[1] Bi Yunrui, Lu Xiaobo, Sun Zhe, Zeng Weili, et al. Fuzzy traffic signal control with DNA evolutionary algorithm [J]. Journal of Southeast University (English Edition), 2013, 29 (2): 207-210. [doi:10.3969/j.issn.1003-7985.2013.02.017]

Copy

Fuzzy traffic signal control with DNA evolutionary algorithm()

Share：

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

29

Issue:

2013 2

Page:

207-210

Research Field:

Computer Science and Engineering

Publishing date:

2013-06-20

Info

Title:

Fuzzy traffic signal control with DNA evolutionary algorithm

Author(s):

Bi Yunrui¹;  Lu Xiaobo¹;  Sun Zhe²;  Zeng Weili³

¹School of Automation, Southeast University, Nanjing 210096, China
²Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China
³School of Transportation, Southeast University, Nanjing 210096, China

Keywords:

DNA evolutionary algorithm;  genetic algorithm(GA);  fuzzy control;  traffic signal control

PACS:

TP391

DOI:

10.3969/j.issn.1003-7985.2013.02.017

Abstract:

In order to optimize the signal control system, this paper proposes a method to design an optimized fuzzy logic controller(FLC)with the DNA evolutionary algorithm. Inspired by the DNA molecular operation characteristics, the DNA evolutionary algorithm modifies the corresponding genetic operators. Compared with the traditional genetic algorithm(GA), the DNA evolutionary algorithm can overcome weak local search capability and premature convergence. The parameters of membership functions are optimized by adopting the quaternary encoding method and performing corresponding DNA genetic operators. The relevant optimized parameters are combined with the FLC for single intersection traffic signal control. Simulation experiments shows the better performance of the FLC with the DNA evolutionary algorithm optimization. The experimental results demonstrate the efficiency of the proposed method.

References:

[1] Pappis C, Mamdani E. A fuzzy logic controller for a traffic junction [J]. IEEE Transactions on Systems, Man and Cybernetics, 1977, 7(10): 707-717.
[2] Trabia M B, Kaseko M S, Ande M. A two-stage fuzzy logic controller for traffic signals [J]. Transportation Research Part C, 1999, 7(6): 353-367.
[3] Murat Y S, Gedizlioglu E. A fuzzy logic multi-phased signal control model for isolated junctions [J]. Transportation Research Part C, 2005, 13(1): 19-36.
[4] Srinivasan D, Choy M C, Cheu R L. Neural networks for real-time traffic signal control [J]. IEEE Transactions on Intelligent Transportation Systems, 2006, 7(3): 261-272.
[5] Anderson J J, Sayers T M, Bell M G H. Optimizations of a fuzzy logic traffic signal controller by a multiobjective genetic algorithm [C]//Proceedings of the 9th International Conference on Road Transport Information and Control. London, UK, 1998:186-190.
[6] Garcia-Nieto J, Alba E, Olivera A C. Swarm intelligence for traffic light scheduling: application to real urban areas [J]. Engineering Applications of Artificial Intelligence, 2012, 25(2): 274-283.
[7] Dimitriou L, Tsekeris T, Stathopoulos A. Adaptive hybrid fuzzy rule-based system approach for modeling and predicting urban traffic flow [J]. Transportation Research Part C, 2008, 16(5): 554-573.
[8] Chen X, Wang N. A DNA based genetic algorithm for parameter estimation in the hydrogenation reaction [J]. Chemical Engineering Journal, 2009, 150(2/3): 527-535.
[9] Chen X, Wang N. Optimization of short-time gasoline blending scheduling problem with a DNA based hybrid genetic algorithm [J]. Chemical Engineering and Processing: Process Intensification, 2010, 49(10): 1076-1083.

Memo

Memo:

Biographies: Bi Yunrui(1983—), female, graduate; Lu Xiaobo(corresponding author), male, doctor, professor, xblu@seu.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.60972001), the Scientific Innovation Research of College Graduates in Jiangsu Province(No.CXZZ_0163), the Scientific Research Foundation of Graduate School of Southeast University(No.YBPY1212).
Citation: Bi Yunrui, Lu Xiaobo, Sun Zhe, et al. Fuzzy traffic signal control with DNA evolutionary algorithm[J].Journal of Southeast University(English Edition), 2013, 29(2):207-210.[doi:10.3969/j.issn.1003-7985.2013.02.017]

Common functions