Autonomous Vehicle Accident Detection with Event Data Recording for Accident Analysis

The increasing occurrence of traffic accidents necessitates innovative solutions to enhance vehicle safety and improve accident analysis. This paper presents the development of an Event Data Recorder (EDR) system specifically designed for autonomous vehicles, utilizing Internet of Things (IoT) technology. The system integrates various sensors, including 3-axis gyroscope and a 3-axis accelerometer, flame sensors, smoke sensors and collision switches with a microcontroller equipped with Bluetooth and Wi-Fi capabilities. The microcontroller manages data collection, processing and communication, capturing essential information such as vehicle movement, orientation, fire risks, smoke detection and collision impacts. The system's decision-making algorithm triggers alerts based on sensor thresholds and collision detection. In the event of an accident, the system utilizes a GPS module to transmit precise location data (latitude and longitude) to emergency contacts and medical facilities via the Blynk application. The Blynk application also provides remote access to accident and sensor data for further analysis. Initial testing of the prototype demonstrated its ability to accurately detect and respond to simulated accident conditions, indicating its potential for real-world application. By enabling timely medical intervention and detailed accident analysis, it plays a crucial role in advancing vehicle safety.