scholarly journals Multi-Ship Collision Avoidance Decision-Making Based on Collision Risk Index

2020 ◽  
Vol 8 (9) ◽  
pp. 640
Author(s):  
Yingjun Hu ◽  
Anmin Zhang ◽  
Wuliu Tian ◽  
Jinfen Zhang ◽  
Zebei Hou
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Risk Analysis ◽  
Real Time ◽  
Collision Avoidance ◽  
Evaluation Method ◽  
Risk Index ◽  
Collision Risk ◽  
Ship Collision ◽  
Risk Thresholds

Most maritime accidents are caused by human errors or failures. Providing early warning and decision support to the officer on watch (OOW) is one of the primary issues to reduce such errors and failures. In this paper, a quantitative real-time multi-ship collision risk analysis and collision avoidance decision-making model is proposed. Firstly, a multi-ship real-time collision risk analysis system was established under the overall requirements of the International Code for Collision Avoidance at Sea (COLREGs) and good seamanship, based on five collision risk influencing factors. Then, the fuzzy logic method is used to calculate the collision risk and analyze these elements in real time. Finally, decisions on changing course or changing speed are made to avoid collision. The results of collision avoidance decisions made at different collision risk thresholds are compared in a series of simulations. The results reflect that the multi-ship collision avoidance decision problem can be well-resolved using the proposed multi-ship collision risk evaluation method. In particular, the model can also make correct decisions when the collision risk thresholds of ships in the same scenario are different. The model can provide a good collision risk warning and decision support for the OOW in real-time mode.

scholarly journals Navigation safety domain and collision risk index for decision support of collision avoidance of USVs

2021 ◽  
Vol 13 ◽  
pp. 340-350
Author(s):  
Jian Zhou ◽  
Feng Ding ◽  
Jiaxuan Yang ◽  
Zhengqiang Pei ◽  
Chenxu Wang ◽  
...  
Keyword(s):  
Decision Support ◽  
Collision Avoidance ◽  
Risk Index ◽  
Collision Risk ◽  
Navigation Safety

Studies on Ships Collision Avoidance with SAPSO Arithmetic

2014 ◽  
Vol 971-973 ◽  
pp. 1338-1342 ◽  
Author(s):  
Bo Tian ◽  
Wei Jie Gao ◽  
Qian Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Simulated Annealing ◽  
Collision Avoidance ◽  
Risk Index ◽  
Science Research ◽  
Collision Risk ◽  
Swarm Optimization ◽  
Index Model ◽  
Collision Prevention ◽  
Ship Collision

Vessel collision prevention issue has always been the focus of the nautical science research. This paper considers a variety of factors that affect the safety of the ship collision avoidance to optimize the research on multi-boat collision avoidance magnitude, by using the improved collision risk index model and simulated annealing particle swarm optimization. The result of the simulation indicates that SAPSO can deal with the problems of angle of avoiding collision, results are accurate and feasible.

scholarly journals A Velocity Obstacle-Based Real-Time Regional Ship Collision Risk Analysis Method

2021 ◽  
Vol 9 (4) ◽  
pp. 428
Author(s):  
Pengfei Chen ◽  
Mengxia Li ◽  
Junmin Mou
Keyword(s):  
Risk Analysis ◽  
Real Time ◽  
Human Life ◽  
Identification System ◽  
Analysis Method ◽  
Collision Risk ◽  
Time Data ◽  
Maritime Safety ◽  
Ship Collision ◽  
Velocity Obstacle

Maritime accidents such as ship collisions pose continuous risks to individuals and society with due to their severe consequences on human life, economic and environmental losses, etc. Supervising the maritime traffic in the different regions and maintaining its safety level is an essential task for stakeholders such as maritime safety administrations. In this research, a new ship collision risk analysis method is developed with the utilisation of AIS (Automatic Identification System) data. A velocity obstacle-based risk measurement is applied to measure the risk of collision between multiple ships from the velocity perspective, based on which, the collision risk and the complexity of the encounter situation are obtained at the same time. Secondly, a density-based clustering technique is introduced to identify the hotspots of ship traffic in the region as an indicator for maritime safety operators. A case study using historical AIS data was implemented to verify the effectiveness of the proposed approach in a manner that simulates the real-time data scenario. Furthermore, a comparison between existing risk analysis method is conducted to validate the proposed method.

Planning Emergency Manoeuvres

2008 ◽  
Vol 62 (1) ◽  
pp. 79-91 ◽  
Author(s):  
Rafal Szlapczynski
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Real Time ◽  
Collision Avoidance ◽  
Support System ◽  
Visualization Tool ◽  
Collision Risk ◽  
The Real ◽  
Target Behaviour ◽  
Avoidance Manoeuvre

The paper addresses the issue of planning emergency manoeuvres and re-planning ship trajectories in case of unpredicted target behaviour. It introduces two methods. The first is responsible for monitoring other ships parameters, estimating the probability of illegal target behaviour and re-planning own trajectory in case of unpredicted events. The second is a visualization tool that enables the navigator to assess collision risk in an encounter situation and choose a collision avoidance manoeuvre if necessary. This tool is based on the Collision Threat Parameters Area display and offers new features: fuzzy sectors of forbidden speed and course values and the possibility to use any given ship domain. Both methods are fast enough to be applied in the real-time decision-support system.

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.

THE RESEARCH TREND OF INFORMATION TECHNOLOGY AND DECISION MAKING IN 2009

2010 ◽  
Vol 09 (01) ◽  
pp. 1-8 ◽  
Author(s):  
YONG SHI
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Decision Support ◽  
Risk Analysis ◽  
Multiple Criteria Decision Making ◽  
Advisory Board ◽  
Research Trend ◽  
Research Topics

The research topics of the 39 papers published in the International Journal of Information Technology and Decision Making (IT&DM) in 2009 can be classified into three major directions: decision support, multiple criteria decision making, and data mining and risk analysis. The Editor-in-Chief, on behalf of the editorial board and advisory board, highlights the key ideas of these contributions. The seven papers in first issue of 2010 IT&DM are also introduced.

Managing Information for Real-Time Decision Support at Community Level

2013 ◽  
Vol 5 (1) ◽  
pp. 60-76
Author(s):  
Hakikur Rahman
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Real Time ◽  
Support System ◽  
Life Support ◽  
Human Life ◽  
Community Level ◽  
Information Support ◽  
Space Technology

Management of real time information systems is gaining importance in all sectors and facets of human life. Varying from their applications in aviation, military, government, space technology, earth science, robotics, human cognitive, life support systems, disasters and emergencies, they emerge in diversified forms and natures. This paper identifies various contexts in the decision making processes of community livelihood; contextualizes the relevant information for taking time-critical decision, conceptualizes appropriate decision making methods, tools, and technologies for proper implementation, and manages an appropriate decision support system focusing knowledge acquisition and learning. Along this perspective, the paper establishes a decision support system framework in the aspect of early warning system in reaching out to grass roots community people at their own language, sign, and interpretation; provides knowledge support during disaster management, especially during post-disaster; provides information support in agriculture related matters, focusing pest control, and pre and post harvesting issues; provides emergency health assistance support during road accidents, or emergency health cases, or epidemic breakouts; and finally provides collaborative learning to improve e-governance at community level.

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