Objective Intelligent ship navigation has become a core technological enabler for accelerating the digital, intelligent and low-carbon transformation of the global shipping industry. Driven by the International Maritime Organization’s greenhouse gas emission reduction targets and China’s strategic policies for intelligent shipping development, ship intelligent navigation systems are evolving from experimental validation toward engineering applications. However, several key challenges remain in practical implementation. In particular, the coordination mechanism among navigation decision-making, propulsion response, and energy-efficiency constraints lacks a unified architectural representation. In addition, the adaptive mapping logic between shipboard intelligent capability levels and shore-based hierarchical operation modes has not yet been systematically established. To address these gaps, this study focuses on the architectural design of a bridge–engine integrated ship intelligent navigation system and investigates the adaptive mechanisms of ship–shore collaborative operation.

Method In terms of research methods, this paper firstly defines the functional connotation, system boundaries, and essential characteristics of bridge–engine integration based on existing regulations for intelligent ships and relevant domestic and international research outcomes. Secondly, a hierarchical intelligent navigation architecture is established. A three-stage evolution pathway for shipboard autonomy is proposed, including enhanced navigation, assisted navigation and autonomous navigation. In parallel, three shore-based operation modes are defined, namely monitoring, remote control, and supervisory navigation. On this basis, an asymmetric ship–shore functional adaptation matrix is developed to systematically clarify recommended combination, restricted feasible combinations, and inapplicable combinations, with typical application scenarios clearly specified. Finally, key enabling technologies are comprehensively analyzed, including environmental perception and situational awareness, navigation decision-making and path planning control, intelligent engine room operation and energy efficiency management, system testing and evaluation, as well as ship–shore human-machine collaborative control.

Results The research results systematically present the overall hierarchical architecture of a bridge–engine integrated ship intelligent navigation system under ship–shore collaboration. They clarify the functional connotation and operational boundaries of each shipboard capability level and shore-based operation mode, and reveal the asymmetric adaptation rules and principles of control authority allocation between shipboard and shore-end systems.

Conclusion It is concluded that the proposed system architecture and asymmetric adaptation matrix can provide a solid theoretical foundation and technical reference for the engineering implementation of intelligent ship navigation systems and the development of relevant industrial standards. Furthermore, the findings offer important theoretical guidance for improving ship–shore collaborative operation mechanisms, standardizing control authority switching, and promoting the development and application of a new-generation intelligent and green maritime transportation system.