ADAS Based Adaptive Lane Detection Algorithm for Curved and Discontinuous Road Markings Using MATLAB

Over the last few years, autonomous cars have picked up as a means to minimize the prevalence of accidents induced by driver distraction. Intended to increase safety for passengers and optimize traffic conditions, these cars use sophisticated technology for navigation as well as identifying lanes. Existing lane detection has mostly been implemented to detect linear lane markings, but curved as well as non-existent lanes still pose a difficulty. The present research applies MATLAB for detecting lanes in images and videos, including straight, curved, and interrupted lane markings. A camera is installed on the vehicle to obtain real-time road images, which are then processed for the detection of lanes. The Hough Transform method is used to identify lane boundaries by processing through two hyperbolas, making it possible to correctly identify complicated lane patterns. By capitalizing on this method, autonomous cars are able to obtain more accurate lane detection, thus improving overall driving efficiency and safety..