SeerDrive — Bench2Drive / pdm_lite port
End-to-end driving model: SeerDrive (NeurIPS 2025) ported onto CARLA pdm_lite
(carla_garage / Bench2Drive). Geometric-path + speed-bin formulation (BridgeDrive-style).
Pipeline (waypoint -> destination)
TransFuser BEV features [1512,8,8] + 12-dim ego status (incl. navigation target_point)
-> SeerDrive (21M params) predicts a 20-point geometric path (lateral) + a 9-bin target
speed (longitudinal, RL-tuned) -> controller -> throttle/steer/brake -> closed-loop to goal.
- Path branch: 60 k-means shape anchors + offset decoder (imitation-selected)
- Speed branch: 9-bin head; deploy
argmax(speed_logit + lambda*reward)
- World model: predicts future BEV at path completion (self-supervised)
- RL on speed: NC/DAC/EP/TTC/Comfort box-geometry sim-reward heads
Training
30 epochs, per-GPU bs16 x 8 GPUs (eff_bs 128), full pdm_lite (~475k train / 120k val frames),
cosine LR 1e-4, Adam.
Final val metrics (ep30)
| geo_ade | geo_fde | speed_acc | speed_l1 | mIoU | mIoU_fut |
|---|
| 0.058 m | 0.113 m | 0.946 | 0.547 | 0.416 | 0.308 |
IoU: road 0.55 / lane 0.37 / veh 0.28 / ego 0.97.
Files
seerdrive_ep30.pt — final model weights + val metrics (~85 MB)seerdrive_last.pt — full state (model + optimizer + scheduler) for --resume (~254 MB)
