, we select “distance of closest point of approach (DCPA)” and “time to closest point of approach (TCPA)” as the main factors affecting the ship collision risk and analyze the data of DCPA, TCPA, and collision risk index (CRI) based on their cloud models. By combining these analyses with a double-condition-single-rule generator, we construct a cloud model for ship collision risk and finally develop a cloud model-based inference engine system to assess ship collision risk. This engine allows us to establish different ship collision risk analysis models according to the scenario encountered by the ship, which can be used to verify the feasibility of the proposed algorithm for ship collision risk modeling. Through comparisons with traditional ship collision risk models, the proposed ship collision risk model is found to be superior owing to its simple implementation, accurate results, and shorter time required to generate the risk model. The model established in this study enables the crew to determine the key objects to be avoided in case of potential collision with multiple ships. At last,analysis and research of cloud model ship collision risk based on global sensitivity and uncertainty are done to reduce the dimension of the risk parameters and show the main factors of unstable collision risk,therefore,the uncertain results in the calculation of the degree of danger are avoided, some reasonable suggestions are proposed for real navigation safety. the maritime pilot can make correct decisions promptly to reduce or avoid the occurrence of collision accidents.

A New Approach for Probabilistic Risk Assessment of Ship Collision with Riverside Bridges

The configuration of riverside bridges, such as the spatial distribution, wading status, and ship accessibility of piers, is generally different from river‐crossing bridges. Thus, the ship collision risk of riverside bridges cannot be assessed using conventional assessment methods applicable to river‐crossing bridges. The aim of this paper is, therefore, to develop a new probabilistic method for assessing the risk of ship collision with riverside bridges. First, a fully probabilistic framework for assessing the ship‐bridge collision risk is presented. Second, a new probabilistic hazard analysis model of ship collision with riverside bridges is proposed, based on a combined study of riverside bridge characterization and an improved yaw ship collision model. A simplified empirical model for evaluating ship‐bridge collision force is then adopted, and the probabilistic distribution of the collision force is obtained based on Monte Carlo simulation. Furthermore, finite element simulation is conducted to estimate the collapse probability of piers. Finally, the method developed is applied to the probabilistic assessment of ship collision risk with riverside bridges located at Shabin Road, Chongqing, China. The results show that the risk of ship‐bridge collision at Shabin Road is low to moderate. The example demonstrated indicates that the methodology introduced in this paper is capable of assessing the ship‐bridge collision risk in a concise and rapid way.

Ship Collision Risk Assessment Based on Collision Detection Algorithm

Ningbo Zhoushan port handled 1.08 billion tons cargoes in 2018 which is considered as the one of biggest ports in the world. There are more than 1 000 ships enter or depart the port per day. Therefore, it is of importance to assess the collision risk for ships passing through the harbor area. In this article, a novel approach is initially proposed to assess ship collision risk in the harbor area based on collision detection technology of ship domain using automatic identified system (AIS) data. This study aims to build a unified framework of collision risk assessment which does not need to build different models in accordance with the ship domain we selected. To clean the historical motion data of ships, a method for anomaly detection of ship static information based on autoencoder (AE) is proposed. Based on the above proposed method, the ship collision frequency can be estimated, besides, the risk area can also be determined. The results obtained from the method could provide a reference on furthering enhance the navigational safety for the Maritime and Port Authority.

Collision risk assessment based on the vulnerability of marine accidents using fuzzy logic

Based on the trend, there have been numerous researches analysing the ship collision risk. However, in this scope, the navigational conditions and external environment are ignored or incompletely considered in training or/and real situation. It has been identified as a significant limitation in the navigational collision risk assessment. Therefore, a novel algorithm of the ship navigational collision risk solving system has been proposed based on basic collision risk and vulnerabilities of marine accidents. The vulnerability can increase the possibility of marine collision accidents. The factors of vulnerabilities including bad weather, tidal currents, accidents prone area, traffic congestion, operator fatigue and fishing boat operating area are involved in the fuzzy reasoning engines to evaluate the navigational conditions and environment. Fuzzy logic is employed to reason basic collision risk using Distance to Closest Point of Approach (DCPA) and Time of Closest Point of Approach (TCPA) and the degree of vulnerability in the specific coastal waterways. Analytical Hierarchy Process (AHP) method is used to obtain the integration of vulnerabilities. In this paper, vulnerability factors have been proposed to improve the collision risk assessment especially for non-SOLAS ships such as coastal operating ships and fishing vessels in practice. Simulation is implemented to validate the practicability of the designed navigational collision risk solving system.

An Improved Ship Collision Risk Evaluation Method for Korea Maritime Safety Audit Considering Traffic Flow Characteristics

Ship collision accidents account for the majority of marine accidents. The collision risk can be even greater in ports where the traffic density is high and terrain conditions are difficult. The proximity assessment model of the Korea Maritime Safety Audit (KMSA), which is a tool for improving maritime traffic safety, employs a normal distribution of ship traffic to calculate the ship collision risk. However, ship traffic characteristics can differ according to the characteristics of the sea area and shipping route. Therefore, this study simulates collision probabilities by estimating the best-fit distribution function of ship traffic flow in Ulsan Port, which is the largest hazardous cargo vessel handling port in Korea. A comparison of collision probability simulation results using the best-fit function and the normal distribution function reveals a difference of approximately 1.5–2.4 times for each route. Moreover, the collision probability estimates are not accurate when the normal distribution function is uniformly applied without considering the characteristics of each route. These findings can be used to improve the KMSA evaluation method for ship collision risks, particularly in hazardous port areas.

Analisa Hazard Navigation Map terhadap Resiko Tubrukan Kapal

Hazard Navigation Map Analysis on Risk of Ship Collision (Case Study: Water way of Port of Makassar). Accidents in Indonesian Marine Transportation should be a concern of all parties that effect accumulation of dangers score from some factors, based on data from the KNKT (Komite Nasional Keselamatan Transportasi) ship accident investigation report. The collision cases were among the highest in recent years and most collisions occurred in the harbor area. The purpose of this study was to analyze and compile the danger score criteria that affect ship collision risk from several factors consisting of ship condition factors, human factors, environmental factors, machinery factors, and management factors. The research was conducted with the AHP (Analytical Hierarchy Process) method. AHP method is used to create a model of the problem that has no structure, applying to problems measurable (quantitative), as well as problems that need an opinion from expert or a complex situation or do not have a frame work. AHP stages are decomposition problem, assessment and comparison of the elements of the synthesis in priorities. The result showed that human factor is the highest priority that affects the value of danger score in Makassar Port to the value of 0.395 or 39% and management factors with the lowest priority value of 0.073 or 7.3%. While the total value of danger score in Makassar Port with AHP method is 196.95 which means at the level of a fairly safe.