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ReFOCUS: A hybrid fog-cloud based intelligent traffic re-routing system

The continuous rapid growth of vehicles and nonexpansion of existing infrastructure in large cities due to space constraints and heavy costs leads to increase the traffic congestion, which causes to increase the travel time of the drivers, fuel consumption, and emissions. In order to overcome the above-mentioned issues, this paper presents a novel method for dynamic rerouting system based on a hybrid FOG-Cloud intelligent control system called ReFOCUS, which is able to dynamically compute the best path for drivers those are in or will be in the congested area, based on the current traffic density of different regions with considering the road future congestion status. The system is implemented in a FOG-Cloud computing environment that can use traffic data of the roads and provide the necessary information in real-time to drivers where significantly decrease the data exchange compared to other cloud-based systems. Mathematical modeling and algorithm for the ReFOCUS has been proposed in this paper and a primary simulation has been done to evaluate the efficiency of the method. The results of the simulation illustrate that the proposed novel method can decrease the average travel time 65%, CO2 emission 36%, and fuel consumption 36%.