|
|
|
|
|
Tanja Brcko and Bla? Luin
The increasing traffic and complexity of navigation at sea require advanced decision support systems to ensure greater safety. In this study, we propose a novel decision support system that employs fuzzy logic to improve situational awareness and to assi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Bo Xiang and Yongqiang Zhuo
Effective and timely collision avoidance decision support is essential for super-large vessels navigating in port waters. To guarantee the navigational safety of super-large vessels, this work proposes a collision avoidance decision support method based ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xiaoyuan Wang, Gang Wang, Quanzheng Wang, Junyan Han, Longfei Chen, Bin Wang and Huili Shi
As one of the key technologies restricting the development of intelligent ships, autonomous collision avoidance has attracted the attention of many scholars all over the world. Existing research on collision-avoidance behavior focuses more on collision r...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ke Zhang, Liwen Huang, Xiao Liu, Jiahao Chen, Xingya Zhao, Weiguo Huang and Yixiong He
In the last few years, autonomous ships have attracted increasing attention in the maritime industry. Autonomous ships with an autonomous collision avoidance capability are the development trend for future ships. In this study, a ship manoeuvring process...
ver más
|
|
|
|
|
|
|
|
|
|
|
Weifeng Li, Lufeng Zhong, Yang Xu and Guoyou Shi
The traditional ship collision risk index model based on the distance at the closest point of approach (DCPA) and the time to the closest point of approach (TCPA) is insufficient for estimating ship collision risk and planning collision avoidance operati...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jinwan Park and Jung-Sik Jeong
According to the statistics of maritime collision accidents over the last five years (2016?2020), 95% of the total maritime collision accidents are caused by human factors. Machine learning algorithms are an emerging approach in judging the risk of colli...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yingjun Hu, Anmin Zhang, Wuliu Tian, Jinfen Zhang and Zebei Hou
Most maritime accidents are caused by human errors or failures. Providing early warning and decision support to the officer on watch (OOW) is one of the primary issues to reduce such errors and failures. In this paper, a quantitative real-time multi-ship...
ver más
|
|
|
|
|
|