TY  - JOUR
PY  - 2019//
TI  - Uncertainty quantification in a macroscopic traffic flow model calibrated on GPS data
JO  - Mathematical biosciences and engineering
A1  - Bertino, Enrico
A1  - Duvigneau, Regis
A1  - Goatin, Paola
SP  - 1511
EP  - 1533
VL  - 17
IS  - 2
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 1547-1063
UR  - http://dx.doi.org/10.3934/mbe.2020078
ID  - ref1
ER  -