Road Accident Avoiding System (RAAS)

Abstract

Our traffic and tendency for aggressive and dangerous driving are among the many things that the subcontinent is notorious for. Every year, this results in an increasing number of horrifying automobile accidents that could have been avoided. A lot of the elements that allow this to happen are related to the driver's situation, i.e., the state in which they are driving. The system in place will estimate the risk of an accident at any point during travel using facial recognition, body language analysis, and traffic density. A camera over the dash will give a live feed to the system, which will compare facial expressions and check for indicators of exhaustion and intoxication using Machine Learning Algorithms. It will also use a driver's body language to see whether they are distracted by any electronics or other variables, and warn them about the dangers via a linked app. The driver will be given guidance on how to proceed, and if the motorist follows the advice, the odds of prevention are considerably improved. In the event of unforeseen incidents, the system also serves as a black box, storing data for use in legal procedures (if necessary).