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Compression Algorithm of Road Traffic Spatial Data Based on LZW Encoding

Journal article published in 2017 by Dong-Wei Xu ORCID, Yong-Dong Wang, Li-Min Jia ORCID, Gui-Jun Zhang, Hai-Feng Guo
This paper is available in a repository.
This paper is available in a repository.

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Preprint: policy unknown
Question mark in circle
Postprint: policy unknown
Question mark in circle
Published version: policy unknown

Abstract

Wide-ranging applications of road traffic detection technology in road traffic state data acquisition have introduced new challenges for transportation and storage of road traffic big data. In this paper, a compression method for road traffic spatial data based on LZW encoding is proposed. First, the spatial correlation of road segments was analyzed by principal component analysis. Then, the road traffic spatial data compression based on LZW encoding is presented. The parameters determination is also discussed. Finally, six typical road segments in Beijing are adopted for case studies. The final results are listed and prove that the road traffic spatial data compression method based on LZW encoding is feasible, and the reconstructed data can achieve high accuracy.