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research article

A rolling-horizon quadratic-programming approach to the signal control problem in large-scale congested urban road networks

Aboudolas, K.
•
Papageorgiou, M.
•
Kouvelas, A.
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2010
Transportation Research Part C-Emerging Technologies

The paper investigates the efficiency of a recently developed signal control methodology, which offers a computationally feasible technique for real-time network-wide signal control in large-scale urban traffic networks and is applicable also under congested traffic conditions. In this methodology, the traffic flow process is modeled by use of the store-and-forward modeling paradigm, and the problem of network-wide signal control (including all constraints) is formulated as a quadratic-programming problem that aims at minimizing and balancing the link queues so as to minimize the risk of queue spillback. For the application of the proposed methodology in real time, the corresponding optimization algorithm is embedded in a rolling-horizon (model-predictive) control scheme. The control strategy's efficiency and real-time feasibility is demonstrated and compared with the Linear-Quadratic approach taken by the signal control strategy TUC (Traffic-responsive Urban Control) as well as with optimized fixed-control settings via their simulation-based application to the road network of the city centre of Chania, Greece, under a number of different demand scenarios. The comparative evaluation is based on various criteria and tools including the recently proposed fundamental diagram for urban network traffic. (C) 2009 Elsevier Ltd. All rights reserved.

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Type
research article
DOI
10.1016/j.trc.2009.06.003
Author(s)
Aboudolas, K.
Papageorgiou, M.
Kouvelas, A.
Kosmatopoulos, E.
Date Issued

2010

Publisher

Elsevier

Published in
Transportation Research Part C-Emerging Technologies
Volume

18

Start page

680

End page

694

Subjects

Traffic signal control

•

Traffic congestion

•

Store-and-forward modeling

•

Rolling-horizon (model-predictive) control

•

Fundamental diagram of networks

•

Control Strategy

•

Traffic Flow

•

TUC

Editorial or Peer reviewed

REVIEWED

Written at

OTHER

EPFL units
NEARCTIS
Available on Infoscience
November 16, 2010
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/57635
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