Zhanshuo Zhang , Hengchao Zhao , Jiawei Wang , Hongbo Wang
{"title":"Efficient collaborative collision avoidance algorithm considering COLREGs in complex multi-ship encounter scenarios","authors":"Zhanshuo Zhang , Hengchao Zhao , Jiawei Wang , Hongbo Wang","doi":"10.1016/j.apor.2025.104753","DOIUrl":null,"url":null,"abstract":"<div><div>In recent years, the issue of autonomous ship collision avoidance has attracted widespread attention. Although various automatic collision avoidance algorithms have been proposed, the development of decision-making systems for collision avoidance in complex multi-ship encounter scenarios and in cases where the target ship’s motion is uncertain has not received sufficient attention. To address this gap, the study considers the uncertainty in the velocity observations of other vessels and proposes a time-interactive ship domain model to assess collision risks. Combining the maneuvering characteristics of ships, a dual time-scale domain model is proposed to accurately determine the timing for evasive maneuvers. Based on collision avoidance regulations, a role-symmetric encounter situation classification algorithm is developed to clarify the coordinated actions in multi-ship encounter scenarios. Moreover, a velocity obstacle primitive method constrained by ship dynamics is proposed to generate real-time evasive actions. The experimental results show that the proposed autonomous ship collision avoidance decision-making algorithm not only ensures navigation safety but also demonstrates high decision-making efficiency, coordinating the actions in multi-ship encounters to provide safe and efficient collision avoidance strategies.</div></div>","PeriodicalId":8261,"journal":{"name":"Applied Ocean Research","volume":"163 ","pages":"Article 104753"},"PeriodicalIF":4.4000,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Ocean Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0141118725003396","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, OCEAN","Score":null,"Total":0}
引用次数: 0
Abstract
In recent years, the issue of autonomous ship collision avoidance has attracted widespread attention. Although various automatic collision avoidance algorithms have been proposed, the development of decision-making systems for collision avoidance in complex multi-ship encounter scenarios and in cases where the target ship’s motion is uncertain has not received sufficient attention. To address this gap, the study considers the uncertainty in the velocity observations of other vessels and proposes a time-interactive ship domain model to assess collision risks. Combining the maneuvering characteristics of ships, a dual time-scale domain model is proposed to accurately determine the timing for evasive maneuvers. Based on collision avoidance regulations, a role-symmetric encounter situation classification algorithm is developed to clarify the coordinated actions in multi-ship encounter scenarios. Moreover, a velocity obstacle primitive method constrained by ship dynamics is proposed to generate real-time evasive actions. The experimental results show that the proposed autonomous ship collision avoidance decision-making algorithm not only ensures navigation safety but also demonstrates high decision-making efficiency, coordinating the actions in multi-ship encounters to provide safe and efficient collision avoidance strategies.
期刊介绍:
The aim of Applied Ocean Research is to encourage the submission of papers that advance the state of knowledge in a range of topics relevant to ocean engineering.