Reference
Z. Zhou, B. De Schutter, S. Lin, and Y. Xi, "Multi-agent model-based predictive
control for large-scale urban traffic networks using a serial scheme,"
IET Control Theory & Applications, vol. 9, no. 3, pp.
475-484, 2015.
Abstract
Urban traffic networks are large-scale systems, consisting of many
intersections controlled by traffic lights and interacting connected links. For
efficiently regulating the traffic flows and mitigating the traffic congestion
in cities, a network-wide control strategy should be implemented. Control of
large-scale traffic networks is often infeasible by only using a single
controller, i.e. in a centralized way, because of the high dimension,
complicated dynamics, and uncertainties of the system. In this paper we propose
a multi-agent control approach using a congestion-degree-based serial scheme.
Each agent employs a model-based predictive control approach and communicates
with its neighbors. The congestion-degree-based serial scheme helps the agents
to reach an agreement on their decisions regarding traffic control actions as
soon as possible. A simulation study is carried out on a hypothetical
large-scale urban traffic network based on the presented control strategy. The
results illustrate that this approach has a better performance with regard to
computation time compared with the centralized control method and a faster
convergence speed compared with the classical parallel scheme.
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BibTeX
@article{ZhoDeS:15-001,
author = {Zhou, Zhao and De Schutter, Bart and Lin, Shu and Xi, Yugeng},
title = {Multi-Agent Model-Based Predictive Control for Large-Scale Urban
Traffic Networks Using a Serial Scheme},
journal = {IET Control Theory \& Applications},
volume = {9},
number = {3},
pages = {475--484},
year = {2015}
}