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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2012  >  12(3): 113-119
LI Qing-quan, ZHOU Yao, LE Yang, YE Jia-an. Compression method of traffic flow data based on compressed sensing[J]. Journal of Traffic and Transportation Engineering, 2012, 12(3): 113-119. doi: 10.19818/j.cnki.1671-1637.2012.03.017
Citation: LI Qing-quan, ZHOU Yao, LE Yang, YE Jia-an. Compression method of traffic flow data based on compressed sensing[J]. Journal of Traffic and Transportation Engineering, 2012, 12(3): 113-119. doi: 10.19818/j.cnki.1671-1637.2012.03.017
shu

Compression method of traffic flow data based on compressed sensing

doi: 10.19818/j.cnki.1671-1637.2012.03.017
  • 1.

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, Hubei, China

  • 2.

    Engineering Research Center for Spatio-Temporal Data Smart Acquisition and Application of Ministry of Education, Wuhan University, Wuhan 430079, Hubei, China

  • 3.

    School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, Hubei, China

  • 4.

    Centre of Urban Studies and Urban Planning, The University of Hong Kong, Hong Kong, China

More Information
  • Author Bio:

    LI Qing-quan (1965-), male, professor, PhD, +86-27-68778222, qqli@whu.edu.cn

  • Received Date: 2012-01-17
  • Publish Date: 2012-06-25
    Abstract
  • In order to obtain transformation matrix accurately, a new compression method of traffic flow data based on compressed sensing was introduced.The original data were projected into the low-dimension space directly by Gauss projection regardless of transformation matrix selection at the data compression side.Firstly, traffic flow data were proved to have sparse representation under the K-SVD trained dictionary.Secondly, original high-dimension data were projected into low-dimension space at the data compression side by using the random matrix with restricted isometry property, which made efficient and rapid data compression possible.Finally, after data transmission, data decompression were accomplished by convex algorithm at the data processing side.The traffic flow data obtained from the coil sensors located on a certain highway of America were used to validated the new method.The experimental result shows that the data compression method is fast and efficient.When the compression ratio is 4∶1, the relative error of data decompression is only 0.060 8.

     

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    • References(18)
  • [1]
    肖扬, 鲁凌云, 高爽, 等. 基于二维离散小波变换的智能交通系统数据去噪声压缩[J]. 北京交通大学学报, 2004, 28(5): 1-5. doi: 10.3969/j.issn.1673-0291.2004.05.001

    XIAO Yang, LU Ling-yun, GAO Shuang, et al. Traffic data denoising compression for intelligent traffic systems based on2-D discrete wavelet transformation[J]. Journal of Beijing Jiaotong University, 2004, 28(5): 1-5. (in Chinese). doi: 10.3969/j.issn.1673-0291.2004.05.001
    [2]
    练秋生, 王成儒, 孔令富. 心电图压缩算法中的小波基选择[J]. 计算机工程与应用, 2002, 38(18): 6-8. doi: 10.3321/j.issn:1002-8331.2002.18.003

    LIAN Qiu-sheng, WANG Cheng-ru, KONG Ling-fu. The choice of wavelet in electrocardiogram compression algorithm[J]. Computer Engineering and Applications, 2002, 38(18): 6-8. (in Chinese). doi: 10.3321/j.issn:1002-8331.2002.18.003
    [3]
    COIFMAN R R, WICKERHAUSER M V. Entropy-based algorithms for best basis selection[J]. IEEE Transactions on Information Theory, 1992, 38(2): 713-718. doi: 10.1109/18.119732
    [4]
    蔡敦虎. 多种小波基的图像去噪性能研究[D]. 武汉: 武汉大学, 2003.

    CAI Dun-hu. The research on the performance of manifold wavelet basis in image denoising[D]. Wuhan: Wuahan University, 2003. (in Chinese).
    [5]
    费铭薇, 乐全明, 张沛超, 等. 电力系统故障录波数据压缩与重构小波基选择[J]. 电力系统自动化, 2005, 29(17): 64-67, 97. doi: 10.3321/j.issn:1000-1026.2005.17.012

    FEI Ming-wei, YUE Quan-ming, ZHANG Pei-chao, et al. Wavelets selection of compression and reconstruction algorithm based on digital recorded data from a faulted power system[J]. Automation of Electric Power Systems, 2005, 29(17): 64-67, 97. (in Chinese). doi: 10.3321/j.issn:1000-1026.2005.17.012
    [6]
    魏玉芬, 梦艳君. 图像编码压缩小波基的选择[J]. 装备制造技术, 2009(4): 49-50, 61. doi: 10.3969/j.issn.1672-545X.2009.04.020

    WEI Yu-fen, MENG Yan-jun. The choice of orthogonal wavelets base in image compression[J]. Equipment Manufac-turing Technology, 2009(4): 49-50, 61. (in Chinese). doi: 10.3969/j.issn.1672-545X.2009.04.020
    [7]
    赵志强, 张毅, 胡坚明, 等. 基于PCA和ICA的交通流量数据压缩方法比较研究[J]. 公路交通科技, 2008, 25(11): 109-118. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200811022.htm

    ZHAO Zhi-qiang, ZHANG Yi, HU Jian-ming, et al. Compara-tive study of PCA and ICA based traffic flow compression[J]. Journal of Highway and Transportation Research and Devel-opment, 2008, 25(11): 109-118. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200811022.htm
    [8]
    QU Li, HU Jian-ming, ZHANG Yi. A flow volumes data compression approach for traffic network based on principal component analysis[C]∥IEEE. Proceedings of the2007IEEE Intelligent Transportation Systems Conference. Seattle: IEEE, 2007: 125-130.
    [9]
    耿彦斌, 于雷, 武旭, 等. 基于信号处理技术的ITS数据压缩方法与应用[J]. 土木工程学报, 2006, 39(11): 107-113. https://www.cnki.com.cn/Article/CJFDTOTAL-TMGC200611017.htm

    GENG Yan-bin, YU Lei, WU Xu, et al. Signal-processing-based ITS data compression techniques and applications[J]. China Civil Engineering Journal, 2006, 39(11): 107-113. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-TMGC200611017.htm
    [10]
    CANDES E J, ROMBERG J, TAO T. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information[J]. IEEE Transactions on Information Theory, 2006, 52(2): 489-509. doi: 10.1109/TIT.2005.862083
    [11]
    DONOHO D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306. doi: 10.1109/TIT.2006.871582
    [12]
    CANDES E J, WAKIN M B. An introduction to compressive sampling[J]. IEEE Signal Processing Magazine, 2008, 25(2): 21-30. doi: 10.1109/MSP.2007.914731
    [13]
    金坚, 谷源涛, 梅顺良. 压缩采样技术及其应用[J]. 电子与信息学报, 2010, 32(2): 470-475. https://www.cnki.com.cn/Article/CJFDTOTAL-DZYX201002041.htm

    JIN Jian, GU Yuan-tao, MEI Shun-liang. An introduction to compressive sampling and its applications[J]. Journal of Electronics and Information Technology, 2010, 32(2): 470-475. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-DZYX201002041.htm
    [14]
    RAUHUT H, SCHNASS K, VAN DERGHEYNST P. Compressed sensing and redundant dictionaries[J]. IEEE Transactions on Information Theory, 2008, 54(5): 2210-2219. https://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4494699&contentType=Journals+%26+Magazines
    [15]
    CANDES E J, ELDAR Y C, NEEDELL D, et al. Com-pressed sensing with coherent and redundant dictionaries[J]. Applied and Computational Harmonic Analysis, 2011, 31(1): 59-73. https://www.sciencedirect.com/science/article/pii/S1063520310001156
    [16]
    AHARON M, ELAD M, BRUCKSTEIN A. K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation[J]. IEEE Transactions on Signal Processing, 2006, 54(11): 4311-4322. https://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.89.4935&rank=5&q=sparse%20radon%20transform&osm=&ossid=
    [17]
    徐鹏. 信号的稀疏分解及其在脑电信号处理中的应用研究[D]. 成都: 电子科技大学, 2006.

    XU Peng. Study on sparse decomposition of signal and its application in EEG processing[D]. Chengdu: University of Electronic Science and Technology of China, 2006. (in Chinese).
    [18]
    TROPP J A, GILBERT A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. IEEE Transactions on Information Theory, 2007, 53(12): 4655-4666. https://authors.library.caltech.edu/27144
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