Objective   In order to realize the intelligent navigation and autonomous collision avoidance of unmanned ships in coastal areas, an intelligent collision avoidance decision-making method based on driving practice is proposed.

  Method   First, the real-time rationality and uniqueness of the unmanned ship intelligent collision avoidance decision-making process is analyzed. The ontology conceptual model of the navigation situation is then designed and combined with the international regulations for preventing collisions at sea (COLREGS) and good seamanship practices, and the ship encounter scenarios are quantitatively divided into 12 types. An improved composite collision risk index assessment model is then proposed from the perspective of piloting practice to reflect collision risk more accurately. Finally, an intelligent collision avoidance decision-making model based on operator's perspective (BOP) is established, and the optimal collision avoidance strategy is solved by taking the shortest total collision avoidance path as the objective function under the constraints of ship maneuverability and rudder angle amplitude limit. Simulation experiments are then conducted in different obstacle environments.

  Results   The simulation results show that this method can accurately determine the piloting situation, provide a reasonable steering strategy and achieve effective collision avoidance in different obstacle environments.

  Conclusion   This study provides a theoretical basis and method for realizing the intelligent collision avoidance decision-making and dynamic local collision avoidance path planning of ships.