Smart Traffic Control System Based on Neural Network

Abstract

This paper presents a smart traffic light control technique based on neural system NN as a hypothesis for the intersection. In the first place, the quantity of taking a break of one vehicle inside a green light time frame is estimated in the fundamental line and sub-line of a choose intersection. At that point, the estimated information is received to develop an estimation strategy dependent on NN for perceiving the traffic stream of a standard intersection. Some exploratory outcomes are made to check the viability of the proposed acute traffic stream control strategy. The demonstrative outcomes show that the proposed evaluation strategy can segregate the traffic stream of a standard intersection quickly and precisely. Also, consist of multi agent mechanism and decision-making using hybrid NN. Through a hybrid neural network, 80% result can be achieved.