Road Steering system with several metrics (RSSSM): A novel technique for a Smart Vehicular Network to control congestion

Abstract

Due to a growth in the number of vehicles and people, traffic flow on highways has expanded dramatically during the last few decades. Congestion is caused by fixed road infrastructure and excessive traffic on traffic lanes, especially in developing international cities. In major cities, traffic bottlenecks are common, resulting in increased travel time, increased fuel use, and increased pollution. This paper proposes a Road Steering system with several metrics(RSSSM) that analyses traffic congestion circumstances using many metrics and suggests efficient best routes to vehicles based on those conditions. The suggested mechanism is simulated in the smart vehicular network using SUMO and a python script. The suggested mechanism, RSSSM, beats existing systems, according to the data whether efficiency of traffic, duration of journey, consumption of fuel or level of pollutions are concerned.