刚做了一份VLA学习路线图，面向初学者......

Core Insights - The focus of academia and industry has shifted towards VLA (Visual Language Action), which provides human-like reasoning capabilities for more reliable and safer autonomous driving [1][4] - Traditional areas like BEV perception and lane detection have matured, leading to decreased attention from both academia and industry [4] - Major autonomous driving companies are actively developing their own VLA solutions, indicating a competitive landscape [4] Summary by Sections Introduction to Autonomous Driving VLA - VLA is divided into modular VLA, integrated VLA, and reasoning-enhanced VLA, each representing different approaches to autonomous driving [1][4] Course Overview - The course on Autonomous Driving VLA includes detailed explanations of cutting-edge algorithms across the three subfields, supplemented by practical assignments [8] Core Content of Autonomous Driving VLA - Key topics include visual perception, large language models, action modeling, model deployment, and dataset creation, with advanced algorithms like CoT, MoE, RAG, and reinforcement learning [7] Course Structure - The course is structured into six chapters, covering VLA algorithms, foundational algorithms, VLM as an interpreter, modular and integrated VLA, reasoning-enhanced VLA, and a final project [13][21] Chapter Highlights - Chapter 1 provides an overview of VLA algorithms and their development history, along with benchmarks and evaluation metrics [14] - Chapter 2 focuses on foundational knowledge in Vision, Language, and Action, including the deployment of large models [15] - Chapter 3 discusses VLM's role as an interpreter in autonomous driving, covering classic and recent algorithms [16] - Chapter 4 delves into modular and integrated VLA, emphasizing the evolution of language models in planning and control [17] - Chapter 5 explores reasoning-enhanced VLA, introducing new modules for decision-making and action output [18][20] Learning Outcomes - The course aims to deepen understanding of current advancements in autonomous driving VLA and equip participants with the skills to apply VLA in projects [23][25] Course Logistics - The course starts on October 20 and spans approximately two and a half months, featuring offline video lectures and online Q&A sessions [24]