Non-linear analysis of traffic flow

A. S. Nair, J. C. Liu, L. Rilett, S. Gupta

Research output: Contribution to conferencePaperpeer-review

45 Scopus citations


Traffic flow prediction is an important application of the ITS technology. In this paper, we applied non-linear time-series modeling techniques to analyze a traffic data. Our objective is to investigate the deterministic properties of traffic flow using a nonlinear time series analysis technique. The experiment is performed for inductance loop data collected from the San Antonio freeway system. Our study concludes that the traffic data exhibits chaotic properties and techniques based on phase space dynamics can be used to analyze and predict the traffic flow.

Original languageEnglish (US)
Number of pages5
StatePublished - 2001
Externally publishedYes
Event2001 IEEE Intelligent Transportation Systems Proceedings - Oakland, CA, United States
Duration: Aug 25 2001Aug 29 2001


Other2001 IEEE Intelligent Transportation Systems Proceedings
Country/TerritoryUnited States
CityOakland, CA


  • Chaos
  • Lyapunov exponent
  • Phase space embedding
  • Time delay neural network
  • Time series prediction

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


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