世界模型自动驾驶小班课！特斯拉世界模型、视频&OCC生成速通

Core Viewpoint - The article introduces a new course titled "World Models and Autonomous Driving Small Class," focusing on advanced algorithms in the field of autonomous driving, including general world models, video generation, and OCC generation [1][3]. Course Overview - The course is developed in collaboration with industry leaders and follows the success of a previous course on end-to-end and VLA autonomous driving [1]. - The course aims to enhance understanding and practical skills in world models, which are crucial for the advancement of autonomous driving technology [11]. Course Structure Chapter 1: Introduction to World Models - This chapter covers the relationship between world models and end-to-end autonomous driving, the history of world models, and current application cases [6]. - It discusses various types of world models, including pure simulation, simulation plus planning, and generating sensor inputs and perception results [6]. Chapter 2: Background Knowledge of World Models - The second chapter focuses on foundational knowledge related to world models, including scene representation, Transformer technology, and BEV perception [6][12]. - It highlights key technical terms frequently encountered in job interviews related to world models [7]. Chapter 3: Discussion on General World Models - This chapter addresses popular general world models and recent trends in autonomous driving jobs, including models from Li Feifei's team and DeepMind [7]. - It provides insights into the core technologies and design philosophies behind these models [7]. Chapter 4: Video Generation-Based World Models - The fourth chapter focuses on video generation algorithms, showcasing significant works such as GAIA-1 & GAIA-2 and recent advancements from various institutions [8]. - It includes practical applications using open-source projects like OpenDWM [8]. Chapter 5: OCC-Based World Models - This chapter explores OCC generation algorithms, discussing three major papers and a practical project that extends to vehicle trajectory planning [9]. Chapter 6: World Model Job Topics - The final chapter shares practical experiences from the instructor's career, addressing industry applications, pain points, and interview preparation for related positions [10]. Target Audience and Learning Outcomes - The course is designed for individuals aiming to deepen their understanding of end-to-end autonomous driving and world models [11]. - Upon completion, participants are expected to achieve a level equivalent to one year of experience as a world model autonomous driving algorithm engineer, mastering key technologies and being able to apply learned concepts in projects [14].