Research on collision Avoidance Path Planning of Inland Waterway Vessels Based on Deep Learning Technology

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.