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CLC number: TP273; U491

On-line Access: 2016-08-31

Received: 2015-07-19

Revision Accepted: 2016-04-18

Crosschecked: 2016-08-09

Cited: 1

Clicked: 5956

Citations:  Bibtex RefMan EndNote GB/T7714


Guo-jiang Shen


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Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.9 P.907-918


A dynamic signal coordination control method for urban arterial roads and its application

Author(s):  Guo-jiang Shen, Yong-yao Yang

Affiliation(s):  College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310014, China; more

Corresponding email(s):   gjshen1975@zjut.edu.cn

Key Words:  Urban arterial, Control subarea, Coordination control, Correlation degree, Fuzzy logic, Intelligent transportation

Guo-jiang Shen, Yong-yao Yang. A dynamic signal coordination control method for urban arterial roads and its application[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(9): 907-918.

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DOI - 10.1631/FITEE.1500227

We propose a novel dynamic traffic signal coordination method that takes account of the special traffic flow characteristics of urban arterial roads. The core of this method includes a control area division module and a signal coordination control module. Firstly, we analyze and model the influences of segment distance, traffic flow density, and signal cycle time on the correlation degree between two neighboring intersections. Then, we propose a fuzzy computing method to estimate the correlation degree based on a hierarchical structure and a method to divide the control area of urban arterial roads into subareas based on correlation degrees. Subarea coordination control arithmetic is used to calculate the public cycle time of the control subarea, up-run offset and down-run offset of the section, and the split of each intersection. An application of the method in Shaoxing City, Zhejiang Province, China shows that the method can reduce the average travel time and the average stop rate effectively.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Febbraro, A.D., Giglio, D., Sacco, N., 2015. A deterministic and stochastic Petri net model for traffic-responsive signaling control in urban areas. IEEE Trans. Intell. Transp. Syst., 17(2):510-524.

[2]Gartner, N.H., Stamatiadis, C., 2004. Progression optimization featuring arterial- and route-based priority signal networks. Intell. Transp. Syst., 8(2):77-86.

[3]Kong, Q.J., Li, L.F., Yan, B., et al., 2013. Developing parallel control and management for urban traffic systems. IEEE Intell. Syst., 28(3):66-69.

[4]Kong, X.J., Shen, G.J., Xia, F., et al., 2011. Urban arterial traffic two-direction green wave intelligent coordination control technique and its application. Int. J. Contr. Autom. Syst., 9(1):60-68.

[5]Kumar, P., Merzouki, R., Conrard, B., et al., 2014. Multilevel modeling of the traffic dynamic. IEEE Trans. Intell. Transp. Syst., 15(3):1066-1082.

[6]Lee, J.H., Lee-Kwang, H., 1999. Distributed and cooperative fuzzy controllers for traffic intersections group. IEEE Trans. Syst. Man Cybern. C, 29(2):263-271.

[7]Liu, Z.Y., 2003. Intelligent Traffic Control Theory and Application. Science Public House, Beijing, China, p.22-23 (in Chinese).

[8]Lu, K., Xu, J.M., Zheng, S.J., 2009. Correlation degree analysis of neighboring intersections and its application. J. South China Univ. Technol. Nat. Sci., 37(11):37-42 (in Chinese).

[9]Pillai, R.S., Rathi, A.K., Cohen, S.L., 1998. A restricted branch-and-bound approach for generating maximum bandwidth signal timing plans for traffic networks. Transp. Res. B-Method, 32(8):517-529.

[10]Lertworawanich, P., Kuwahara, M., Miska, M., 2011. A new multiobjective signal optimization for oversaturated networks. IEEE Trans. Intell. Transp. Syst., 12(4):967-976.

[11]Ren, S.P., Shen, G.J., 2010. Intelligent hybrid forecasting technique for short-term traffic flow. J. Zhejiang Univ. Eng. Sci., 44(8):1473-1478 (in Chinese).

[12]Shen, G.J., Kong, X.J., 2009. Study on road network traffic coordination control technique with bus priority. IEEE Trans. Syst. Man Cybern. C, 39(3):343-351.

[13]Shen, G.J., Sun, Y.X., 2002. Multi-phase fuzzy traffic control based on phase sequencer. Contr. Dec., 17(Suppl.): 654-658 (in Chinese).

[14]Tettamanti, T., Luspay, T., Kulcsár, B., et al., 2014. Robust control for urban road traffic networks. IEEE Trans. Intell. Transp. Syst., 15(1):385-398.

[15]Wu, W.G., Zhang, J.B., Luo, A.X., et al., 2015. Distributed mutual exclusion algorithms for intersection traffic control. IEEE Trans. Parall. Distr. Syst., 26(1):65-74.

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