AD-H: Language-guided Autonomous Driving with Hierarchical Agents 事件

AD-H: Language-guided Autonomous Driving with Hierarchical Agents arXiv:2406.03474v2 Announce Type: replace Abstract: Language-guided autonomous driving requires bridging a large abstraction gap between high-level natural-language instructions and low-level vehicle control. End-to-end approaches that use a single multimodal large language model (MLLM) to map language directly to actions struggle with this mismatch, often failing to exploit the reasoning capabilities of the model and exhibiting