Reference
A. Jamshidnejad, I. Papamichail, M. Papageorgiou, and B. De Schutter,
"Sustainable model-predictive control in urban traffic networks: Efficient
solution based on general smoothening methods,"
IEEE
Transactions on Control Systems Technology, vol. 26, no. 3, pp. 813-827,
May 2018.
Abstract
Traffic-responsive control approaches, including model-predictive control, are
efficient methods for making the best use of the available network capacity.
Moreover, gradient-based approaches, which can be applied to smooth
optimization problems, have proven their efficiency, both computationally and
performance-wise, in finding optima of optimization problems. In this paper, we
propose a model-predictive control system for an urban traffic network that
applies a gradient-based optimization approach to solve the control
optimization problem. The controller uses a new smooth integrated flow-emission
model to find a balanced trade-off between reduction of the congestion and of
the total emissions. We also introduce efficient smoothening methods for
nonsmooth mathematical models of physical systems. The effectiveness of the
proposed approach is demonstrated via a case study.
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BibTeX
@article{JamPap:15-033,
author = {Jamshidnejad, Anahita and Papamichail, Ioannis and Papageorgiou,
Markos and De Schutter, Bart},
title = {Sustainable Model-Predictive Control in Urban Traffic Networks:
{Efficient} Solution Based on General Smoothening Methods},
journal = {IEEE Transactions on Control Systems Technology},
volume = {26},
number = {3},
pages = {813--827},
month = may,
year = {2018}
}