Towards Distance Induced Automatic Braking System for Vehicular Agents using Neural Network and Proportional Integral Derivative Controller

Human fault and recklessness of drivers especially in developing countries are mainly responsible for numerous road traffic accidents recorded in those countries. Many of these road accidents have led to injuries and loss of lives. Technological advancement has led to the development of autonomous braking system to aid drivers in avoiding collision with another car or obstacle. This has been further advanced with the development of driverless vehicles. In this article, Proportional Integral Derivative (PID) and an Artificial Intelligence (AI) based on Neural Network (NN) model for Automatic Braking System (ABS) is proposed. The inputs to the network are the distance from vehicle to an obstruction and the velocity while the force applied on the brake to bring the vehicle to a halt without hitting the obstruction is the output. The simulation results for the two techniques show that the vehicle was able to stop at a good and acceptable distance before the obstacle and at minimal time. It is therefore reasonable to state that the PID and especially NN based ABS are excellent at providing robust and safe braking and can be implemented to good effect.

کلیدواژه ها:

ABS ، Artificial Intelligent ، Automation ، Driverless vehicle ، Neural Network ، PID