An analysis of ship collision risk parameters based on speed ship domain

2021 ◽  
Author(s):  
Yang Xu ◽  
Weifeng Li
Keyword(s):  
Collision Risk ◽  
Ship Collision ◽  
Risk Parameters

An analysis of domain-based ship collision risk parameters

2016 ◽  
Vol 126 ◽  
pp. 47-56 ◽  
Author(s):  
Rafal Szlapczynski ◽  
Joanna Szlapczynska
Keyword(s):  
Collision Risk ◽  
Ship Collision ◽  
Risk Parameters

scholarly journals An Estimation of Ship Collision Risk Based on Relevance Vector Machine

2021 ◽  
Vol 9 (5) ◽  
pp. 538
Author(s):  
Jinwan Park ◽  
Jung-Sik Jeong
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Risk Estimation ◽  
Good Method ◽  
Relevance Vector Machine ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Collision Risk ◽  
Estimation Model ◽  
Ship Collision

According to the statistics of maritime collision accidents over the last five years (2016–2020), 95% of the total maritime collision accidents are caused by human factors. Machine learning algorithms are an emerging approach in judging the risk of collision among vessels and supporting reliable decision-making prior to any behaviors for collision avoidance. As the result, it can be a good method to reduce errors caused by navigators’ carelessness. This article aims to propose an enhanced machine learning method to estimate ship collision risk and to support more reliable decision-making for ship collision risk. In order to estimate the ship collision risk, the conventional support vector machine (SVM) was applied. Regardless of the advantage of the SVM to resolve the uncertainty problem by using the collected ships’ parameters, it has inherent weak points. In this study, the relevance vector machine (RVM), which can present reliable probabilistic results based on Bayesian theory, was applied to estimate the collision risk. The proposed method was compared with the results of applying the SVM. It showed that the estimation model using RVM is more accurate and efficient than the model using SVM. We expect to support the reasonable decision-making of the navigator through more accurate risk estimation, thus allowing early evasive actions.

scholarly journals Improving Near Miss Detection in Maritime Traffic in the Northern Baltic Sea from AIS Data

2021 ◽  
Vol 9 (2) ◽  
pp. 180
Author(s):  
Lei Du ◽  
Osiris A. Valdez Banda ◽  
Floris Goerlandt ◽  
Pentti Kujala ◽  
Weibin Zhang
Keyword(s):  
Baltic Sea ◽  
Perceived Risk ◽  
Maritime Transportation ◽  
Near Miss ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Ship Collision ◽  
The Impact ◽  
Ship Behavior

Ship collision is the most common type of accident in the Northern Baltic Sea, posing a risk to the safety of maritime transportation. Near miss detection from automatic identification system (AIS) data provides insight into maritime transportation safety. Collision risk always triggers a ship to maneuver for safe passing. Some frenetic rudder actions occur at the last moment before ship collision. However, the relationship between ship behavior and collision risk is not fully clarified. Therefore, this work proposes a novel method to improve near miss detection by analyzing ship behavior characteristic during the encounter process. The impact from the ship attributes (including ship size, type, and maneuverability), perceived risk of a navigator, traffic complexity, and traffic rule are considered to obtain insights into the ship behavior. The risk severity of the detected near miss is further quantified into four levels. This proposed method is then applied to traffic data from the Northern Baltic Sea. The promising results of near miss detection and the model validity test suggest that this work contributes to the development of preventive measures in maritime management to enhance to navigational safety, such as setting a precautionary area in the hotspot areas. Several advantages and limitations of the presented method for near miss detection are discussed.

Ship Collision with Bridges

1993 ◽  
Author(s):  
Ole Damgaard Larsen
Keyword(s):  
Prevention Measures ◽  
Collision Risk ◽  
Protection Measures ◽  
Planning And Design ◽  
Federal Highway ◽  
The Usa ◽  
Ship Collision ◽  
Average Size ◽  
Existing Bridges ◽  
Vessel Impact

<p>Any struoture in navigable waters constitutes a hazard to shipping and is itself vulnerable to damage or destruction in the event of vessel collision. Worldwide vessel traffic and the average size of vessels continue to lncrease. At the same time, ever more bridges crossing navigable waterways are being planned and constructed, sometimes with inadequate navigation clearance and/or lnadequate protection. <p> The objective of this publication is to provide information and guidelinesfor engineers charged with the planning and design of new bridges, navlgation channels, and prevention and protection measures. Lt offers advice on up­grading and retrofrtting existing bridges and navigation channels. And lt provides the means to evaluate the safety of bridges, vessels, persons and the environment. <p>After reviewing some basics o! navigatlon and vessel traffic, and consider­ing risk acceptance and collision risk, the publication examines vessel impact forces on bridges and proposes appropriate bridge design criteria. Prevention measures, such as regulations and management systems. And protectlon measures and systems are also described. Major international research projects have provided the analytical basis for the publication, including the development of vessel collision guide specifi­c-atrons for the Federal Highway Administration in the USA and the vessel colllsion design crrteria developed for the Great Bell Crossing in Oenmark. <p>Prepared by Ole Damgaard LARSEN, Chairman of the IABSE Working Group "Ship Collision with Bridges'', lhis 132 page publlcation is a must for any engineer dealing with structures in navigable waters.

Hazard Identification and Probablistic Scenario Selection for Shipship Collision Accidents

2014 ◽  
Vol 156 (A1) ◽  
Keyword(s):  
Sampling Technique ◽  
Hazard Identification ◽  
Probability Density Distribution ◽  
Collision Risk ◽  
Near Misses ◽  
Different Types ◽  
Design Loads ◽  
Ship Collision ◽  
Selection For ◽  
Accident Scenarios

In collision risk-based design frameworks it is necessary to accurately define and select a set of credible scenarios to be used in the quantitative assessment and management of the collision risk between two ships. Prescriptive solutions and empirical knowledge are commonly used in current maritime industries, but are often insufficient for innovation because they can result in unfavourable design loads and may not address all circumstances of accidents involved. In this study, an innovative method using probabilistic approaches is proposed to identify relevant groups of ship-ship collision accident scenarios that collectively represent all possible scenarios. Ship-ship collision accidents and near-misses recently occurred worldwide are collated for the period of 21 years during 1991 to 2012. Collision scenarios are then described using a set of parameters that are treated individually as random variables and analysed by statistical methods to define the ranges and variability to formulate the probability density distribution for each scenario. As the consideration of all scenarios would not be practical, a sampling technique is applied to select a certain number of prospective collision scenarios. Applied examples for different types of vessels are presented to demonstrate the applicability of the method.

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

2019 ◽  
Vol 7 (12) ◽  
pp. 448 ◽  
Author(s):  
Yunja Yoo ◽  
Tae-Goun Kim
Keyword(s):  
Distribution Function ◽  
Normal Distribution ◽  
Traffic Flow ◽  
Evaluation Method ◽  
Collision Probability ◽  
Normal Distribution Function ◽  
Collision Risk ◽  
Ship Traffic ◽  
Ship Collision ◽  
Best Fit

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.

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