As the International Maritime Organization (IMO) introduced the e-Navigation strategy, ship-on-shore data exchange is digitized, and research on autonomous ships and unmanned ships continues, research is actively underway to utilize intelligent systems in marine transportation environments. In an intelligent system, the situation judgment function at the navigator level must be supported, and to this end, it is based on the navigator's decision-making model. The navigator's situation judgment requires a combination of various information and navigation knowledge. In particular, in order to collect information on the surrounding geographical environment, the hydrographic information is essential.
The hydrographic information plays an important role in recognizing the surrounding situation of an intelligent system and creating a navigation plan. Currently, the hydrographic information is provided to navigators in the form of paper charts, electronic navigational charts (ENCs), and nautical publication which are used as key information in determining the situation of navigators such as location, direction, and route environment. The hydrographic information so far has been produced and provided in the form of helping people understand the sailing environment as the human-readable concept.
In order for an intelligent system to recognize the situation at the same level as a navigator's situation perception model, it is necessary to judge and predict the situation through (1) accurate understanding of the hydrographic information, (2) the vision of a navigator, real-time information exchange between ships, and information based on information provided by navigation equipment. However, the current hydrographic information is provided in the form of human understanding through vision, and the navigator's tacit knowledge is not included in the hydrographic information, making it difficult for an intelligent system to recognize the situation at the same level as humans.
To solve the above problem, this paper proposes the Unified Raster Hydrographic Data Model for Identical Interpretation on Navigation Environment (URHII), the hydrographic information model combined with existing the hydrographic information to enable the same level of situational recognition as humans in a given situation. URHII developed a simple and clear information model by combining the existing hydrographic environment model with the navigator's navigation knowledge. In addition, unlike the current hydrographic information model, which was presented in six stages for each purpose of navigation to maintain readability, URHII minimized information duplication and loss due to the application of scale. In addition, the Raster type is selected to maximize the information processing performance of the system, making it easy to compare/synthesize the information structure with other information, and to apply uncertainty information for each object easily. Therefore, URHII is the hydrographic information model for intelligent systems that enables understanding of the same level of the hydrographic information as humans and recognizing the same information in each intelligent system, and enables simple information processing.
For validation of the proposed model, the results of using the existing hydrographic information data as input in the algorithm of optimal safety route support service and using data from the URHII model as input were compared.
For validation of the proposed model, the results of using the existing hydrographic information data as input in the algorithm of optimal safety route support service and using data from the URHII model as input were compared. The two route plans those result waterway were analyzed for similarity to the route provided by the Pilot Association, and the difference from the right side line of the route was analyzed to review the stability within the route. From the analysis results, it was confirmed that better results could be obtained by changing only the waterway information model.
As research on intelligent systems in the maritime field is underway in earnest, standardization of information models for intelligent systems will also emerge as an important issue. The URHII proposed in this study aims to be used in an intelligent system for navigation safety. What is important in the development of standard models should include process information that is advanced and efficient enough to be widely utilized. By extending the contents of URHII to make extensive use of the model in the future, it is expected that URHII could be developed into an official hydrographic information standard model for machines.