This repository is dedicated to the collection of research papers on LLM for Autonomous Driving. We aim to continuously update it with the latest and most cutting-edge research in the field. This repository is maintained by the Intelligent Vehicle Institute of SJTU.
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- A Survey for Foundation Models in Autonomous Driving. 2024.02
- World Models for Autonomous Driving: An Initial Survey. 2024.05
- A Survey of Large Lanuguage Models for Autonomous Driving. 2023.11
- A Survey on Multimodal Large Language Models for Autonomous Driving. [WACV 2024]
- Vision Language Models in Autonomous Driving and Intelligent Transportation Systems.2023.10
- Towards Knowledge-driven Autonomous Driving. 2023.12
- Language-Image Models with 3D Understanding. 2024.05
- LLM-Seg: Bridging Image Segmentation and Large Language Model Reasoning. 2024.04
- OpenAnnotate2: Multi-modal Auto-annotating for Autonomous Driving. [IEEE TIV]
- AccidentBlip2: Accident Detection With Multi-View MotionBlip2. 2024.04
- AIDE: An Automatic Data Engine for Object Detection in Autonomous Driving. 2024.03
- HiLM-D: Towards High-Resolution Understanding in Multimodal Large Language Models for Autonomous Driving. 2023.09
- Language Prompt for Autonomous Driving. 2023.09
- GeoDiffusion: Text-Prompted Geometric Control for Object Detection Data Generation. [ICLR 2024]
- SPOT: Scalable 3D Pre-training via Occupancy Prediction for Autonomous Driving.
- RAG-based Explainable Prediction of Road Users Behaviors for Automated Driving using Knowledge Graphs and Large Language Models. 2024.05
- Traj-LLM: A New Exploration for Empowering Trajectory Prediction with Pre-trained Large Language Models. 2024.05
- LC-LLM: Explainable Lane-Change Intention and Trajectory Predictions with Large Language Models. 2024.03
- Large Language Models Powered Context-aware Motion Prediction. 2024.03
- GPT-4 Enhanced Multimodal Grounding for Autonomous Driving: Leveraging Cross-Modal Attention with Large Language Models. 2023.12
- LeGo-Drive: Language-enhanced Goal-oriented Closed-Loop End-to-End Autonomous Driving. 2024.03
- GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior Prediction. 2024.01
- Can you text what is happening? Integrating pre-trained language encoders into trajectory prediction models for autonomous driving. 2023.09
- MTD-GPT: A Multi-Task Decision-Making GPT Model for Autonomous Driving at Unsignalized Intersections. 2023.07
- DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experiences. [VLADR 2024]
- Enhancing Q-Learning with Large Language Model Heuristics. 2024.05
- Large Language Models as Decision Makers for Autonomous Driving
- AGENTSCODRIVER: Large Language Model Empowered Collaborative Driving with Lifelong Learning. 2024.04
- Multi-Modal GPT-4 Aided Action Planning and Reasoning for Self-driving Vehicles. [ICASSP 2024]
- Drive Like a Human: Rethinking Autonomous Driving with Large Language Models.2023.07
- DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models. [ICLR 2024]
- Large Language Models for Autonomous Driving:Real-World Experiments.
- LanguageMPC: Large Language Models as Decision Makers for Autonomous Driving. 2023.10
- MTD-GPT: A Multi-Task Decision-Making GPT Model for Autonomous Driving at Unsignalized Intersections. 2023.07
- OmniDrive: A Holistic LLM-Agent Framework for Autonomous Driving with 3D Perception,Reasoning and Planning. 2024.05
- NL2Plan: Robust LLM-Driven Planning from Minimal Text Descriptions. 2024.05
- AGENTSCODRIVER: Large Language Model Empowered Collaborative Driving with Lifelong Learning. 2024.04
- Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs. 2024.04
- DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models. 2024.02
- DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving. 2023.12
- Driving Everywhere with Large Language Model Policy Adaptation. 2024.04
- Feedback-Guided Autonomous Driving. [CVPR 2024]
- LangProp: A code optimization framework using Large Language Models applied to driving. 2024.05
- LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning. 2023.12
- DriveLM: Driving with Graph Visual Question Answering. [CVPR 2024 Autonomous Driving Challenge]
- LMDrive: Closed-Loop End-to-End Driving with Large Language Models. [CVPR 2024]
- Empowering Autonomous Driving with Large Language Models: A Safety Perspective. 2023.12
- ADriver-I: A General World Model for Autonomous Driving. 2023.11
- A Language Agent for Autonomous Driving. 2023.11
- ChatGPT as Your Vehicle Co-Pilot: An Initial Attempt. 2023.10
- Receive, Reason, and React: Drive as You Say with Large Language Models in Autonomous Vehicles. 2023.10
- DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model. 2023.10
- GPT-DRIVER: LEARNING TO DRIVE WITH GPT. 2023.10
Awesome-LLM-for-Autonomous-Driving is released under the Apache 2.0 license.