Lane Detection and Steering Control of Autonomous Vehicle

In recent times autonomous vehicle industry is evolving and is supposed to arrive at a worldwide income of 175 billion bucks toward the close of 2025. Autonomous vehicle utilizes different fusion of sensors to independently drive the vehicle. The present-day vehicles are equipped with add-ons that supports the driver to place the vehicle in the specific path. This call for a reasonable detection of lane procedure strong enough to errors and outputs a defined result. A number of algorithms have been proposed by researchers for lane identification in order to coordinate the driverless-vehicle not to move away from it. Computer vision based algorithms and models based on deep learning trained with huge interpreted datasets to accurately forecast the line of lanes. The proposed algorithm describes the method of lane identification employing sliding window based search and identify the position of the vehicle from the lane using incremental encoder feedback. The results are verified by performing navigation.