期刊
IEEE ACCESS
卷 8, 期 -, 页码 161969-161980出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2020.3013957
关键词
Marine vehicles; Artificial intelligence; Risk management; Context modeling; Navigation; Data models; Safety; Waterway transportation; risk assessment; collision detection; ship domain; safety
资金
- Fundamental Research Funds for the Central Universities [3132020134, 3132020139]
Ningbo Zhoushan port handled 1.08 billion tons cargoes in 2018 which is considered as the one of biggest ports in the world. There are more than 1 000 ships enter or depart the port per day. Therefore, it is of importance to assess the collision risk for ships passing through the harbor area. In this article, a novel approach is initially proposed to assess ship collision risk in the harbor area based on collision detection technology of ship domain using automatic identified system (AIS) data. This study aims to build a unified framework of collision risk assessment which does not need to build different models in accordance with the ship domain we selected. To clean the historical motion data of ships, a method for anomaly detection of ship static information based on autoencoder (AE) is proposed. Based on the above proposed method, the ship collision frequency can be estimated, besides, the risk area can also be determined. The results obtained from the method could provide a reference on furthering enhance the navigational safety for the Maritime and Port Authority.
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