下周开课！我们设计了一份自动驾驶世界模型学习路线图....

Core Viewpoint - The article discusses the distinction between world models and end-to-end models in autonomous driving, emphasizing that world models are a means to achieve end-to-end autonomous driving rather than a specific technology [2]. Summary by Sections Chapter 1: Introduction to World Models - This chapter provides an overview of the relationship between world models and end-to-end autonomous driving, covering the development history and current applications of world models. It introduces various types of world models, including pure simulation, simulation plus planning, and those generating sensor inputs and perception results, along with their industry applications and relevant datasets [5]. Chapter 2: Background Knowledge of World Models - The second chapter focuses on the foundational knowledge necessary for understanding world models, starting with scene representation and expanding to technologies like Transformer and BEV perception. It highlights key technical terms frequently encountered in job interviews related to world models [6][11]. Chapter 3: Discussion on General World Models - This chapter centers on general world models and recent popular works in autonomous driving, including models from Li Fei-Fei's team (Marble), DeepMind (Genie 3), and Meta (JEPA). It also discusses the widely talked-about VLA+ world model algorithms and Tesla's latest world model simulator shared at ICCV [7]. Chapter 4: Video Generation-Based World Models - The fourth chapter focuses on video generation algorithms, which are currently the most researched in both academia and industry. It covers classic works like GAIA-1 & GAIA-2 from Wayve and recent advancements such as UniScene and OpenDWM, providing a comprehensive view of the field's progress [8]. Chapter 5: OCC-Based World Models - This chapter discusses OCC generation algorithms, explaining three major papers and a practical project. These methods can be easily extended for vehicle trajectory planning, contributing to end-to-end solutions [9]. Chapter 6: World Model Job Topics - The final chapter shares practical insights from the instructor's years of experience, addressing the application of world models in the industry, existing pain points, and how to prepare for related job interviews, focusing on what companies prioritize [10]. Course Outcomes - The course aims to advance understanding of end-to-end autonomous driving, equipping participants with knowledge of world model technologies, including video generation and OCC generation methods, and preparing them for roles in the autonomous driving industry [10][13].