Smart Signal Optimization System

Urban traffic congestion has become a major problem due to the rapid increase in vehicle density and inefficient traffic management systems. Traditional traffic signals operate on fixed timing cycles without considering the actual number of vehicles on each road, which results in unnecessary delays, fuel wastage, and increased pollution. This project proposes a Smart Signal Optimization System using ESP32 and IR sensors to dynamically control traffic signals based on vehicle density. The system uses four IR sensors placed at four different lanes to detect vehicles waiting at the signal. The ESP32 microcontroller processes the sensor data and controls the traffic signals through red, yellow, and green LEDs. The system counts the number of vehicles waiting in each lane and automatically gives priority to the lane with higher traffic density. If a lane exceeds a predefined vehicle count threshold, the system temporarily prioritizes that lane to reduce congestion. Additionally, the ESP32 WiFi capability allows the system to host a simple web dashboard that displays real-time traffic signal status and vehicle count. This smart traffic management approach improves traffic flow efficiency, reduces waiting time, and supports the development of intelligent transportation systems in smart cities. Keywords: Smart Traffic System, IR Sensor, ESP32, Traffic Signal Optimization, IoT Traffic Control.