DocumentCode :
476121
Title :
An intelligent traffic light control method based on extension theory for crossroads
Author :
Chao, Kuei-Hsiang ; Lee, Ren-hao ; Yen, Kun-Lung
Author_Institution :
Dept. of Electr. Eng., Nat. Chin-Yi Univ. of Technol., Taichung
Volume :
4
fYear :
2008
fDate :
12-15 July 2008
Firstpage :
1882
Lastpage :
1887
Abstract :
This paper presents an intelligent traffic light control method based on extension theory for crossroads. First, the number of passing vehicles and maximum passing time of one vehicle within green light time period are measured in the main-line and sub-line of a selected crossroad. Then, the measured data are adopted to construct the extended matter-element model and accordingly the correlation degrees are calculated for recognizing the traffic flow of a standard crossroad. Some experimental results are made to verify the effectiveness of the proposed intelligent traffic flow control method. The diagnostic results indicate that the proposed estimated method can discriminate the traffic flow of a standard crossroad rapidly and accurately.
Keywords :
automated highways; intelligent control; road traffic; road vehicles; correlation degree; crossroad; extended matter-element model; extension theory; green light time period; intelligent traffic light control method; traffic flow recognition; Artificial neural networks; Convergence; Evolutionary computation; Fuzzy control; Intelligent control; Lighting control; Machine learning; Optimization methods; Traffic control; Vehicles; Correlation Degree; Extended Matter-element Model; Extension Theory; Traffic Flow Control; Traffic Light System;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
Type :
conf
DOI :
10.1109/ICMLC.2008.4620713
Filename :
4620713
Link To Document :
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