Intelligent Vehicular Traffic Control System Using Priority Longest Queue First Model

Samuel Sunday Udoh

Intelligent Vehicular Traffic Control System Using Priority Longest Queue First Model

Samuel Sunday Udoh * §

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University of Uyo

Intelligent Vehicular Traffic Control System Using Priority Longest Queue First Model

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Abstract

Traffic congestion of vehicles at road intersections is a growing problem in many developing countries of the world, especially in large urban areas. This stems from a continuous increase in the human population, poor road networks and the proliferation of vehicles for transportation of humans and goods from one location to another towards the performance of civil, social and economic activities. These vehicles often meet at road intersections and desire the Right-of-Way (RoW) towards their destination. This situation always results in race competition, traffic jam and gridlock condition with its attendant effects on time, fuel wastages as well as accident and fire outbreak which often results to loss of lives and property. The conventional traffic light control system which employs a static time cycle for issuance of RoW to each lane at the intersection lacks human-like intelligence and traffic situational awareness.

References

28 Cites in Article

Reference Format

Pavan Adnan,K Abdelwahed,M (2018). Smart TrafficController using Fuzzy Logic.
C Anuran,B Saumya,C Anirudhha (2014). Intelligent Traffic Control System using RFID.
A Escalera,J Armingol,M Mata (2013). Traffic sign recognition and analysis for intelligent vehicles.
Harpel Singh,Krishan Kumar,Harbans Kaur (2012). Intelligent Traffic Lights Based on RFID.
Udoinyang Inyang,Oluwole Akinyokun (2014). A hybrid knowledge discovery system for oil spillage risks pattern classification.
Alam Javed,Manoj Pandey,Kumar (2015). Design and Analysis of a Two Stage Traffic Light System Using Fuzzy Logic.
G Lee,S Kim (2002). A longitudinal control system for a platoon of vehicles using a fuzzy-sliding mode algorithm.
E Mamdani,S Assilian (1975). An experiment in linguistic synthesis with a fuzzy logic controller.
Marco Wiering,Jelle Van Veenen,Jilles Vrecken,Ame Koopman (2014). Intelligent.
Traffic Light Control.
N Maslekar,M Boussedjra,J Mouzna,H Labiod (2011). VANET Based Adaptive Traffic Signal Control.
J Mendel (2001). On the importance of interval sets in type-2 fuzzy logic systems.
J Mendel,Q Liang (2000). Pictorial Comparisons of Type-1 and Type-2 Fuzzy Logic Systems.
O Obot (2007). Neuro Fuzzy Expert System For the Diagnosis and Therapy of Cardiovascular Diseases.
C Osigwe,F Oladipo,E Onibere (2011). Design and simulation of Intelligent Traffic Control System.
Pati Vidya (2016). Intelligent Traffic Control System.
D Prajakta,W Seng,D Aniruddha,Jack (2011). Multi-Agent Based Vehicular Congestion Management, Intelligent Vehicles Symposium.
S Rajeswaran,S Rajasekaran (2013). A Study Of Vehicular Traffic Flow Modeling Based On Modified Cellular Automata.
P Sinhmar (2012). Intelligent traffic light and density control using IR sensors and microcontroller.
Ali Syed,Abass,Muhammed Syed,Humera Sheraz,Noor (2007). Fuzzy Rule Traffic Signal Control System for Oversaturated Intersections.
Malik Tubaishat,Yi Shang,Hongchi Shi (2007). Adaptive Traffic Light Control with Wireless Sensor Networks.
Enikanselu Adekunle,Balogun Adedoyin,Ewetumo Theophilus,A. A. Osinowo,Margaret Ogundare,Ashiru Raheemat,James Abe,A. S. Ifanegan,Babatande Okunlola (2016). Exploration of Wind-Wave Energy Potentials for Renewable Energy Development in Parts of Ondo Coastal and Offshore Locations, Southwestern Nigeria.
S Udoh,O Akinyokun,U Inyang,O Olabode,G Iwasokun (2017). Discrete event based hybrid framework for petroleum products pipeline activities classification.
S Udoh,U Umoh,M Umoh (2019). Diagnosis of Prostate Cancer using Soft Computing Paradigms.
E Uthara,Athira Prakash,Thankappan,K Vishnupriya,Arun Balakrishnan (2018). Density Based Traffic Control System using Image Processing.
L Zadeh (1975). MANAGEMENT OF UNCERTAINTY IN EXPERT SYSTEMS.
W Zhizhou,Z Yiming,T Guishan,H Jia (2019). The research of traf fic density extraction method under vehicular adhoc network environment.
B Zhou,J Cao,X Zeng,H Wu (2010). Adaptive traffic light control in wireless sensor network-based intelligent transportation system.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Samuel Sunday Udoh. 2021. "Intelligent Vehicular Traffic Control System Using Priority Longest Queue First Model". Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 21 (GJCST Volume 21 Issue D1).

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GJCST Volume 21 Issue D1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-D Classification I.2.0

Submission ReceivedJune 10, 2021
Peer Review Double Blind
Handling Editor
Accepted July 3, 2021
Published July 15, 2021

Version of record

v1.2

Issue date

March 25, 2021

Language

English

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