Title of article
Formalized learning automata with adaptive fuzzy coloured Petri net; an application specific to managing traffic signals
Author/Authors
Barzegar, S. islamic azad university - Department of Electronic and Computer Engineering, ايران , Davoudpour, M. Ryerson University - Department of Computer Science, Canad , Meybodic, M.R. amirkabir university of technology - Department of Computer Engineering and Information Technology, تهران, ايران , Sadeghian, A. Ryerson University - Department of Computer Science, Canada , Tirandazian, M. Ryerson University - Department of Computer Science, Canada
From page
554
To page
565
Abstract
Investigation of the chaotic behavior of traffic streams at urban intersections due to signals has involved researchers in endeavoring to predict a smooth traffic flow model for stabilizing traffic congestion and avoid unnecessary delays. In this paper, we study a hybrid adaptive model, based on a combination of coloured Petri nets, fuzzy logic and learning automata, to efficiently control traffic signals. We show that m comparison with results found in the literature, vehicle delay time is significantly reduced using the proposed method.
Keywords
Adaptive coloured Petrinets , Fuzzy logic , Learning automata , Traffic signal control.
Journal title
Scientia Iranica(Transactions B:Mechanical Engineering)
Journal title
Scientia Iranica(Transactions B:Mechanical Engineering)
Record number
2718269
Link To Document