NDLI: An Intelligent Control Method for Urban Traffic Signal Based on Fuzzy Neural Network

Content Provider	IEEE Xplore Digital Library
Author	Lilin Zang Lei Jia Yonggang Luo
Copyright Year	2006
Description	Author affiliation: Sch. of Control Sci. & Eng., Shandong Univ. (Lilin Zang; Lei Jia)
Abstract	The paper presents a traffic signal control method using a layer-structured fuzzy neural network (FNN) for learning rules of fuzzy logic control system. The FNN has advantages of both fuzzy expert system (fuzzy reasoning) and artificial neural network (self-study). The system is not needed to build the model of traffic flow for signal control approach at an intersection, it can be successfully trained to adapt different traffic flow and different conditions at the intersection based on the real-time data. This significantly reduces a lot of effort of extracting traffic expert's knowledge into fuzzy if-then rules. In order to get better dynamic response and reduce the computing capacity, the weights of FNN are optimized and the step length for self-study is modified based on fuzzy logic. Compared with traditional fuzzy control plan for traffic signal, the proposed FNN algorithm shows better performances and adaptability
Starting Page	3430
Ending Page	3434
File Size	130249
Page Count	5
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1713005
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent control Communication system traffic control Fuzzy neural networks Fuzzy control Traffic control Control systems Fuzzy logic Hybrid intelligent systems Fuzzy reasoning Artificial neural networks simulation Traffic signal control Fuzzy neural network optimization
Content Type	Text
Resource Type	Article

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