Enabling Smart City With Intelligent Congestion Control Using Hops With a Hybrid Computational Approach

Author:

Abbas Sagheer1,Khan Muhammad Adnan2,Athar Atifa3,Shan Syed Ali4,Saeed Anwar4,Alyas Tahir2

Affiliation:

1. School of Computer Sciences, National College of Business Administration and Economics, Gulberg-III, 54000, Lahore, Pakistan

2. Department of Computer Science, Lahore Garrison University, DHA Phase-6, Sector-C, 54000, Lahore, Pakistan

3. Department of Computer Science, CUI, 54000, Lahore, Pakistan

4. Department of Computer Science & IT, Virtual University of Pakistan, 54000, Lahore, Pakistan

Abstract

ABSTRACT In a smart city, the subject of the congestion-free traffic has been leading objectives from the past decade, and many approaches are adopted to make congestion-free roads. These approaches and signals at one junction are not inter-linked with the signal at the previous one. Therefore, the traffic flow on the same road and at associative roads is not smooth. The study proposed a model with a hybrid computational approach in which the current signal incorporates the associative signals information. Simulation results have shown that the proposed approach gives more attractive results as compared to previously published approaches. It will help improve the flow of traffic and reduce traffic congestion.

Publisher

Oxford University Press (OUP)

Subject

General Computer Science

Reference16 articles.

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2. Large-scale transportation network congestion evolution prediction using deep learning theory;Ma;PLoS One,2015

3. Modelling smart road traffic congestion control system using machine learning techniques;Ata;Neural Netw. World,2019

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