Syed Thousif , Kambam Nithin Kumar Reddy , Gajjula Ashok Vardhan Reddy , Kummara Sruthi "Smart AI-Based Traffic and Parking Management System Using Machine Learning and Computer Vision"

Paper_id: 30_3

Abstract

Traffic congestion and difficulties in parking have become common problems in contemporary cities due to the rapid urbanization. The conventional traffic control systems are dynamic and do not reflect the actual traffic conditions. The present paper suggests a Smart AI-Based Traffic and Parking Management System which will combine the concepts of machine learning and computer vision to forecast traffic jams and find vacant parking spots in real-time. The system relies on the algorithm of the Random Forest to compare historical and real- time traffic data, as a result of which intelligent traffic movement forecasts and adaptive traffic lights control are possible. The use of computer vision can be used to track the parking space and aid an early reservation of parking. The suggested system is more efficient in traffic, it lowers down congestion, the travel time is also minimized and emergency vehicles are also prioritized. The solution offers scalable and cost-effective solution to smart city transportation systems