In order to develop an HNS safety management system to assess and visualize hazard levels via an automated method, we have conceptualized and configured a sample system. It is designed to quantify the risk of a vessel carrying HNS with a matrix method along navigational route and indicate hazards distribution with a contour map. The basic system which provides a visualized degree of hazards in real time has been introduced for the safe navigation of HNS ships. This is useful not only for decision making and circumstantial judgment but may also be utilized for HNS safety management with a risk base. Moreover, this system could be extended to address the navigational safety of marine traffic as well as of autonomous vessels in the near future if the sensors used are connected with IoT technology.

Despite the development of safety measures and improvements in preventive systems technologies, maritime traffic accidents that involve ships carrying hazardous and noxious substances (HNS) continuously occur owing to increased amount of HNS goods transported and the growing number of HNS fleet. To prevent maritime traffic accidents involving ships carrying HNS, this study proposes an intuitive route risk assessment technique using risk contours that can be visually and quantitatively analyzed. The proposed technique offers continuous information based on quantified values. It determines and structures route risk factors classified as absolute danger, absolute factors, and influential factors within the assessment area. The route risk is assessed in accordance with the proposed algorithmic procedures by means of contour maps overlaid on electronic charts for visualization. To verify the effectiveness of the proposed route risk assessment technique, experimental case studies under various conditions were conducted to compare results obtained by the proposed technique to actual route plans used by five representative companies operating the model ship carrying HNS. This technique is beneficial not only for assessing the route risk of ships carrying HNS, but also for identifying better route options such as recommended routes and enhancing navigation safety. Furthermore, this technique can be used to develop optimized route plans for current maritime conditions in addition to future autonomous navigation application.