Ship abnormal behaviour detection based on AIS data at the approach to ports

IF 11 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Reliability Engineering & System Safety Pub Date : 2025-09-11 DOI:10.1016/j.ress.2025.111712

Dapei Liu, C. Guedes Soares

{"title":"Ship abnormal behaviour detection based on AIS data at the approach to ports","authors":"Dapei Liu, C. Guedes Soares","doi":"10.1016/j.ress.2025.111712","DOIUrl":null,"url":null,"abstract":"<div><div>This study proposes a novel framework for abnormal ship behaviour detection, extracting traffic characteristics in port approach waters from collected Automatic Identification System (AIS) data and establishing corresponding anomaly indicators to measure the degree of abnormal vessel behaviour. The method involves shipping route modelling, which consists of route centreline definition and boundaries quantification. Then, the constructed model is applied to the extraction of traffic position characteristics and the generation of GraphSAGE-based dynamic transportation patterns. Subsequently, the optimal distribution-based abnormal indicators of position, Speed Over Ground, and Course Over Ground are developed with the extracted position characteristics and generated dynamic patterns. The effectiveness of the proposed study is validated with the outbound behaviour abnormal indicators of Leixões port in Portugal. The results show objectively, effectively, and interpretably that the method quantifies vessel behaviour anomalies based on local traffic characteristics.</div></div>","PeriodicalId":54500,"journal":{"name":"Reliability Engineering & System Safety","volume":"266 ","pages":"Article 111712"},"PeriodicalIF":11.0000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Reliability Engineering & System Safety","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0951832025009123","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}

引用次数: 0

Abstract

This study proposes a novel framework for abnormal ship behaviour detection, extracting traffic characteristics in port approach waters from collected Automatic Identification System (AIS) data and establishing corresponding anomaly indicators to measure the degree of abnormal vessel behaviour. The method involves shipping route modelling, which consists of route centreline definition and boundaries quantification. Then, the constructed model is applied to the extraction of traffic position characteristics and the generation of GraphSAGE-based dynamic transportation patterns. Subsequently, the optimal distribution-based abnormal indicators of position, Speed Over Ground, and Course Over Ground are developed with the extracted position characteristics and generated dynamic patterns. The effectiveness of the proposed study is validated with the outbound behaviour abnormal indicators of Leixões port in Portugal. The results show objectively, effectively, and interpretably that the method quantifies vessel behaviour anomalies based on local traffic characteristics.

查看原文本刊更多论文

基于AIS数据的船舶进港异常行为检测

本研究提出了一种新的船舶异常行为检测框架，从收集的AIS数据中提取港口进近水域的交通特征，并建立相应的异常指标来衡量船舶异常行为的程度。该方法涉及航线建模，包括航线中心线定义和边界量化。然后，将构建的模型应用于交通位置特征提取和基于graphsage的动态交通模式生成。然后，利用提取的位置特征和生成的动态模式，建立基于最优分布的位置、对地速度和对地航向异常指标。通过葡萄牙Leixões港口的出站行为异常指标验证了所提出研究的有效性。结果表明，该方法能够客观、有效、可解释地量化基于局部交通特征的船舶行为异常。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Reliability Engineering & System Safety 管理科学-工程：工业

CiteScore

15.20

自引率

39.50%

发文量

621

审稿时长

67 days

期刊介绍： Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.