Ship Trajectory Online Compression Algorithm Considering Handling Patterns

With the widespread use of shipborne Automatic Identification System (AIS) and establishment shore-based AIS networks in past twenty years, a large amount trajectory data has been generated accumulated systems. However, big size increases cost storing, querying, processing practical applications. includes not only ship spatial position information but also course, speed, heading et al. In other words, knowledge handling behavior is hidden data. fact, many applications, such as maritime accident investigation evidence collection, route extraction, analysis, will require compression algorithm to retain key points original trajectory. To address these research challenges, considering patterns proposed this paper. order explain implicit trajectories, suggested method adopts rate course change (ROCC) speed (ROSC) sliding window criterion whether current point can be simplified. Numerical experiments are performed verify effectiveness algorithm. Compared with Douglas-Peucker (DP) algorithm, Sliding Window (SW) Opening Time Ratio (OPW-TR) results show that efficiently compress trajectories by under application requirement.