Abstract: Human−machine shared navigation control for intelligent ships integrates advanced technologies including enhanced perception, intelligent decision-making and autonomous control, and establishes an innovative navigation control paradigm featuring efficient collaboration between ship operators and autonomous navigation systems, dynamic authority allocation and friendly human-machine interaction. It has become a core technical direction for developing next-generation intelligent maritime transportation systems and improving the safety of maritime operations. Driven by the practical application demands of intelligent ships, this paper focuses on the deep coupling characteristics of each core link in human-machine shared navigation control. From the full-process perspective of modeling, perception, decision-making, navigation control and fault-tolerant safety assurance, this work systematically reviews the global research progress and summarizes typical architectures of human-machine shared navigation control systems. Furthermore, the state-of-the-art developments in key technologies are analyzed, such as ship operator behavior modeling and risk quantification, navigation situational awareness enhancement, intelligent navigation decision-making, cooperative navigation control, fault diagnosis and fault-tolerant control, as well as the cross-module coupling and coordination mechanisms. Finally, the future development trends of human-machine shared navigation control for intelligent ships are discussed. Special attention is paid to several promising interdisciplinary research directions, including large language model enabled human-machine interaction, digital twin modeling, self-learning intelligent decision-making, and dynamic game-theoretic allocation of control authority.