Topology Modeling of Inland Traffic Based on Vessel Trajectory Turning Points

The inland waterway system features numerous tributaries and varied channel structures, forming a highly coupled traffic network that results in diverse and complex vessel encounters at river intersections. To investigate the vessel traffic flow conditions at waterway intersections, data were collected at the confluence of the Yangtze River and Xiangjiang River, which represents a typical and strategically important inland navigation hub with intensive traffic activities. Based on high-resolution AIS data, vessel trajectory turning points were identified by using the Douglas–Peucker algorithm, and the topological structure of intersection traffic networks was constructed through OPTICS clustering, thereby extracting turning patterns and navigation paths. Given the complexity of inland vessel traffic flows, the trajectories are classified into four categories according to whether they enter tributaries and their navigation directions. For each trajectory category, representative turning points were identified and treated as network nodes. The node weights were assigned based on the normalized vessel traffic density, which reflects the relative importance of different navigation behaviors. These elements were integrated into a unified topological network that captures both spatial structure and traffic intensity. The topology result reveals the distinct turning patterns and dominant navigation paths associated with vessel traffic flows at inland waterway intersections. The present findings provide a methodological basis for inland waterway planning and maritime safety management.