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[00516] Parameters Estimation For Car Following Models Using Bayesian Inference

  • Session Time & Room : 2D (Aug.22, 15:30-17:10) @E503
  • Type : Contributed Talk
  • Abstract : Car following (CF) models play an important role in traffic simulation software. Estimating their parameters is necessary to enhance predictive performance and is traditionally accomplished through optimisation. In this research, we adopted Bayesian inference which is advantageous for uncertainty quantification. As the CF model depends on its parameters through solution of a delay differential equation, the likelihood is analytically intractable so we employed an adaptive Markov chain Monte Carlo algorithm to sample from the posterior.
  • Classification : 62F15, 65Cxx
  • Format : Talk at Waseda University
  • Author(s) :
    • Samson Ting (The University of Western Australia)
    • Michael Small (The University of Western Australia)
    • Thomas Stemler (The University of Western Australia)
    • Chao Sun (The University of Western Australia)
    • Thomas Lymburn (The University of Western Australia)