Advanced Driver Assistance System to Avoid Accidents at T-Junctions in India - Vaibhavi B Wali; Dr. Mohammed Abdul Waheed; Saniya Farheen (Utilitas Mathematica, 2025)
T-junctions on Indian roads are highly prone to vehicular collisions due to limited visibility, poor traffic regulation, and unpredictable driver behaviour. To address this critical issue, an intelligent and cost-effective Advanced Driver Assistance System (ADAS) is proposed to proactively detect potential collisions and enhance driver awareness at T-junctions. The system utilizes a master–slave architecture comprising one Arduino Mega microcontroller (master) and three Arduino Uno boards (slaves). Each slave is equipped with ultrasonic sensors to detect approaching vehicles at junction arms, and data is transmitted wirelessly to the master using ZigBee modules. The master node aggregates sensor inputs and displays real-time alerts on three 16x2 LCD modules, installed strategically to warn oncoming drivers. Additionally, a piezo sensor is integrated with the master controller to detect collision impacts and capture GPS location for emergency response. The system leverages the ESP8266 Wi-Fi module to push accident or congestion data to the Adafruit IO cloud platform for remote monitoring and analysis. Experimental testing in a prototype environment demonstrated reliable vehicle detection, low-latency communication, and accurate event logging. This integrated approach offers a scalable, low-power solution that can be deployed in accident-prone junctions to minimize risk and improve road safety through real-time, data-driven interventions.