Abstract
For the complex and time-varying traffic flow, single-strategy based fuzzy traffic control algorithms are not very ideal. In order to further improve the capacity of isolated intersection, we propose a multi-strategy fuzzy control algorithm to adapt to the variation of urban traffic flow, and then optimize its control rules and membership functions by using improved genetic algorithm. The simulation result shows that compared with traditional genetic algorithm, the efficiency of improved genetic algorithm is higher, and its performance is more stable. The multi-strategy fuzzy control model possesses the stronger self-adaptive competence and performance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Pappis, C.P., Mamdani, E.H.: A Fuzzy Logic Controller for a Traffic Junction. IEEE Trans on Systems, Man, and Cybernetics SMC-7(10), 707–717 (1977)
Chih-Hsun, C., Jen-Chao, T.: A fuzzy controller for traffic junction signals. Information Sciences 143, 73–97 (2002)
Niittymaki, J., Pursula, M.: Signal Control Using fuzzy logic. Fuzzy Sets and Systems 116, 11–22 (2000)
Qiao, J., Xuan, H.-y.: A Need Degree-based Isolated Intersection Fuzzy Control Algorithm. Systems Engineering 22(10), 59–64 (2004)
Pedrycz, W.: Fuzzy control and Fuzzy Systems, 2nd extended edn. Wiley, New York (1993)
Michalewicz, Z.: Genetic Algorithms + Data Structures = Evolution Programs, 3rd edn. Springer, Heidelberg (1996)
Herrera, F., Lozano, M., Verdegay, J.L.: Tuning fuzzy logic controllers by genetic algorithms. International Journal of Approximate Reasoning 12, 299–315 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Qiao, J., Xuan, H., Jiang, J. (2005). Improvement of Genetic Algorithm and Its Application in Optimization of Fuzzy Traffic Control Algorithm. In: Megiddo, N., Xu, Y., Zhu, B. (eds) Algorithmic Applications in Management. AAIM 2005. Lecture Notes in Computer Science, vol 3521. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11496199_16
Download citation
DOI: https://doi.org/10.1007/11496199_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26224-4
Online ISBN: 978-3-540-32440-9
eBook Packages: Computer ScienceComputer Science (R0)