Four way effective traffic management system

Abstract

This study presents a comprehensive approach to developing an effective traffic management system for a four-way intersection. To optimize traffic flow and alleviate congestion, the system incorporates fuzzy logic, image processing, and proximity sensors. The study compares the performance of each technology and concludes that proximity sensors are the best option due to their high accuracy, low cost, and ease of deployment. The suggested system detects the presence of vehicles and adjusts traffic lights in real time using proximity sensors. The duration of the green light is controlled by fuzzy logic based on the number of vehicles in each lane, while image processing is employed to detect and respond to emergency vehicles. The system is tested using simulations and demonstrates considerable improvements in traffic flow and waiting times, particularly during high traffic hours. The study emphasizes proximity sensors' potential as a cost-effective and dependable solution for traffic control systems, particularly in developing nations. The findings of this research can help transportation planners and policymakers design successful traffic control systems in their cities.