Short-Term Traffic Flow Forecasting by Improved Chaotic Method Based on the Maximum Lyapunov Exponent

The accuracy of rapid short-term traffic flow forecasting has become a key studying part of intelligent transportation system (ITS). In this paper, based on the maximum Lyapunov exponent, an improved chaotic time series method for forecasting short-term traffic flow is proposed. Several neighboring phase points are selected in reconstructed phase space and fused in the evolution process by considering the distance and angle between neighboring phase points and forecasting phase point to increase the forecasting precision. Finally, the actual data is used to verify the effectiveness of the improved method.


  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 613-620
  • Monograph Title: CICTP 2015: Efficient, Safe, and Green Multimodal Transportation

Subject/Index Terms

Filing Info

  • Accession Number: 01574527
  • Record Type: Publication
  • ISBN: 9780784479292
  • Files: TRIS, ASCE
  • Created Date: Jul 22 2015 3:02PM