DriveLM is an ECCV 2024 Oral paper that uses LLMs for autonomous driving by framing driving as graph visual question answering. It employs structured reasoning approaches including chain-of-thought, graph-of-thoughts, and tree-of-thoughts to enable visual understanding and decision-making for self-driving systems. The project provides datasets and evaluation benchmarks for the Autonomous Driving Challenge 2024.