To become a scientist in AI for autonomous vehicles, build expertise in areas like computer vision, sensor fusion, and reinforcement learning. Start by learning programming languages such as Python and mastering AI frameworks like TensorFlow and PyTorch.
Gain knowledge in robotics, perception systems, and control algorithms by studying topics like path planning, object detection, and SLAM. Projects involving autonomous robotics, simulations, or real-world datasets (e.g., KITTI) are excellent ways to develop practical skills.
Pursue advanced education (e.g., a master’s or PhD in AI or robotics) and contribute to research in self-driving technology. Collaborate with industry or academia to solve real-world problems, and stay updated with advancements by attending conferences like CVPR or ICCV.