Title :
Estimation of optimal green time simulation using fuzzy neural network
Author :
You Sik Hong ; JongSoo, Kim ; Son, JeongKwang ; Chongkug Park
Author_Institution :
Dept. of Comput. Sci., Sangji Univ., Wonju, South Korea
Abstract :
In the past, when there were few vehicles on the road, the TOD (time of day) traffic signal worked very well. The TOD signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Today, with increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end lag time so that thirty to forty-five percent efficiency in traffic handling is lost, as well as adding to fuel costs. To solve this problem, the paper proposes a concept of the optimal green time algorithm, which reduces average vehicle waiting time while improving average vehicle speed using fuzzy rules and neural networks. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signals. The fuzzy neural network will consistently improve average waiting time, vehicle speed, and fuel consumption.
Keywords :
digital simulation; fuzzy control; fuzzy neural nets; neurocontrollers; road traffic; traffic control; average vehicle speed; average vehicle waiting time; fuzzy rules; optimal green time simulation; Communication system traffic control; Computer simulation; Delay effects; Fuels; Fuzzy control; Fuzzy neural networks; Neural networks; Road vehicles; Telecommunication traffic; Traffic control;
Conference_Titel :
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International
Conference_Location :
Seoul, South Korea
Print_ISBN :
0-7803-5406-0
DOI :
10.1109/FUZZY.1999.793044