Reference
A. Jamshidnejad, B. De Schutter, and
M. J.
Mahjoob, "Urban traffic control using a fuzzy multi-agent system,"
Proceedings of the 2015 European Control Conference, Linz,
Austria, pp. 3046-3051, July 2015.
Abstract
This paper presents a fuzzy multi-agent system for control of the traffic
signals of an urban network, where the aim is to reduce the total average delay
time of the vehicles. The large-scale traffic system is first divided into
sub-areas and an agent, using a fuzzy controller, is considered for each
sub-area. In order to develop the fuzzy rule bases for the agents, an extensive
set of data is collected and the corresponding origin-destination (OD) matrices
are calculated. The OD matrices are then clustered using a new clustering
algorithm proposed in this paper. Finally, the resulting cluster centers, which
are matrices of the same dimension as the OD matrices, are mapped to a
2-dimensional space and the corresponding triangular fuzzy sets are extracted.
An optimal cycle plan is found for each fuzzy set and this way the fuzzy rule
bases are constructed (the triangular fuzzy sets form the IF-parts and the
optimal cycle plans form the THEN-parts). In a case study the proposed
multi-agent control system is applied to a microscopic urban traffic network
and the results are compared with a controller that applies optimal signal
plans calculated by PASSER V. The results show that the proposed fuzzy
multi-agent system outperforms the non-fuzzy control system, where the average
delay time of the traveling vehicles is decreased by 19% using the multi-agent
control system.
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BibTeX
@inproceedings{JamDeS:15-007,
author = {Jamshidnejad, Anahita and De Schutter, Bart and Mahjoob,
Mohammad J.},
title = {Urban Traffic Control Using a Fuzzy Multi-Agent System},
booktitle = {Proceedings of the 2015 European Control Conference},
address = {Linz, Austria},
pages = {3046--3051},
month = jul,
year = {2015}
}