Gaussian Approximation for Modeling Traffic Flow on a Homogeneous Road Segment

A Gaussian approximation of the stochastic model by Jabari and Liu proposed is implemented for a case study. The Gaussian approximation estimates the mean traffic density from the long-term trend of a stochastic model, and a variance calculated from the deviance of the stochastic model and its long-term limit. The mean is the deterministic Godunov scheme. Through this case study the model is shown capable of producing accurate queue size estimates in a viable amount of time for cycle-by-cycle traffic estimation on an arterial road. Model variance is controllable by choice of time step; however, smaller time steps limit the ability of the model to produce a range of solutions which contain the ground truth observation.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: pp 334-349
  • Monograph Title: Celebrating 50 Years of Traffic Flow Theory: A Symposium. August 11-13, 2014, Portland, Oregon
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 01604722
  • Record Type: Publication
  • Files: TRIS, TRB, ATRI
  • Created Date: Jul 14 2016 3:30PM