NDLI: Traffic signal control based on Adaptive Neural-Fuzzy Inference System applied to intersection

Content Provider	IEEE Xplore Digital Library
Author	Soh, A.C. Rahman, R.Z.A. Lai Ghuan Rhung Sarkan, H.M.
Copyright Year	2011
Description	Author affiliation: Advanced Informatics School, UTM International Campus, 54100, Kuala Lumpur, Malaysia (Sarkan, H.M.) \|\| Department Electrical & Electronic Engineering, Universiti Putra Malaysia, 43400, Selangor, Malaysia (Soh, A.C.; Rahman, R.Z.A.; Lai Ghuan Rhung)
Abstract	Adaptive Neural-Fuzzy Inference System (ANFIS) that integrates the best features of fuzzy systems and neural networks has been widely applied in many areas. It can be applied to synthesize controllers, which are able to tune the fuzzy control system automatically, and models that learn from past data to predict future behavior. The aim of this research is to develop an ANFIS traffic signals controller for multilane intersection in order to ease traffic congestions at traffic intersections. The new concept to generate sample data for ANFIS training is introduced in this research. The sample data is generate based on fuzzy rules and can be analysed using tree diagram. This controller is simulated on multilane traffic intersection model developed using M/M/1 queuing theory and its performance in terms of average waiting time, queue length and delay time are compared with traditional controllers and fuzzy controller. Simulation result shows that the average waiting time, queue length, and delay time of ANFIS traffic signal controller are the lowest as compared to the other three controllers. In conclusion, the efficiency and performance of ANFIS controller are much better than that of fuzzy and traditional controllers in different traffic volumes.
Starting Page	231
Ending Page	236
File Size	515361
Page Count	6
File Format	PDF
ISBN	9781612849317
e-ISBN	9781612849317
DOI	10.1109/ICOS.2011.6079251
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-25
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Firing Multilane intersection Neurons Switches ANFIS controller Next phase module Decision module Queueing analysis Delay Vehicles Green phase module
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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