No abstract

With the increasing development of GPS-equipped mobile devices such as smart phones and vehicle navigation systems, the trajectories containing valuable spatiotemporal information are recorded. Typically, plenty of trajectory records are generated and stored, making the device memory suffer a heavy storage pressure. Thus, it is a vital issue to compress the trajectories. The trajectory semantics are usually ignored or reduced in traditional trajectory compression techniques. In addition, most of existing trajectory compression algorithms only concern the position errors rather than the velocity errors of trajectories. This paper proposes a velocity-preserving trajectory compression algorithm based on retrace point detection (VPTC-RP) that can compress a set of trajectories by removing unnecessary redundancy points, while the skeleton of these trajectories is maintained as much as possible. In VPTC-RP, the retrace points and the velocity errors are taken to reflect the speeds and directions attached with the points. VPTC-RP first determines the retrace points based on the changed movement directions, and then, the retrace points are extracted from the original trajectories. Especially, the retrace points are put in a buffer, and the subtrajectories in the buffer are compressed according to the measured velocity errors. Simulations are carried out on the Geolife trajectory dataset, and the simulation results indicate that VPTC-RP can achieve a preferable tradeoff among the compression error, compression ratio, and running time.