Congestion Control by Reducing Wait Time at the Traffic Junction Using Fuzzy Logic Controller

Author(s): Manpreet Singh Bhatia*, Alok Aggarwal

Journal Name: International Journal of Sensors, Wireless Communications and Control

Volume 10 , Issue 6 , 2020

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Graphical Abstract:


Background: Traffic congestion is one of the most severe problems especially in metro cities due to ever increasing number of vehicles on roads by 20% per year even with well-planned road management system and sufficient infra.

Objectives: Most of the existing traffic signal controllers use fixed cycle type, giving a constant green/red/yellow phase for each traffic signal cycle. These traditional controllers cannot adapt the dynamics of traffic at real time which a traffic man can do.

Methods: Deploying traffic men at every traffic light junction is not feasible due to manpower shortage and cost considerations. In this work a three input fuzzy controller is proposed which can adapt the dynamics of real time traffic and reduce the congestion at the traffic light junction. Proposed fuzzy controller has three inputs namely; queue length, arrival rate and peak hours and one output parameter, time extension which is to be controlled by the use of the three input parameters.

Results: All four lanes have been allocated a fixed green signal time of 60 seconds at the start. Extension/ decrease of the green light is done dynamically with ±28 seconds. Compared to conventional fixed cycle type, proposed approach gives a minimum improvement of 6% and a maximum of 47% depending on various traffic conditions at the junction.

Conclusion: In terms of CO2 emission improvement of 20% and 42.12% and in terms of fuel consumption improvement of 34.73% and 57.18% has been observed compared to UCONDES (Urban CONgestion DEtection System) and OVMT (Original Vehicular Mobility Trace) respectively.

Keywords: Defuzzification, fuzzy controller, fuzzification, fuzzy inference, traffic congestion, OVMT.

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Article Details

Year: 2020
Published on: 10 February, 2021
Page: [989 - 1000]
Pages: 12
DOI: 10.2174/2210327910666200226113614
Price: $25

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