Objective  Sailling saftey is the chief matter for ship navigation, supposing that collision avoidance operation is heavily dependent on the captain's performance or judgement, it would pose potential risks to the ship safety. In order to coordinate all ships (tourist ships, cargo ships, etc.) in key waters and predict their routes, it is necessary to establish an anti-collision mechanism.

  Methods  Using the deep deterministic policy gradient (DDPG) algorithm and the Fujii's ship domain model, an electronic chart is used to simulate the ship's navigation route, and an improved strategy for the DDPG algorithm based on the key learning of failure regions and the improved parameters of the ship domain model according to the characteristics of tourist ships are proposed, so as to enhance the accuracy of route prediction and anti-collision.

  Results  Using the improved DDPG algorithm and ship domain model, compared with the previous algorithm, the accuracy of ship collision avoidance is raised from 84.9% to 89.7%, and the average error between the simulated and real route is reduced from 25.2 m to 21.4 m.

  Conclusion  Through the proposed ship collision avoidance path planning based on the improved DDPG algorithm and ship domain model, the supervision function of ship routes in water areas can be realized; when the predicted route intersects with other ships, the dispatcher will be alerted, realizing an effective anti-collision early warning mechanism.