To improve the efficiency of ship entry into the lock chambers and intelligently guide the ship into the ship lift chambers safely and efficiently, the Markov decision-making model is used to model the ship entry process based on the reinforcement learning method. The model training results are compared to identify the optimal solution by setting different reward functions and time steps. Subsequently, an intelligent navigation aid system is obtained by software development. Finally, a sea trail is conducted by using a typical ship passing through the lock chamber. The results show that the optimal maneuvering strategy not only reduces the number of operations but also enables faster arrival at the destination. Furthermore, the theoretical entry time planned by the navigation aid system is 124 seconds shorter than the actual entry time, corresponding to a 34.4% reduction in entry time. The research can provide references for the intelligent guidance of ship entry into the lock chambers.