Core Viewpoint - The article discusses the evolution of autonomous driving technology, highlighting the transition from rule-based systems to end-to-end models represented by companies like Ideal and XPeng, and currently to the world model phase represented by NIO, emphasizing the continuous presence of deep learning throughout these changes [1]. Group 1: Course Introduction - The course covers the development from modular production algorithms to end-to-end systems and now to VLA, focusing on core algorithms such as BEV perception, visual language models (VLM), diffusion models, reinforcement learning, and world models [5]. - Participants will gain a comprehensive understanding of the end-to-end technology framework and key technologies, enabling them to reproduce mainstream algorithm frameworks like diffusion models and VLA [5]. - Feedback indicates that students completing the course can achieve approximately one year of experience as end-to-end autonomous driving algorithm engineers, benefiting from the training for internships and job recruitment [5]. Group 2: Instructor Profile - The main instructor, Jason, holds a C9 undergraduate degree and a PhD from a QS top 50 university, with multiple published papers in CCF-A and CCF-B journals [6]. - He is currently an algorithm expert at a leading domestic manufacturer, engaged in the research and production of cutting-edge algorithms, with extensive experience in the development and delivery of autonomous driving perception and end-to-end algorithms [6]. Group 3: Research Guidance - The program aims to enhance practical skills and knowledge in cutting-edge topics, with a focus on helping students publish high-level papers to improve their academic prospects [8]. - The community includes over 300 instructors specializing in autonomous driving and embodied intelligence, with a high manuscript acceptance rate of 96% over the past three years [8]. Group 4: Research Process - The guidance process includes selecting research topics based on student interests, explaining key concepts, and providing essential foundational knowledge and recommended learning materials [11]. - Students will learn how to critically read literature, conduct research, and write various sections of a paper, including methods and experimental results, with continuous feedback and support throughout the process [11].
端到端和VLA,这些方向还适合搞研究
自动驾驶之心·2025-11-03 00:04