ANN Enabled Obstacle Avoiding Automated Car

Abstract

Automated vehicle is one which is equipped for visualizing the current circumstances and taking the decisions by itself on the movement and control with the assistance of the human. Human driver is not needed always and takes the responsibility in all decision making of driving since it is self-driven. It mimics the actions of the driver by the predefined sets of rules and self-learning on the decisions to be taken dynamically. It will depend on sensors, actuators, calculations, complex decision and Artificial Intelligent frameworks. Specialized processors are available on the design and programming aspects now. Radar sensors are useful in screening the situations nearby to the vehicles. Camcorders will identify traffic signals, digitize street signs, monitor different vehicles and keep the people updated without their request. Light Identification and Ranging (LIDAR) sensors skip beats of light off the environmental factors of the vehicles to gauge distances, recognize markings of the path and distinguish street edges. Ultrasonic sensors in the wheels of the vehicle distinguish controls and different vehicles on the fly of the vehicle. This research deals the automation of the car by finding the path and avoiding the obstacles automatically in 360 degrees.