Freeway Traffic Congestion Identification Based on Fuzzy Logic Inference

Abstract:

Traffic congestion detection is the basis of dynamic traffic control and real time guidance. This study proposes a fuzzy logic based traffic congestion identification method. The components of a fuzzy logic inference are firstly formulated. According to such information as the speed and occupancy of freeway traffic flow, and the weather conditions on the freeway, a congestion identification method based on fuzzy logic inference is then designed. Gauss curves are assumed for the membership functions of the input and output variables, and 45 fuzzy rules are also established. Finally, the congestion identification method is simulated. Simulation results verify the effectiveness of the above method. Fuzzy logic inference is suitable for estimating the traffic congestion index.

• Periodical: Applied Mechanics and Materials (Volumes 397-400)
• Pages: 2227-2230
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.397-400.2227
• Online since: September 2013
• Authors: Ming Long Peng, Xin Rong Liang, Chao Jun Dong, Yan Yan Liu
• Keywords: Freeway, Fuzzy Logic Inference, Simulation, Traffic Congestion Identification

References

[1] G. Y. Jiang, S. F. Niu, A. D. Chang: Proc. of the Second International Conference on Advanced Computer Control. Vol. 2 (2010), p.648.

[2] Z. Q. Sun, J. Q. Feng, W. Liu: Proc. of the eighth Conference on Natural Computation. Vol. 1 (2012), p.286.

[3] G. Y. Jiang, L. H. Gang, J. F. Wang: Journal of Traffic and Transportation Engineering. Vol. 6 (2006), p.87 (In Chinese).

[4] J. M. Hu: IET Intelligent Transport Systems. Vol. 6 (2012), p.153.

[5] X. R. Liang, Z. Y. Liu, Z. Y. Mao: Control Theory and Applications. Vol. 23 (2006), p.99 (In Chinese).

[6] X. R. Liang, D. Q. Wang: Applied Mechanics and Materials. Vols. 220-223 (2012), p.988.