Reference
P. Deo, B. De Schutter, and A. Hegyi, "Model predictive control for multi-class
traffic flows,"
Proceedings of the 12th IFAC Symposium on
Transportation Systems, Redondo Beach, California, pp. 25-30, Sept.
2009.
Abstract
In this paper we first present an extension of the macroscopic traffic flow
model METANET to multi-class flows. The resulting multi-class model takes into
account the differences between, e.g., fast vehicles (cars) and slow vehicles
(trucks) including their possibly different free-flow speeds and critical
densities. Next, we show how this model can be used in a model-based predictive
control approach for coordinated and integrated traffic flow control. In
particular, we use Model Predictive Control (MPC) to coordinate various traffic
control measures such as variable speed limits, ramp metering, etc. Using a
simple benchmark example from the literature we illustrate that by taking the
heterogeneous nature of multi-class traffic flows into account a better
performance can be obtained.
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BibTeX
@inproceedings{DeoDeS:09-023,
author = {Deo, Puspita and De Schutter, Bart and Hegyi, Andreas},
title = {Model Predictive Control for Multi-Class Traffic Flows},
booktitle = {Proceedings of the 12th IFAC Symposium on Transportation
Systems},
address = {Redondo Beach, California},
pages = {25--30},
month = sep,
year = {2009}
}