[NeurIPS 2024 Datasets and Benchmarks Track] Closed-Loop E2E-AD Benchmark Enhanced by World Model RL Expert

LLM based data scientist, AI native data application. AI-driven infinite thinking redefines BI.

[CVPR 2024] LMDrive: Closed-Loop End-to-End Driving with Large Language Models

Transformer: PyTorch Implementation of "Attention Is All You Need"

[CVPR 2023] Pytorch implementation of ThinkTwice, a SOTA Decoder for End-to-end Autonomous Driving under BEV.

[NeurIPS 2022] Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline.

[CVPR 2023 Best Paper Award] Planning-oriented Autonomous Driving

PyTorch code for the paper "Model-Based Imitation Learning for Urban Driving".

[ICCV 2023 Oral] A New Paradigm for End-to-end Autonomous Driving to Alleviate Causal Confusion

[IROS 2024] PP-TIL: Personalized Planning for Autonomous Driving with Instance-based Transfer Imitation Learning

Official repo for consistency models.

[RSS 2023] Diffusion Policy Visuomotor Policy Learning via Action Diffusion

BEVFormer, UniAD, VAD in Closed-Loop CARLA Evaluation with World Model RL Expert Think2Drive

[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving

[ICCV 2023] VAD: Vectorized Scene Representation for Efficient Autonomous Driving

Optimization-based real-time path planning for vehicles.

TidyBot: Personalized Robot Assistance with Large Language Models

All kind of experts that can collect data for e2e learning in CARLA; 根据现有的开源代码，收集的相关experts

C++-accelerated Frenet Trajectory Planning Handler

[IROS 2023] FISS+: Efficient and Focused Trajectory Generation and Refinement using Fast Iterative Search and Sampling Strategy

[RA-L 2022] FISS: A Trajectory Planning Framework using Fast Iterative Search and Sampling Strategy for Autonomous Driving

LimSim & LimSim++: Integrated traffic and autonomous driving simulators with (M)LLM support

MotionPlanner

ICRA2024 Paper List

[ICCV & CVPR Workshop] Learning-enabled Interactive Prediction and Planning Framework for Autonomous Vehicles

PyTorch code for the EvoMAL algorithm presented in "Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning" (TPAMI-2023). Paper Link: https://arxiv.org/abs/2209.08907