Comparative Study of PCA and ICA Based Traffic Flow Compression

In this paper, data compression methods of traffic flow based on principle component analysis (PCA) and independent component analysis (ICA) are provided and compared. First, the statistical properties of freeway and urban road traffic flow are examined. It is found that the sample rate does not affect the analysis result and the distribution of deviation for traffic flow of different sample rates are similar. All of them are super-Gaussian distribution but near Gaussian distribution. Second, the compressions and reconfiguration based on PCA and ICA were tested and compared for freeway and urban road traffic flow, respectively. The results show that: 1) PCA is a better choice for both traffic flows since they yield less non-Gaussian distribution; and 2) the compression for freeway is better than for urban road since the freeway flow is more stable and regular. This result also gives some insight into the intrinsic nature of traffic flow.

  • Availability:
  • Authors:
    • Zhao, Zhiqiang
    • Zhang, Yi
    • Hu, Jianming
    • Li, Li
  • Publication Date: 2009-6

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01149308
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jan 28 2010 3:33PM