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MRGM: an adaptive mechanism for congestion control in smart vehicular network

journal contribution
posted on 10.11.2020, 03:35 by GS Shahi, RS Batth, Simon Egerton
© 2020, Kohat University of Science and Technology. Traffic flow on roads has increased manifolds from past few decades due to increase in number of vehicles and rise in population. With fixed road infrastructure and more vehicles on traffic routes lead to traffic congestion conditions especially in urban areas of developing nations. Traffic jams are normal in major cities which ultimately cause delay in travel time, more fuel consumption and more pollution. This manuscript propose a Multi-metric road guidance mechanism (MRGM) which considers multiple metrics to analyze the traffic congestion conditions and based on the conditions effective optimal routes are suggested to the vehicles. The Simulation of the proposed mechanism is performed with the SUMO by using the python script and the results show that proposed mechanism i.e. MRGM outperforms other mechanism in terms of traffic efficiency, travel time, fuel consumption and pollution levels in the smart vehicular network.

History

School

  • School of Engineering and Mathematical Sciences

Publication Date

01/08/2020

Journal

International Journal of Communication Networks and Information Security

Volume

12

Issue

2

Pagination

8p. (p. 273-280)

Publisher

Kohat University of Science and Technology, Institute of Information Technology

ISSN

2076-0930

Rights Statement

The Author reserves all moral rights over the deposited text and must be credited if any re-use occurs. Documents deposited in OPAL are the Open Access versions of outputs published elsewhere. Changes resulting from the publishing process may therefore not be reflected in this document. The final published version may be obtained via the publisher’s DOI. Please note that additional copyright and access restrictions may apply to the published version.

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