Controlling traffic flow in multilane-isolated intersection using ANFIS approach techniques

Many controllers have applied the Adaptive Neural-Fuzzy Inference System (ANFIS) concept for optimizing the controller performance. However, there are less traffic signal controllers developed using the ANFIS concept. ANFIS traffic signal controller with its fuzzy rule base and its ability to learn...

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Main Authors: Lai, Ghuan Rhung, Che Soh, Azura, Md. Sarkan, Haslina, Abdul Rahman, Ribhan Zafira, Hassan, Mohd Khair
Format: Article
Language:English
Published: School of Engineering, Taylor's University 2015
Online Access:http://psasir.upm.edu.my/id/eprint/36910/
http://psasir.upm.edu.my/id/eprint/36910/1/Controlling%20traffic%20flow%20in%20multilane-isolated%20intersection%20using%20ANFIS%20approach%20techniques.pdf
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author Lai, Ghuan Rhung
Che Soh, Azura
Md. Sarkan, Haslina
Abdul Rahman, Ribhan Zafira
Hassan, Mohd Khair
author_facet Lai, Ghuan Rhung
Che Soh, Azura
Md. Sarkan, Haslina
Abdul Rahman, Ribhan Zafira
Hassan, Mohd Khair
author_sort Lai, Ghuan Rhung
building UPM Institutional Repository
collection Online Access
description Many controllers have applied the Adaptive Neural-Fuzzy Inference System (ANFIS) concept for optimizing the controller performance. However, there are less traffic signal controllers developed using the ANFIS concept. ANFIS traffic signal controller with its fuzzy rule base and its ability to learn from a set of sample data could improve the performance of Existing traffic signal controlling system to reduce traffic congestions at most of the busy traffic intersections in city such as Kuala Lumpur, Malaysia. The aim of this research is to develop an ANFIS traffic signals controller for multilane-isolated four approaches intersections 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 generated based on fuzzy rules and can be analysed using tree diagram. This controller is simulated on multilane-isolated 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.
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spelling upm-369102020-07-06T03:33:23Z http://psasir.upm.edu.my/id/eprint/36910/ Controlling traffic flow in multilane-isolated intersection using ANFIS approach techniques Lai, Ghuan Rhung Che Soh, Azura Md. Sarkan, Haslina Abdul Rahman, Ribhan Zafira Hassan, Mohd Khair Many controllers have applied the Adaptive Neural-Fuzzy Inference System (ANFIS) concept for optimizing the controller performance. However, there are less traffic signal controllers developed using the ANFIS concept. ANFIS traffic signal controller with its fuzzy rule base and its ability to learn from a set of sample data could improve the performance of Existing traffic signal controlling system to reduce traffic congestions at most of the busy traffic intersections in city such as Kuala Lumpur, Malaysia. The aim of this research is to develop an ANFIS traffic signals controller for multilane-isolated four approaches intersections 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 generated based on fuzzy rules and can be analysed using tree diagram. This controller is simulated on multilane-isolated 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. School of Engineering, Taylor's University 2015 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/36910/1/Controlling%20traffic%20flow%20in%20multilane-isolated%20intersection%20using%20ANFIS%20approach%20techniques.pdf Lai, Ghuan Rhung and Che Soh, Azura and Md. Sarkan, Haslina and Abdul Rahman, Ribhan Zafira and Hassan, Mohd Khair (2015) Controlling traffic flow in multilane-isolated intersection using ANFIS approach techniques. Journal of Engineering Science and Technology, 10 (8). pp. 1009-1034. ISSN 1823-4690 http://jestec.taylors.edu.my/V10Issue8.htm
spellingShingle Lai, Ghuan Rhung
Che Soh, Azura
Md. Sarkan, Haslina
Abdul Rahman, Ribhan Zafira
Hassan, Mohd Khair
Controlling traffic flow in multilane-isolated intersection using ANFIS approach techniques
title Controlling traffic flow in multilane-isolated intersection using ANFIS approach techniques
title_full Controlling traffic flow in multilane-isolated intersection using ANFIS approach techniques
title_fullStr Controlling traffic flow in multilane-isolated intersection using ANFIS approach techniques
title_full_unstemmed Controlling traffic flow in multilane-isolated intersection using ANFIS approach techniques
title_short Controlling traffic flow in multilane-isolated intersection using ANFIS approach techniques
title_sort controlling traffic flow in multilane-isolated intersection using anfis approach techniques
url http://psasir.upm.edu.my/id/eprint/36910/
http://psasir.upm.edu.my/id/eprint/36910/
http://psasir.upm.edu.my/id/eprint/36910/1/Controlling%20traffic%20flow%20in%20multilane-isolated%20intersection%20using%20ANFIS%20approach%20techniques.pdf