Enhancing Road Safety: Reckless Driver Detection via OpenCV in Simulated Environments

A major traffic violation known as “reckless driving” is defined as driving with a deliberate disrespect for other people’s safety. Since there are too many unknowns in the scenario, reckless driving cannot be stopped. It is the driver’s obligation to drive safely; it is not under their control. Therefore, in order to address the issues around careless driving, we developed a method for determining whether or not a vehicle is being driven carelessly. Prior studies on the subject used the vehicle’s current speed and the presence of dents to identify the driver as careless. They neglect to take the vehicle’s trajectory into account. A car that is driving while intoxicated or that frequently changes lanes does not travel in a straight line. This trajectory can be examined to determine whether a car is being driven carelessly. With a CNN model, the vehicle’s trajectory may be examined. Without any pre-processing, analyzing the vehicle’s path would make the CNN model complex and time-consuming to train. In order to address this problem, we create a graph of the car’s trajectory and use it as input data to train a CNN model that determines whether or not the vehicle is being driven recklessly.