Research article Special Issues

Uncertainty quantification in a macroscopic traffic flow model calibrated on GPS data

  • Received: 31 July 2019 Accepted: 24 November 2019 Published: 02 December 2019
  • The objective of this paper is to analyze the inclusion of one or more random parameters into the deterministic Lighthill-Whitham-Richards traffic flow model and use a semi-intrusive approach to quantify uncertainty propagation. To verify the validity of the method, we test it against real data coming from vehicle embedded GPS systems, provided by Autoroutes Trafic.

    Citation: Enrico Bertino, Régis Duvigneau, Paola Goatin. Uncertainty quantification in a macroscopic traffic flow model calibrated on GPS data[J]. Mathematical Biosciences and Engineering, 2020, 17(2): 1511-1533. doi: 10.3934/mbe.2020078

    Related Papers:

  • The objective of this paper is to analyze the inclusion of one or more random parameters into the deterministic Lighthill-Whitham-Richards traffic flow model and use a semi-intrusive approach to quantify uncertainty propagation. To verify the validity of the method, we test it against real data coming from vehicle embedded GPS systems, provided by Autoroutes Trafic.


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