A Review Paper On Intelligent Traffic Signal Control System Based On Machine Learning

Authors: Prof. S.M. Chougule, Ms. Vaishnavi Gaikwad, Mr. Avish Jadhav, Mr. Gaurav Jadhav, Mr. Sanskar Yadav, Mr. Pawan Yewale, Mr.Shreyash Jadhav, Mr. Harshwardhan Chavan, Mr. Aditya Jadhav

Abstract: Traffic congestion has become a major problem in urban areas due to the rapid increase in the number of vehicles. Traditional traffic signal systems operate on fixed timing methods, which often lead to unnecessary delays and traffic jams. The Intelligent Traffic Signal Control System based on Machine Learning is designed to improve traffic management by dynamically controlling signal timings according to real-time traffic density. The proposed system uses cameras and machine learning algorithms to detect the number of vehicles on each road. Based on traffic density analysis, the system automatically adjusts signal timing to reduce waiting time, fuel consumption, and traffic congestion. The intelligent system improves road efficiency and supports smart city development. Machine learning techniques help in predicting traffic flow and making faster decisions compared to conventional systems. This project provides an effective, economical, and scalable solution for modern traffic management systems.

DOI: http://doi.org/10.5281/zenodo.20521943