A High-Resolution Dynamic Marine Traffic Flow Visualization Model Using AIS Data

The introduction of Maritime Autonomous Surface Ships (MASS) and the accelerating digitalization of ports require precise and dynamic analysis of traffic conditions. However, conventional marine traffic analyses have been limited to low-resolution grids and static density visualizations without fully integrating vessel direction and speed. To address this limitation, this study proposes a traffic flow visualization model that incorporates dynamic maritime traffic structure. The model integrates density, dominant direction, and average speed into a single symbol, thereby complementing the limitations of static analyses. In addition, high-resolution grids of approximately 90 m were applied to enable detailed analysis. AIS data collected between 2022–2023 from the coastal waters of Mokpo, South Korea, were preprocessed, aggregated into grid cells, and analyzed to estimate representative directions (at 10° intervals) as well as average speeds. These results were visualized through color, thickness, length, and direction of arrows. The analysis showed high-density, low-speed traffic patterns and starboard-passage behavior in port approaches and narrow channels, while irregular directions with low density were observed in non-standard routes. The proposed model provides a visual representation of dynamic traffic structures that cannot be revealed by density maps alone, thus offering practical applicability for MASS route planning, VTS operation support, and risk assessment.