最近收到了很多同学关于自驾方向选择的咨询......

Core Insights - The article discusses various advanced directions in autonomous driving research, emphasizing the importance of deep learning and traditional methods for different academic backgrounds [2][3]. Group 1: Research Directions - Key areas of focus include VLA, end-to-end learning, reinforcement learning, 3DGS, and world models, which are recommended for students in computer science and automation [2]. - For mechanical and vehicle engineering students, traditional methods like PnC and 3DGS are suggested due to their lower computational requirements and ease of entry [2]. Group 2: Paper Guidance Services - The article announces the launch of a paper guidance service that covers various topics such as end-to-end learning, multi-sensor fusion, and trajectory prediction [3][6]. - The service includes support for topic selection, full process guidance, and experimental assistance [6]. Group 3: Publication Success - The guidance service has a high acceptance rate for papers submitted to top conferences and journals, including CVPR, AAAI, and ICLR [7]. - The article highlights the range of publication venues, including CCF-A, CCF-B, and various SCI categories [10].