Aiming at the problem of deviation between the navigation state and the ideal state during the autonomous collision avoidance process of inland waterway vessels,a BAS algorithm based autonomous collision avoidance optimization method for the navigation route of inland waterway vessels is studied.By determining the relative speed and heading angle status of the vessel,the dynamic driving risk level is determined and the vessel position isupdated.By using the BAS algorithm to compare fitness states,the pheromone matrix is updated to determine the historical optimal target value.Using Ackley/Rosenbrock functions for decision search,generating autonomous collision avoidance decisions under finite state machine,and completing autonomous collision avoidance optimization of inland waterway vessel travel routes.The experimental results show that the collision avoidance path planned by this method can always maintain a safe distance of more than 70 m from dynamic and static obstacles,with an average reduction of about 15% in rudder angle adjustment amplitude and an improvement of about 20% in heading stability.It successfully avoid collisions in all test scenarios,and the ship can quickly return to the ideal route after collision avoidance.The proposed method significantly improves the autonomy,safety,and stability of collision avoidance decision-making for inland vessels,and can provide an effective technical approach for autonomous navigation in inland rivers.