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

被引：3

作者：

Bertino, Enrico ^{[1
]}

Duvigneau, Regis ^{[2
]}

Goatin, Paola ^{[2
]}

机构：

[1] Politecn Milan, Piazza Leonardo da Vinci 32, I-20133 Milan, Italy

[2] Univ Cote dAzur, Inria Sophia Antipolis Mediterranee, INRIA, CNRS,LJAD, 2004 Route Lucioles BP 93, F-06902 Sophia Antipolis, France

来源：

MATHEMATICAL BIOSCIENCES AND ENGINEERING | 2020年 / 17卷 / 02期

关键词：

macroscopic traffic flow models; stochastic conservation laws; uncertainty quantification; stochastic parameters; real data; HYPERBOLIC CONSERVATION-LAWS; STOCHASTIC-MODEL; KINEMATIC WAVES;

D O I：

10.3934/mbe.2020078

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页码：1511 / 1533

页数：23

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