Design and Implementation of Cascaded Ant Colony Optimization Coupled with Sliding Mode Controller for Autonomous Cruise Control System

Driving assist systems are being widely used in modern cars nowadays for safety, efficiency and comfort. These systems are used in cruise control, self-driving control and even obstacle avoidance. All these systems include a lot of sensors and radars, which work together and generate fast responses to manipulate the direction or speed of a car. The main objective of using this sort of technology is to reduce accidents by reducing stress on the driver by increasing comfort of travel. The aim of this research is to develop a controller for cruise control in vehicles that can help to reach the desired speed most accurately, quite fast and efficiently. The proposed Ant Colony Optimization coupled with Sliding Mode Controller (ACO & SMC) used in this research is more accurate and robust that can help to tune the parameters in a way that the cruise control system gives a minimum error, stable results with the least possible disturbances. Later on, the results are also compared with already used state-of-the-art technologies implemented for cruise control to show the superiority of the proposed controller.