A Study on Using AI for Traffic Management System

This research scrutinizes the disruptive influence of digital commerce platforms on the fresh fruit export 
trade originating from the Pune district, focusing on the high-value commodities of Grapes and Pomegranates. 
Intelligent traffic management systems are increasingly required to address severe congestion in rapidly 
growing urban areas. Conventional fixed-time traffic signals often cause inefficiencies, including long waiting 
times and traffic jams at busy intersections. This study proposes an AI-driven traffic light management system 
using YOLO-based vehicle detection and dynamic signal control. Real-time images from IP cameras are 
processed to estimate vehicle density across multiple lanes. Based on traffic conditions, signal timings are 
adaptively adjusted to prioritize highly congested lanes while maintaining fair signal distribution. The system is 
fully software-based and implemented using Python, OpenCV, and Ultra lytic YOLO. Experimental results 
indicate improved traffic flow efficiency compared to traditional static traffic signal systems.