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A model-based demand-balancing control for dynamically divided multiple urban subnetworks.

Authors :
Lin, Shu
Kong, Qing-Jie
Huang, Qingming
Source :
Journal of Advanced Transportation. Oct2016, Vol. 50 Issue 6, p1046-1060. 15p.
Publication Year :
2016

Abstract

Traffic control is an effective and efficient method for the problem of traffic congestion. It is necessary to design a high-level controller to regulate the network traffic demands, because traffic congestion is not only caused by the improper management of the traffic network but also to a great extent caused by excessive network traffic demands. Therefore, we design a demand-balance model predictive controller based on the macroscopic fundamental diagram-based multi-subnetwork model, which can optimize the network traffic mobility and the network traffic throughput by regulating the input traffic flows of the subnetworks. Because the transferring traffic flows among subnetworks are indirectly controlled and coordinated by the demand-balance model predictive controller, the subnetwork division can variate dynamically according to real traffic states, and a global optimality can be achieved for the entire traffic network. The simulation results show the effectiveness of the proposed controller in improving the network traffic throughput. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01976729
Volume :
50
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Advanced Transportation
Publication Type :
Academic Journal
Accession number :
118553832
Full Text :
https://doi.org/10.1002/atr.1389