Trajectory Data Compression Algorithm Based on Motion State Changing

Shuo Zhang, Jian Zhang and Lin Qi

Mathematical Problems in Engineering, 2021, vol. 2021, 1-8

Abstract:

The trajectory information generated by the moving object plays an important role in studying the object movement. In this paper, a trajectory data compression algorithm based on the motion state changing is proposed to reduce trajectory data storage space and increase compression speed, which can accurately show the motion state and trajectory characteristics. This study has certain significance for the exploration of mass traffic data and the planning of traffic network. Combining the angle threshold with the velocity threshold of a moving object, the key data points are found and the redundant information is removed. Subsequently, the compressed trajectory is obtained. The experimental results show that the new algorithm can help to improve compression efficiency. The compressed trajectory has high similarity with the original trajectory in movement tendency.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6647074

DOI: 10.1155/2021/6647074

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