An optimal Internet of Things–based smart cities using vehicular cloud for smart driving

摘要

Empowering vehicular cloud can be done by having certain snapshot of the quantity of vehicles and their accessibility in a given lane through a model, and in addition, some additional framework, including movement of vehicles. The quantity of vehicles determines the calculation abilities accessible in this area and the traveling time shows the time of validity for a particular lane. Accordingly, in this paper, we do research using stochastic investigation of a few traffic attributes identified with the usage of cloud computing in a street portion to embrace appropriate activity prototypes. In particular, we have two sorts of activity situations that are considered: free-flow movement and queueing- up activity. We utilize a perceptible traffic model to explore the free-flow activity and examine some parameters, for example, activity thickness, vehicles quantity, and living arrangement time. Likewise, we use the queueing- up hypothesis to demonstrate the queue movement; the line length and the holding up time in the line are investigated. The outcomes will be presented for the customers who got struck in road traffic a common problem in all countries to get rid of traffic conditions. By using this, an alternate route will be predicted for the customer which is traffic free while driving.