Compression Algorithm of Road Traffic Spatial Data Based on LZW Encoding
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, th...
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Format: | Article |
Language: | English |
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Wiley
2017-01-01
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Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2017/8182690 |
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author | Dong-wei Xu Yong-dong Wang Li-min Jia Gui-jun Zhang Hai-feng Guo |
author_facet | Dong-wei Xu Yong-dong Wang Li-min Jia Gui-jun Zhang Hai-feng Guo |
author_sort | Dong-wei Xu |
collection | DOAJ |
description | 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. |
format | Article |
id | doaj-art-d25164773d5b4ae29b4c0fc2c118c408 |
institution | Kabale University |
issn | 0197-6729 2042-3195 |
language | English |
publishDate | 2017-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Advanced Transportation |
spelling | doaj-art-d25164773d5b4ae29b4c0fc2c118c4082025-02-03T05:50:57ZengWileyJournal of Advanced Transportation0197-67292042-31952017-01-01201710.1155/2017/81826908182690Compression Algorithm of Road Traffic Spatial Data Based on LZW EncodingDong-wei Xu0Yong-dong Wang1Li-min Jia2Gui-jun Zhang3Hai-feng Guo4College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaCollege of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaWide-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.http://dx.doi.org/10.1155/2017/8182690 |
spellingShingle | Dong-wei Xu Yong-dong Wang Li-min Jia Gui-jun Zhang Hai-feng Guo Compression Algorithm of Road Traffic Spatial Data Based on LZW Encoding Journal of Advanced Transportation |
title | Compression Algorithm of Road Traffic Spatial Data Based on LZW Encoding |
title_full | Compression Algorithm of Road Traffic Spatial Data Based on LZW Encoding |
title_fullStr | Compression Algorithm of Road Traffic Spatial Data Based on LZW Encoding |
title_full_unstemmed | Compression Algorithm of Road Traffic Spatial Data Based on LZW Encoding |
title_short | Compression Algorithm of Road Traffic Spatial Data Based on LZW Encoding |
title_sort | compression algorithm of road traffic spatial data based on lzw encoding |
url | http://dx.doi.org/10.1155/2017/8182690 |
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