Reference
M. Hajiahmadi,
G. S. van de Weg,
C. M. J. Tampère, R. Corthout, A.
Hegyi, B. De Schutter, and H. Hellendoorn, "Integrated predictive control of
freeway networks using the extended link transmission model,"
IEEE Transactions on Intelligent Transportation Systems, vol.
17, no. 1, pp. 65-78, Jan. 2016.
Abstract
In this paper, the recently developed link transmission model (LTM) is utilized
in an on-line hybrid model-based predictive control (MPC) framework. The model
is extended to include the effects of ramp metering and variable speed limits.
Next, an integrated freeway traffic control based on the new model is presented
in order to minimize the total time spent in the network. The integrated scheme
has the capability of controlling large-scale freeway networks in real-time as
the model is computationally efficient and it is yet accurate enough for our
control purposes. In addition, the extended model is reformulated as a system
of linear inequalities with mixed binary and real variables. The reformulated
model along with the linearized total travel time objective function establish
a mixed integer linear optimization problem that is more tractable and even
faster than the original optimization problem integrated in the MPC scheme.
Finally, to investigate the performance of the proposed approaches (nonlinear
MPC and the mixed integer linear counterpart), a freeway network layout based
on the Leuven Corridor in Belgium is selected. The extended LTM is calibrated
for this network using micro-simulation data and next, is used for prediction
and control of the large network. Micro-simulation results show that the
proposed methods are able to efficiently improve the total travel time.
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BibTeX
@article{Hajvan:15-022,
author = {Hajiahmadi, Mohammad and van de Weg, Goof S. and Tamp{\`{e}}re,
Chris M. J. and Corthout, Ruben and Hegyi, Andreas and De
Schutter, Bart and Hellendoorn, Hans},
title = {Integrated Predictive Control of Freeway Networks Using the
Extended Link Transmission Model},
journal = {IEEE Transactions on Intelligent Transportation Systems},
volume = {17},
number = {1},
pages = {65--78},
month = jan,
year = {2016}
}