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Mathematical Problems in Engineering
Volume 2017, Article ID 8784067, 7 pages
Research Article

Improved Road-Network-Flow Control Strategy Based on Macroscopic Fundamental Diagrams and Queuing Length in Connected-Vehicle Network

1Institute of Rail Traffic, Guangdong Communication Polytechnic, Guangzhou, China
2School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China

Correspondence should be addressed to Xiaohui Lin; moc.361@1891hxnil

Received 17 July 2017; Revised 7 October 2017; Accepted 16 October 2017; Published 12 November 2017

Academic Editor: Francesco Soldovieri

Copyright © 2017 Xiaohui Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Connected-vehicles network provides opportunities and conditions for improving traffic signal control, and macroscopic fundamental diagrams (MFD) can control the road network at the macrolevel effectively. This paper integrated proposed real-time access to the number of mobile vehicles and the maximum road queuing length in the Connected-vehicles network. Moreover, when implementing a simple control strategy to limit the boundary flow of a road network based on MFD, we determined whether the maximum queuing length of each boundary section exceeds the road-safety queuing length in real-time calculations and timely adjusted the road-network influx rate to avoid the overflow phenomenon in the boundary section. We established a road-network microtraffic simulation model in VISSIM software taking a district as the experimental area, determined MFD of the region based on the number of mobile vehicles, and weighted traffic volume of the road network. When the road network was tending to saturate, we implemented a simple control strategy and our algorithm limits the boundary flow. Finally, we compared the traffic signal control indicators with three strategies: no control strategy, boundary control, and boundary control with limiting queue strategy. The results show that our proposed algorithm is better than the other two.