Genetic programming tuned fuzzy controlled traffic light system

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Padmasiri:2014:ICTer,

• author = "T. D. N. D. Padmasiri and D. N. Ranasinghe",
• booktitle = "2014 International Conference on Advances in ICT for Emerging Regions (ICTer)",
• title = "Genetic programming tuned fuzzy controlled traffic light system",
• year = "2014",
• pages = "91--95",
• abstract = "A blend of fuzzy logic and genetic programming is used in this research to achieve a single fine-tuned fuzzy rule, upon giving hundreds of fuzzy rules as the input. The system has Poisson arrival rate of vehicles, and decisions are taken to alter the sequence of lights based on the queue lengths of the lanes. The traffic simulator handles routing of vehicles in a single four-leg intersection with left and right turns. The fuzzy logic traffic controller system is used to generate the simulation data to feed the genetic programming system. The genetic programming system then creates an optimum fuzzy rule. This fine-tuned fuzzy rule is proven to be qualitatively better with respect to the mean square queue length and its error of the total system at any given point of time.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ICTER.2014.7083885",
• month = dec,
• notes = "Also known as \cite{7083885}",

}

Genetic Programming entries for T D N D Padmasiri D N Ranasinghe

Citations