Reference:
S. Lin,
B. De Schutter,
Y. Xi, and
J. Hellendoorn,
"A simplified macroscopic urban traffic network model for model-based
predictive control," Proceedings of the 12th IFAC Symposium on
Transportation Systems, Redondo Beach, California, pp. 286-291,
Sept. 2009.
Abstract:
A model predictive control (MPC) approach offers several advantages
for controlling and coordinating urban traffic networks. To apply MPC
in large urban traffic networks, a fast model that has a low on-line
computational complexity is needed. In this paper, a simplified
macroscopic urban traffic network model is proposed and tested.
Compared with a previous model, the model reduces the computing time
by enlarging its updating time intervals, and preserves the
computational accuracy as much as possible. Simulation results show
that the simplified model reduces the computing time significantly,
compared with the previous model that provided a good trade-off
between accuracy and computational complexity. We also illustrate that
the simplifications introduced in the simplified model have a limited
impact on the accuracy of the simulation results. As a consequence,
the simplified model can be used as prediction model for MPC for
larger urban traffic network.