Reference
Z. Zhou, B. De Schutter, S. Lin, and Y. Xi, "Two-level hierarchical model-based
predictive control for large-scale urban traffic networks,"
IEEE Transactions on Control Systems Technology, vol. 25, no.
2, pp. 496-508, Mar. 2017.
Abstract
Network-wide control of large-scale urban traffic networks using a hierarchical
framework can be more efficient and flexible than centralized strategies for
reducing the traffic congestion in big cities, because it can adequately
address some problems that occur in controlling such large systems, e.g.
computational complexity, multiple control objectives, weak robustness to
uncertainties, and so on. In this paper, we propose a two-level hierarchical
control framework for large-scale urban traffic networks. At the upper level,
based on decomposing a heterogeneous traffic network into several homogeneous
subnetworks, a higher-level optimization problem using the concept of
macroscopic fundamental diagram is formulated to deal with the traffic demand
balance problem. At the lower level, the controller with a more detailed
traffic flow model for each subnetwork determines the optimal signal timing
within the given region under the guidance of the upper-level controller
through communication. For the application of this architecture in real time,
the model-based predictive control approach is utilized so as to obtain the
best solutions for both levels. Moreover, in order to decrease the
computational complexity, a distributed control scheme within each subnetwork
is developed at the lower level. The proposed approach is evaluated by
simulation under different scenarios on a hypothetical urban traffic network,
and the performance is compared with that of other control strategies.
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BibTeX
@article{ZhoDeS:16-010,
author = {Zhou, Zhao and De Schutter, Bart and Lin, Shu and Xi, Yugeng},
title = {Two-Level Hierarchical Model-Based Predictive Control for
Large-Scale Urban Traffic Networks},
journal = {IEEE Transactions on Control Systems Technology},
volume = {25},
number = {2},
pages = {496--508},
month = mar,
year = {2017}
}