Design and Implementation of Smart Traffic Light System Using Renewable Energy, Fail-Safe Systems, and Intelligent Sensors

Abstract

To overcome the disadvantages of traditional traffic lights, this study provides a detailed examination of the development and implementation of a smart traffic light system. The research focuses on developing cutting-edge smart traffic light systems that incorporate intelligent sensors for real-time data collection, fail-safe mechanisms, energy efficiency, and renewable energy sources. The recommended system uses infrared (IR) sensors to track autos and collect exact data for simulations. The system uses this technology to detect lane violations, reduce wait times, avoid inadvertent crashes, and make empty lanes simpler to pass. It also allows for the tracking of vehicle numbers over different weekdays and hours to help with traffic control. The system was evaluated using a simulation program written in Python and powered by the Ursina engine. This software allows the proposed ideas to be tested and confirmed in a realistic setting. The results' correctness and realism are examined, and prior simulations using OpenStreetMap (OSM) are also discussed. The program also looks into other capabilities, such as tracking vehicle movement across the city by capturing license plates and routes, as well as assessing the time between traffic lights to identify speeding cars. This research increases traffic management and safety by incorporating revolutionary traffic signal designs, energy-saving approaches, fail-safe systems, intelligent sensors, and simulation software. The findings provide politicians and urban planners with critical new knowledge.