Dynamic game collision avoidance decision-making for autonomous and manned ships
ObjectiveThis study investigates the interactive collision avoidance (CA) problem of autonomous and manned ships in mixed navigation scenarios in order to achieve the efficient collision avoidance and safe navigation of ships. To this end, a multi-agent interactive ship dynamic game collision avoida...
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Format: | Article |
Language: | English |
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Editorial Office of Chinese Journal of Ship Research
2024-02-01
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Series: | Zhongguo Jianchuan Yanjiu |
Subjects: | |
Online Access: | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.03305 |
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author | Hao CUI Xinyu ZHANG Jing WANG Chengbo WANG Kangjie ZHENG |
author_facet | Hao CUI Xinyu ZHANG Jing WANG Chengbo WANG Kangjie ZHENG |
author_sort | Hao CUI |
collection | DOAJ |
description | ObjectiveThis study investigates the interactive collision avoidance (CA) problem of autonomous and manned ships in mixed navigation scenarios in order to achieve the efficient collision avoidance and safe navigation of ships. To this end, a multi-agent interactive ship dynamic game collision avoidance decision-making method is proposed. MethodsAccording to sailing practices, the ship collision avoidance problem in mixed navigation environments is analyzed and understood, and the ship encounter situation and collision risk are quantified on the basis of the International Regulations for Preventing Collisions at Sea (COLREGs). Dynamic game theory is introduced to model individual ships with collision risk as participants with independent thinking in the game, and the course changes of ships are taken as the strategy for determining the optimal action sequence under the constraints of ship safety and social and economic benefits. Different ship maneuvering modes are introduced to the simulation experiment, and the effectiveness of the collision avoidance decision-making method is verified using Python. ResultsThe results show that this method can realize the safe encounter of multiple ships in a mixed navigation environment of autonomous and manned ships, and each ship can adjust its behavior strategy to achieve safe avoidance when facing target ships with different sailing styles. ConclusionThis study can provide valuable references for the collision avoidance decision-making of autonomous and manned ships. |
first_indexed | 2024-04-24T22:39:17Z |
format | Article |
id | doaj.art-8d7198f94b5c407889678608c9329402 |
institution | Directory Open Access Journal |
issn | 1673-3185 |
language | English |
last_indexed | 2024-04-24T22:39:17Z |
publishDate | 2024-02-01 |
publisher | Editorial Office of Chinese Journal of Ship Research |
record_format | Article |
series | Zhongguo Jianchuan Yanjiu |
spelling | doaj.art-8d7198f94b5c407889678608c93294022024-03-19T06:34:50ZengEditorial Office of Chinese Journal of Ship ResearchZhongguo Jianchuan Yanjiu1673-31852024-02-0119123824710.19693/j.issn.1673-3185.03305ZG3305Dynamic game collision avoidance decision-making for autonomous and manned shipsHao CUI0Xinyu ZHANG1Jing WANG2Chengbo WANG3Kangjie ZHENG4Navigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaNavigation College, Dalian Maritime University, Dalian 116026, ChinaObjectiveThis study investigates the interactive collision avoidance (CA) problem of autonomous and manned ships in mixed navigation scenarios in order to achieve the efficient collision avoidance and safe navigation of ships. To this end, a multi-agent interactive ship dynamic game collision avoidance decision-making method is proposed. MethodsAccording to sailing practices, the ship collision avoidance problem in mixed navigation environments is analyzed and understood, and the ship encounter situation and collision risk are quantified on the basis of the International Regulations for Preventing Collisions at Sea (COLREGs). Dynamic game theory is introduced to model individual ships with collision risk as participants with independent thinking in the game, and the course changes of ships are taken as the strategy for determining the optimal action sequence under the constraints of ship safety and social and economic benefits. Different ship maneuvering modes are introduced to the simulation experiment, and the effectiveness of the collision avoidance decision-making method is verified using Python. ResultsThe results show that this method can realize the safe encounter of multiple ships in a mixed navigation environment of autonomous and manned ships, and each ship can adjust its behavior strategy to achieve safe avoidance when facing target ships with different sailing styles. ConclusionThis study can provide valuable references for the collision avoidance decision-making of autonomous and manned ships.http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.03305mixed navigation scenarioship collision avoidancemaneuvering modegame theory |
spellingShingle | Hao CUI Xinyu ZHANG Jing WANG Chengbo WANG Kangjie ZHENG Dynamic game collision avoidance decision-making for autonomous and manned ships Zhongguo Jianchuan Yanjiu mixed navigation scenario ship collision avoidance maneuvering mode game theory |
title | Dynamic game collision avoidance decision-making for autonomous and manned ships |
title_full | Dynamic game collision avoidance decision-making for autonomous and manned ships |
title_fullStr | Dynamic game collision avoidance decision-making for autonomous and manned ships |
title_full_unstemmed | Dynamic game collision avoidance decision-making for autonomous and manned ships |
title_short | Dynamic game collision avoidance decision-making for autonomous and manned ships |
title_sort | dynamic game collision avoidance decision making for autonomous and manned ships |
topic | mixed navigation scenario ship collision avoidance maneuvering mode game theory |
url | http://www.ship-research.com/en/article/doi/10.19693/j.issn.1673-3185.03305 |
work_keys_str_mv | AT haocui dynamicgamecollisionavoidancedecisionmakingforautonomousandmannedships AT xinyuzhang dynamicgamecollisionavoidancedecisionmakingforautonomousandmannedships AT jingwang dynamicgamecollisionavoidancedecisionmakingforautonomousandmannedships AT chengbowang dynamicgamecollisionavoidancedecisionmakingforautonomousandmannedships AT kangjiezheng dynamicgamecollisionavoidancedecisionmakingforautonomousandmannedships |