死磕技术的自动驾驶黄埔军校，4000人了！

Core Viewpoint - The article emphasizes the establishment of a comprehensive community focused on autonomous driving, aiming to bridge the gap between academia and industry while providing valuable resources for learning and career opportunities in the field [2][16]. Group 1: Community and Resources - The community has created a closed-loop system covering various fields such as industry, academia, job seeking, and Q&A exchanges, enhancing the learning experience for participants [2][3]. - The platform offers cutting-edge academic content, industry roundtables, open-source code solutions, and timely job information, significantly reducing the time needed for research [3][16]. - Members can access nearly 40 technical routes, including industry applications, VLA benchmarks, and entry-level learning paths, catering to both beginners and advanced researchers [3][16]. Group 2: Learning and Development - The community provides a well-structured learning path for beginners, including foundational knowledge in mathematics, computer vision, deep learning, and programming [10][12]. - For those already engaged in research, valuable industry frameworks and project proposals are available to further their understanding and application of autonomous driving technologies [12][14]. - Continuous job sharing and career opportunities are promoted within the community, fostering a complete ecosystem for autonomous driving [14][16]. Group 3: Technical Focus Areas - The community has compiled extensive resources on various technical aspects of autonomous driving, including perception, simulation, planning, and control [16][17]. - Specific learning routes are available for topics such as end-to-end learning, 3DGS principles, and multi-modal large models, ensuring comprehensive coverage of the field [16][17]. - The platform also features a collection of open-source projects and datasets relevant to autonomous driving, facilitating hands-on experience and practical application [32][34].