Research on Traffic Signal Timing Method Based on Ant Colony Algorithm and Fuzzy Control Theory

Authors

  • Linlin Li College of Computer Science and Technology, Jilin University, China
  • Yunhan Ma Department of Statistics, College of Mathematics, Jilin University, China
  • Baiqi Wang College of Computer Science and Technology, Jilin University, China
  • Hongliang Dong Banine Technologies Ltd. Data & Info Research Lab, China
  • Zhanyang Zhang Computer Science Department, Graduate Center, City University of New York, USA

Keywords:

intelligent traffic, dynamic timing, fuzzy control, ant colony

Abstract

The number of private cars has a blowout growth with the development of economics, which leads to the existing limited traffic resources cannot meet the normal traffic demand. The emergence of intelligent traffic has improved this phenomenon. Using intelligent traffic technology to conduct intersection vehicles can alleviate the congestion effectively. Traffic signal timing method plays an important role in intelligent traffic research. An independent intersection dynamic timing method combined with fuzzy control theory and improved ant colony algorithm is proposed in this paper. According to the characteristics of traffic flow distribution, the timing period is obtained with the improved webster algorithm. Through the optimal solution obtained by ant colony algorithm and the added delay of traffic signal calculated by fuzzy control method, the dynamic timing period of the traffic signal is obtained. The validity of the proposed method is proved by comparing with the original time period and the traditional algorithm.

References

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Published

2019-01-01

How to Cite

[1]
L. Li, Y. Ma, B. Wang, H. Dong, and Z. Zhang, “Research on Traffic Signal Timing Method Based on Ant Colony Algorithm and Fuzzy Control Theory”, Proc. eng. technol. innov., vol. 11, pp. 21–29, Jan. 2019.

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Articles