With the continuous advancement of intelligent technology, intelligent transportation has become a prominent area of research within the transportation sector. In contrast to road-based intelligent transportation systems, the development of intelligent maritime transportation remains in its early stages. This paper proposes a foundational theory and related concepts for ship navigation guidance to address the gap in theoretical support for intelligent maritime transportation. By examining both individual and system-level attributes, the similarities and differences between vehicles and ships are analyzed. Drawing on the theoretical framework of road-based intelligent transportation and the unique characteristics of maritime transportation, the paper introduces the core theory of intelligent maritime transportation, specifically the theoretical structure of a ship’s intelligent guidance system. Based on this theoretical framework, a prototype of the ship navigation intelligent guidance system was developed and tested. The experimental results demonstrate that the system successfully integrates core technologies, each fulfilling its intended role. The system significantly enhances the safety of ship navigation and fosters the advancement of intelligent maritime transportation. Therefore, the proposed definition of ship navigation guidance and the associated technical framework for the intelligent guidance system not only enrich the theoretical foundations of intelligent maritime transportation but also offer valuable insights for the development of intelligent ships.

To address the challenges posed by dense shipping traffic and the difficulty of identifying navigation risks in open waters, this paper introduces an Especial Cautious Navigation Angle (ECNA) model for ships, grounded in ship collision avoidance geometry. The ECNA model dynamically identifies the range of navigation angles where collision risks may arise between ships. Building upon this model, a comprehensive scoring algorithm is proposed to assess ship collision risks in open waters. This algorithm not only effectively tracks the evolving risk of collisions but also prioritizes ships with the most imminent danger of collision. Experimental results demonstrate that the ECNA model can accurately define the range of collision risk navigation angles. Furthermore, the scoring algorithm provides a quantitative analysis of the development trends in collision risks and offers continuous monitoring of these risks during navigation in open waters. The proposed model and algorithm exhibit strong practical applicability and operability in identifying ship collision risks in both open and dense navigable areas. These findings not only offer valuable guidance for real-world collision risk identification but also contribute to the theoretical advancement of ship collision risk analysis, presenting a novel solution to this pressing issue.