Lane detection is a crucial component in Advanced Driver Assistance Systems (ADAS) for ensuring vehicle safety and autonomous driving functionality. This project focuses on implementing the Hough transform algorithm for lane detection in a simulated environment using the Qualcomm Connected Automotive Reference (QCAR) platform. The Hough transform method allows for the identification of lane lines in images by detecting straight lines through a voting process in parameter space. Through this project, the effectiveness of the Hough transform in accurately detecting lane lines in various road conditions is evaluated. Experimental results demonstrate the algorithm’s performance in real-time lane detection scenarios, highlighting its potential for integration into ADAS systems for enhanced road safety and autonomous driving capabilities.