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计算机工程 ›› 2024, Vol. 50 ›› Issue (11): 18-37. doi: 10.19678/j.issn.1000-3428.0069893

• 智能态势感知与计算 • 上一篇    下一篇

船舶交通智能感知融合与辅助决策方法综述

韩一1, 郑懿1, 解广聪1, 彭晨飞2, 邵锦依1, 周瑞淳1, 廖杨喆1,*(), 钟毅1   

  1. 1. 武汉理工大学信息工程学院, 湖北 武汉 430070
    2. 武汉理工大学船海与能源动力工程学院, 湖北 武汉 430063
  • 收稿日期:2024-05-22 出版日期:2024-11-15 发布日期:2024-11-01
  • 通讯作者: 廖杨喆
  • 基金资助:
    国家自然科学基金(52201417)

Review of Intelligent Perception Fusion and Assisted Decision-Making Methods for Vessel Traffic

HAN Yi1, ZHENG Yi1, XIE Guangcong1, PENG Chenfei2, SHAO Jinyi1, ZHOU Ruichun1, LIAO Yangzhe1,*(), ZHONG Yi1   

  1. 1. School of Information Engineering, Wuhan University of Technology, Wuhan 430070, Hubei, China
    2. School of Naval Architecture, Ocean and Energy Power Engineering, Wuhan University of Technology, Wuhan 430063, Hubei, China
  • Received:2024-05-22 Online:2024-11-15 Published:2024-11-01
  • Contact: LIAO Yangzhe

摘要:

船舶交通智能感知与辅助决策是船舶智能交通的核心内容, 是保障未来船舶智能航行安全的重大需求。在船舶智能交通系统中, 航行信息感知与融合理解发挥着关键作用, 通过各种传感技术和信息传输、处理技术, 实时获取、分析船舶与环境等相关信息, 直接影响着船舶智能航行的态势判断和风险评估能力, 同时基于数据融合分析的辅助决策生成效果决定了船舶自主航行能力, 关系着船舶交通的安全和效率。船舶智能交通下的感知融合具有多级体系特征, 研究者在通信传输、信息交互和数据融合3个层级进行了多方面改进。深入探讨目前船舶智能交通感知与融合理解的发展和面临的挑战, 针对船舶智能航行过程中对环境目标的感知融合具有复杂动态的特点, 研究网络通信保障、感知信息交互、智能化融合分析3个层级间的相互关联关系, 分析面向复杂水域的船舶智能航行感知体系, 讨论船舶对航行环境的识别和认知能力提升的潜在空间和应用前景, 有助于为船舶航行的自主化、智能化提供技术支持, 服务于船舶交通智能化整体水平的提升。

关键词: 船舶智能交通, 船岸一体化感知, 多源信息融合, 复杂环境感知, 多源异构信息处理

Abstract:

Vessel traffic intelligent perception capability and auxiliary decision-making generation are the core components of intelligent vessel traffic systems and are significant requirements for ensuring the safety of vessel navigation. The perception of navigation information and understanding of fusion play crucial roles in intelligent vessel-traffic systems. Through various sensing, information transmission, and processing technologies, the real-time information acquisition on vessels and analysis of the environment directly affect the situational judgment and risk assessment capabilities of intelligent vessel navigation. In addition, the effectiveness of auxiliary decision-making generation based on data fusion analysis enhances autonomous vessel navigation capability, which is closely related to the safety and efficiency of vessel traffic. Perception fusion in intelligent vessel traffic exhibits multilevel system characteristics. Researchers have introduced multifaceted improvements to communication transmission, information interaction, and data fusion at three levels. This study delves into the development and challenges faced by current perception and fusion in intelligent vessel traffic by focusing on the complex and dynamic characteristics of environmental target perception fusion in intelligent vessel navigation, thereby investigating the interrelation between network communication guarantee, perception information interaction, and intelligent fusion analysis at three levels. This study analyzes intelligent navigation perception systems for vessels in complex waterways, and discusses the potential capabilities and application prospects for enhancing vessel recognition and cognitive abilities in the navigation environment. This research is expected to provide technical support for the autonomy and intelligence of vessel navigation, contributing to the overall improvement of vessel-traffic intelligence.

Key words: intelligent vessel traffic, vessel-shore integrated perception, multisource information fusion, complex environment perception, multisource heterogeneous information processing