A Trajectory Compression Algorithm Based on Non-Uniform Quantization

With the increasing number of GPS-enabled devices, the huge volume of spatiotemporal trajectory data brings about heavy burden for data storing, transmitting and processing. Compressing large scale trajectories is in urgent need. In this paper, we develop an algorithm for trajectory compression based on non-uniform quantization (TCNQ). It is aimed to achieve high compression ratio of large scale trajectory data when lacking geographic context. The method first converts spatiotemporal trajectories into strings by encoding differential coordinates with non-uniform quantization. Then run-length coding is performed to remove redundant points from the trajectories. In this way, quantization and trajectory simplification are combined in the encoding procedures to achieve high compression ratio without losing too much information. Experiments on real large scale trajectory datasets demonstrate that the proposed algorithm has superiority over traditional methods in compression ratio as well as deviation control.