MRGM: An Adaptive Mechanism for Congestion Control in Smart Vehicular Network

Main Article Content

Gurpreet singh Shahi
Ranbir Singh Batth
Simon Egerton


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.

Article Details

How to Cite
Shahi, G. singh, Batth, R. S., & Egerton, S. (2020). MRGM: An Adaptive Mechanism for Congestion Control in Smart Vehicular Network. International Journal of Communication Networks and Information Security (IJCNIS), 12(2).
Research Articles
Author Biographies

Gurpreet singh Shahi, Lovely Professional University

Assistant professor

Ranbir Singh Batth, Lovely Professional University

Associate Professor

Simon Egerton, La Trobe University

Associate Professor