Learning for Prediction of Maritime Collision Avoidance Behavior from AIS Network

Po Ruey Lei, Pei Rong Yu, Wen Chih Peng

研究成果: Conference contribution同行評審

3 引文 斯高帕斯(Scopus)

摘要

With the rapid increase in global maritime shipping, there is a great demand for the technology of maritime traffic monitoring to detect inappropriate encountering interaction between ships and prevent ship collision accidents. The Automatic Identification System (AIS) network makes it possible to collect a large volume of maritime traffic data and investigate the collision avoidance behavior of real-world ships. Most collision avoidance systems are based on expert systems and simulations based on the International Regulations for Preventing Collisions at Sea (COLREGs). Those regulations outline the general principles underlying collision avoidance; however, they do not provide specific guidance and fail to account for the complexity of many real-world situations. Furthermore, guidance systems coordinating the movement of a ship must have the capacity to predict the movement behavior of all ships involved in potential encounter situations, and do so as early as possible for anti-collision reaction. Our objective in this study was to model the collision avoidance behaviors of human operators in order to formulate a set of realistic trajectory predictions for encountering near collision scenarios. By machine learning approach, the proposed framework is able to learn a model of interaction movement behavior from collected AIS historical traffic data involving near collision situations and then generate a set of predicted trajectories while ships encountering. The proposed model eliminates the need for a priori information related to environmental conditions and the rules governing encounter situations. The resulting projections can be used to suggest anti-collision paths for navigators or to guide the selection of collision-free paths for maritime autonomous surface ships.

原文English
主出版物標題2021 22nd Asia-Pacific Network Operations and Management Symposium, APNOMS 2021
發行者Institute of Electrical and Electronics Engineers Inc.
頁面222-225
頁數4
ISBN(電子)9784885523328
DOIs
出版狀態Published - 8 9月 2021
事件22nd Asia-Pacific Network Operations and Management Symposium, APNOMS 2021 - Virtual, Online, Taiwan
持續時間: 8 9月 202110 9月 2021

出版系列

名字2021 22nd Asia-Pacific Network Operations and Management Symposium, APNOMS 2021

Conference

Conference22nd Asia-Pacific Network Operations and Management Symposium, APNOMS 2021
國家/地區Taiwan
城市Virtual, Online
期間8/09/2110/09/21

指紋

深入研究「Learning for Prediction of Maritime Collision Avoidance Behavior from AIS Network」主題。共同形成了獨特的指紋。

引用此