Worked on radar detection enhancements for the driverless car initiative in the OpenHUTB/nn repository, focusing on implementing core improvements to radar functionality and enabling accurate distance measurement. Leveraged Python programming, computer vision, and machine learning techniques to improve the reliability of radar data feeding into autonomous vehicle decision-making systems, thereby reducing detection uncertainty. The work included preparing the codebase for future sensor fusion integration and validation testing, with all changes carefully documented for traceability. Demonstrated effective use of version control and cross-functional collaboration, ensuring that the enhancements aligned with the broader sensor fusion stack and project requirements.