Maneuver Decision-Making Method for Ship Collision Avoidance in Chengshantou Traffic Separation Scheme Waters

Author:

He Yixiong12,Du Zijun1,Huang Liwen12,Yu Deqing1,Liu Xiao1

Affiliation:

1. School of Navigation, Wuhan University of Technology, Wuhan 430063, China

2. Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063, China

Abstract

A maneuvering decision-making model based on time series rolling and feedback compensation methods is proposed to solve the problem of high traffic risk in Chengshantou traffic separation scheme (TSS) waters. Firstly, a digital traffic environment model suitable for the TSS waters is proposed. Secondly, a navigation risk identification method in these waters is constructed based on the digitized traffic environment and situation identification model in the Chengshantou TSS waters. Thirdly, considering the requirements of the rules and good seamanship, minimum course altering is obtained by combining the collision avoidance mechanism. Lastly, a maneuvering decision-making model in the TSS waters based on time series rolling and feedback compensation methods is developed. The simulation results show that the ship can correctly identify the collision risk and appropriately obtain maneuvering decisions, and can resume the planned route under the premise of ensuring safety. When the target ships alter course or change speed, the ship can also make adaptive maneuvering decisions. In summary, the proposed method meets the requirement of safe navigation in Chengshantou waters and provides a theoretical basis for the realization of intelligent navigation in waters similar to TSS.

Funder

National Key Research and Development Program

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3