Reference:
M. Rinaldi,
L. Capisani,
A. Ferrara,
A. Núñez,
M. Hajiahmadi, and
B. De Schutter,
"Distributed identification of the cell transmission traffic model: A
case study," Proceedings of the 2012 American Control
Conference, Montréal, Canada, pp. 6545-6550, June 2012.
Abstract:
The problem of the distributed identification of a macroscopic
first-order traffic model, viz. the Cell Transmission Model (CTM), is
considered in the paper. The parameters to be identified characterize
the dynamics of the density in different sections of the freeway
(cells). We explore different distributed identification schemes. The
purposes of the approach are mainly to obtain good prediction models
through the minimization of the one-step ahead prediction error of the
densities of the cells, and to reduce the computational time and the
effort required to perform the identification. The methodology is
validated relying on real-life data measured on a portion of the A12
freeway in The Netherlands. An evaluation of the performance of the
identified model used as a set of virtual sensors in different
scenarios is presented.