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Research on collision Avoidance Path Planning of Inland Waterway Vessels Based on Deep Learning Technology The Yangtze River Three Gorges Navigation Administration

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Liu, Xingchen, author.
Contributor:
Cui, Jianzhang
Kong, Lingqi
Conference Name:
2025 5th International Conference on Smart City Engineering and Public Transportation (SCEPT2025) (2025-03-28 : Beijing, China)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2025
Summary:
How to realize the intelligent collision avoidance of inland waterway ships has become a hot issue in the field of transportation. The navigation status, position information and speed of inland vessels can be obtained by using the shipborne Beidou terminal and AIS, so as to realize the real-time monitoring of the ship's operation status and the real-time optimization of collision avoidance path planning. In the process of track classification and prediction, it is necessary to use deep learning algorithms to train and learn historical track data, so as to generate a model that can accurately predict future tracks, and make collision avoidance path planning decisions on this basis, so as to realize the intelligence of water traffic organization and ship collision avoidance
Notes:
Vendor supplied data
Publisher Number:
2025-99-0015
Access Restriction:
Restricted for use by site license

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