Traffic Flow Optimizer: Traffic Signal Control With Vehicle Density and Algorithms

Abstract

The goal of this work is to create an intelligent traffic signal control system that will enhance intersection traffic flow. The major goals are to reduce traffic congestion, expedite travel, and improve all-around road safety. To estimate traffic density in real time, the system uses image processing methods, specifically vehicle detection algorithms. The computer vision library is used to evaluate surveillance camera footage at traffic lights in order to precisely count vehicles and gauge traffic density. To detect vehicles and precisely count them, a variety of image processing techniques are applied, such as object recognition and background subtraction. The number of vehicles per area or lane is then taken into account when calculating traffic density. A central server receives this data for further processing.