Article(id=1240655141536330078, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655131507740845, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2025.03.018, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1711641600000, receivedDateStr=2024-03-29, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773724836000, onlineDateStr=2026-03-17, pubDate=1758729600000, pubDateStr=2025-09-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773724836000, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773724836000, creator=13701087609, updateTime=1773724836000, updator=13701087609, issue=Issue{id=1240655131507740845, tenantId=1146029695717560320, journalId=1240618002186551303, year='2025', volume='48', issue='3', pageStart='1', pageEnd='184', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773724833608, creator=13701087609, updateTime=1773725188865, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240656621609742880, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655131507740845, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240656621613937185, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240655131507740845, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=147, endPage=156, ext={EN=ArticleExt(id=1240655141767016818, articleId=1240655141536330078, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Research on the concept, definition and key technologies of Pan-information-based Navigation Scenario Map, columnId=1240655021340160960, journalTitle=Navigation of China, columnName=Intelligent Shipping, runingTitle=null, highlight=null, articleAbstract=

To enhance the cognitive capabilities of waterborne transportation systems for intelligent ship navigation, this study first reviews the development of electronic map systems designed for the new generation of shipping systems and summarizes the technical requirements for future map functionalities in waterborne transportation. Subsequently, the Pan-information-based Navigation Scenario Map (PNSM) is proposed as a core component of the "Navigation Brain System". The elements, characteristics, and conceptual foundations of the PNSM are analyzed, with emphasis placed on its capabilities in object-oriented modeling and computer-cognitive representation of navigational environment data. Key technologies underpinning the PNSM are further discussed, including spatiotemporal object modeling of scenario elements, hierarchical organization of all elements, dynamic association among objects, adaptive cross-domain computing for scenario data, cognitive modeling of scenario semantics, intelligent information services, and multi-dimensional dynamic visualization of the scenario map. The application process and practical effectiveness of the PNSM are illustrated using data from the Intelligent Shipping Project in the Water Network Areas of Zhejiang Province, China. Research results demonstrate that the PNSM can effectively integrate, organize, correlate, and visualize water traffic data, enabling comprehensive cognitive representation of all elements within the waterborne transportation system and their interrelationships. It provides essential technical support for the advancement of next-generation shipping systems, including intelligent navigation technologies and standardized frameworks.

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为提高船舶智能航行的水路交通系统认知能力，总结了与新一代航运系统适配的电子地图系统研究进展，提出了未来水路交通系统的地图技术需求和全息航行场景图的概念。将全息航行场景图作为“航行脑系统”的重要组成部分；解析了其的组成要素和特征内涵，重点阐述了其在通航环境信息对象化建模和机器认知表达方面的核心特征。从场景要素时空对象建模、全要素对象层次组织、全要素对象动态关联、场景自适应跨域计算、语义认知建模、场景图多维动态表达等方面探讨了全息航行场景图的关键技术，依托浙江省水网地区智能航运项目，阐述了全息航行场景图的应用实践与实际成效。结果表明：全息航行场景图可以有效汇聚、组织、关联和呈现水路交通数据，实现水路交通系统全要素及其相互关系的认知表达，为发展新一代航运系统的船舶智能航行技术和标准体系等提供重要技术支撑。

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程小东（1992—），男，博士，研究方向为智能航海，E-mail: cxd921121@whut.edu.cn

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