|
|
|
Ye Xiao, Yupeng Hu, Jizhao Liu, Yi Xiao and Qianzhen Liu
Ship trajectory prediction is essential for ensuring safe route planning and to have advanced warning of the dangers at sea. With the development of deep learning, most of the current research has explored advanced prediction methods based on historical ...
ver más
|
|
|
|
|
|
|
João N. Ribeiro da Silva, Tiago A. Santos and Angelo P. Teixeira
This paper develops a methodology to estimate ship emissions using Automatic Identification System data (AIS). The methodology includes methods for AIS message decoding and ship emission estimation based on the ship?s technical and operational characteri...
ver más
|
|
|
|
|
|
|
Zhaojin Yan, Guanghao Yang, Rong He, Hui Yang, Hui Ci and Ran Wang
Automatic identification systems (AIS) provides massive ship trajectory data for maritime traffic management, route planning, and other research. In order to explore the valuable ship traffic characteristics contained implicitly in massive AIS data, a sh...
ver más
|
|
|
|
|
|
|
Xinyu Wang and Yingjie Xiao
The rapid growth of ship traffic leads to traffic congestion, which causes maritime accidents. Accurate ship trajectory prediction can improve the efficiency of navigation and maritime traffic safety. Previous studies have focused on developing a ship tr...
ver más
|
|
|
|
|
|
|
Pedro Pintor, Manuel Lopez-Martinez, Emilio Gonzalez, Jan Safar and Ronan Boyle
Global Navigation Satellite System (GNSS) technology supports all phases of maritime navigation and serves as an integral component of the Automatic Identification System (AIS) and, by extension, Vessel Traffic Service (VTS) systems. However, the accurac...
ver más
|
|
|
|
|
|
|
Miro Petkovic, Igor Vujovic, Zvonimir Lu?ic and Jo?ko ?oda
Automated surveillance systems based on machine learning and computer vision constantly evolve to improve shipping and assist port authorities. The data obtained can be used for port and port property surveillance, traffic density analysis, maritime safe...
ver más
|
|
|
|
|
|
|
Daping Xi, Yuhao Feng, Wenping Jiang, Nai Yang, Xini Hu and Chuyuan Wang
The extraction of ship behavior patterns from Automatic Identification System (AIS) data and the subsequent prediction of travel routes play crucial roles in mitigating the risk of ship accidents. This study focuses on the Wuhan section of the dendritic ...
ver más
|
|
|
|
|
|
|
Irina Sirkova
Two clear-air over-the-horizon propagation mechanisms affecting the Automatic Identification System (AIS) detection range are considered. Comparison results are presented between the path loss due to tropospheric ducting and path loss due to tropospheric...
ver más
|
|
|
|
|
|
|
Zihao Liu, Zhaolin Wu, Zhongyi Zheng, Xianda Yu, Xiaoxuan Bu and Wenjun Zhang
In recent years, the increasing volume and complexity of ship traffic has raised the probability of collision accidents in ports, waterways, and coastal waters. Due to the relative rarity of collision accidents, near misses have been used in the research...
ver más
|
|
|
|
|
|
|
Chang Liu, Shize Zhang, Lufang Cao and Bin Lin
Automatic identification system (AIS) data record a ship?s position, speed over ground (SOG), course over ground (COG), and other behavioral attributes at specific time intervals during a ship?s voyage. At present, there are few studies in the literature...
ver más
|
|
|
|