- This repo contains the training, open-loop evaluation, and closed-loop evaluation code for BEVFormer, UniAD , VAD in Bench2Drive.
- We merge multiple dependencies of UniAD and VAD including mmcv, mmseg, mmdet, and mmdet3d (v0.17.1) into a single library. As a result, it could support latest pytorch and advanced frameworks like deepspeed for acceleration.
- Use "git checkout tcp/admlp" to obtain their corresponding training and evaluation code.
- Installation
- Prepare Dataset
- Train and Open-Loop Eval
- Closed-Loop Eval in CARLA
- Convert Codes from Nuscenes to Bench2Drive
Method | L2 (m) 2s | Driving Score | Success Rate(%) | Config | Download |
---|---|---|---|---|---|
UniAD-Tiny | 0.80 | 32.00 | 9.54 | config | Hugging Face/Baidu Cloud |
UniAD-Base | 0.73 | 37.72 | 9.54 | config | Hugging Face/Baidu Cloud |
VAD | 0.91 | 39.42 | 10.00 | config | Hugging Face/Baidu Cloud |
Method | mAP | NDS | Config | Download |
---|---|---|---|---|
BEVFormer-Tiny | 0.37 | 0.43 | config | Hugging Face/Baidu Cloud |
BEVFormer-Base | 0.63 | 0.67 | config | Hugging Face/Baidu Cloud |