Communication Improvement and Traffic Control Based on V2I in Smart City Framework

Abstract

This article describes how soft computing techniques are tolerant of imprecision, intended on approximation, focus on uncertainty and are based on partial truth. Current real-world problems pertaining to congested traffic is pervasively imprecise and therefore design of smart traffic control system is a challenging issue. Due to the increasing rate of vehicles at traffic points in smart cities, it creates unexpected delays during transit, chances of accidents are higher, unnecessary fuel consumption is an issue, and unhygienic environment due to pollution also degrades the health condition of general people in a normal city scenario. To avoid such problems many smart cities are currently implementing improved traffic control systems that work on the principle of traffic automation to prevent these issues. The basic challenge lies in the usage of real-time analytics performed with online traffic information and correctly applying it to some traffic flow. In this research article, an enhanced traffic management system called SCICS (Soft Computing based Intelligent Communication System) has been proposed which uses swarm intelligence as a soft computing technique with intelligent communication between smart vehicles and traffic points using the vehicle to infrastructure (V2I) concept of VANET. It uses an improved route diversion mechanism with implemented logic in nanorobots. Under a vehicular ad-hoc network (VANET) scenario, the communication between intelligent vehicles and infrastructure points takes place through nanorobots in a collaborative way. Simulation carried out using Ns2 simulator shows encouraging results in terms of better performance to control the traffic.