Artificial intelligence based automatic decelerating vehicle control system to avoid misfortunes

Abstract

The source of the occurrence of accidents in four wheelers happens due to the failure of decelerating systems. Accidents occur if brake is not applied instantly when there exists an obstacle. Negligence of driver, malfunction in the linkages of decelerating systems, twist and turns of road, unmanageable speed at that instant and fatigue of driver are the reasons of accidents. In today’s world, where traffic is heavy, it is mandatory to control brakes through electronics devices automatically in order to minimize the accidents near accident prone zones. This paper proposes an effective technology to control the decelerating system automatically by proactively sensing the accident-prone zones and preventing the occurrence of accidents. This technology uses Arduino, L293d motor driver and ultrasonic sensor, Machine Learning techniques, RFID and RFID protocols for effective control of decelerating system. This system needs to be embodied in to the dashboard of a vehicle, supported by secured RFID and machine learning techniques for effectively controlling the decelerating system. In order to minimize the occurrence of accidents, the driving pattern of the driver under various conditions are studied with the help of Car Trips data log and acelerolinear_terra dataset. The trained data are used in the development of a mobile app which when fitted into the windshield of the car helps the driver in controlling the decelerating system thus by avoiding accidents and rash driving.