RouteMiner: Mining Ship Routes from a Massive Maritime Trajectories

• Main Authors: Yu-Ting Wen, Chien-Hsiang Lai, Po-Ruey Lei, Wen-Chih Peng
• Format: Conference Proceeding
• Language: English
• Subjects: Data mining; Marine vehicles; Maritime Trajectory; Roads; Ship Route Mining; Trajectory; Trajectory Data Mining; Uncertainty; Vectors; Vehicles
• ISSN: 1551-6245; 2375-0324
• DOI: 10.1109/MDM.2014.52

Mining trajectory data has been attracting significant interest in the last years. By analyzing trajectory data, we are able to discover the movement behavior and location-aware knowledge, and then develop many interesting applications such as movement behavior discovery, location prediction, traffic analysis, and so on. However, trajectory data mining is a challenge task because of the trajectory data is available with uncertainty. Furthermore, discovering the valuable knowledge from maritime trajectory is made even more difficult due to the maritime area is a free moving space. Unlike the vehicles' movements are constrained by road networks, there is no such a sea route for ships to follow in maritime area. A ship's movement may not exactly repeat the same trajectory even the ship has the similar movement behavior with others. In this work, Route Miner system provides a framework of ship route mining for maritime traffic analysis. Given a set of ship trajectories in a maritime area, Route Miner explore the movement behavior from those massive trajectories in a free moving space. Then, ship routes are detected based on those behavioral pattern. Finally, the system generates a set of ships routes to provide operators a better understanding from ship trajectory data. We conduct the experiments on real maritime trajectories to show the effectiveness of proposed Route Miner. In the future, Route Miner is going to serve as the photo type for exploring the solutions of the challenges those related to anomaly detection and traffic management in the maritime domain.