Reference
S. Liu, H. Hellendoorn, and B. De Schutter, "Model predictive control for
freeway networks based on multi-class traffic flow and emission models,"
IEEE Transactions on Intelligent Transportation Systems, vol.
18, no. 2, pp. 306-320, Feb. 2017.
Abstract
The main aim of this paper is to use multi-class macroscopic traffic flow
and emission models for MPC for traffic networks.
Particularly, we use and compare extended versions of multi-class METANET,
FASTLANE, multi-class VT-macro, and multi-class VERSIT+. Besides, end-point
penalties based on these multi-class traffic flow and emission models are also
included in the objective function of MPC to account for the behavior of the
traffic system beyond the prediction horizon. A simulation experiment is
implemented to evaluate the multi-class models. The results show that the
approaches based on multi-class METANET and the extended emission models
(multi-class VT-macro or multi-class VERSIT+) can improve the control
performance for the total time spent and the total emissions w.r.t. the
non-control case, and they are more capable of dealing with the queue length
constraints than the approaches based on FASTLANE. Including end-point
penalties can further improve the control performance with a small sacrifice in
the computational efficiency for the approaches based on multi-class METANET,
but not for the approaches based on FASTLANE.
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BibTeX
@article{LiuHel:15-020,
author = {Liu, Shuai and Hellendoorn, Hans and De Schutter, Bart},
title = {Model Predictive Control for Freeway Networks Based on
Multi-Class Traffic Flow and Emission Models},
journal = {IEEE Transactions on Intelligent Transportation Systems},
volume = {18},
number = {2},
pages = {306--320},
month = feb,
year = {2017}
}