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Nurec_eval

Tasks:
Robotics
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autonomous-driving
nurec
closed-loop-eval
alpasim
alpamayo
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Nurec_eval / README.md
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Add 59 OOD-longtail USDZ scenes with HD-map artifacts injected
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metadata 
license: cc-by-4.0
task_categories:
  - robotics
tags:
  - autonomous-driving
  - nurec
  - closed-loop-eval
  - alpasim
  - alpamayo
size_categories:
  - n<1K

Nurec_eval — NRE Closed-Loop Eval Set with HD Map

59 OOD-longtail scenes for AlpaSim closed-loop evaluation, exported from NVIDIA NRE 26.02 and augmented with HD-map artifacts (lane graph, road boundaries, crosswalks) so models can be evaluated with full map context — not just geometry.

What's inside each pai_<uuid>.usdz

File Purpose
default.usda USDZ entry point
checkpoint.ckpt Neural reconstruction (NRE-26.02 gsplat) weights
parsed_config.yaml NRE training config
data_info.json Sequence metadata
datasource_summary.json Camera/lidar rig info
mesh.ply / mesh.usd Poisson reconstructed scene mesh
ground_mesh.ply Ground mesh (used for offroad / collision_with_ground)
rig_trajectories.json / .usda Recorded ego trajectory (route source)
sequence_tracks.json / .usda Other actors' recorded trajectories
map_data/cf_crosswalks.parquet HD-map: crosswalk polygons
map_data/cf_lane_topology_node.parquet HD-map: lane topology
map_data/cf_road_boundary.parquet HD-map: road boundaries
map_data/dw_lane.parquet HD-map: drivable lanes
map_data/lane_chunk.parquet HD-map: lane geometry
map_data/lane_rail.parquet HD-map: lane center rails

The 6 map_data/*.parquet files were injected via inject_map.py using NRE-internal HD-map data.

Scene composition — 59 scenes from 8 OOD-longtail buckets

Category Scenes
Animals / Birds / Roadkill 7
Complex Intersection Interaction 7
Cyclists & Micromobility Complex 8
Emergency Incident Scene 7
Pedestrian Density / Close Proximity 8
Road Debris / Safety Traces 5
Special / Uncommon Vehicle Behavior 8
Work Zones / Temp Traffic Control 8
⚠️ Broken (route folds back) 1
Total usable 58 × 2 rollouts = 116

Usage with AlpaSim 

# Mount this dataset in the AlpaSim wizard
alpasim_wizard \
  deploy=local topology=1gpu driver=<your_model> \
  +physics=disabled +vehicle=custom \
  scenes.path=/path/to/Nurec_eval \
  scenes.scenes_csv=/path/to/Nurec_eval/sim_scenes.csv \
  scenes.suites_csv=/path/to/Nurec_eval/sim_suites.csv \
  ...

Note: physics=disabled is still required because these are recon-only USDZs (no vehicle-physics config). The HD map is consumed by driver models for lane-aware decision making and by metrics like wrong_lane / offroad-by-lane.

What was missing before

Without map_data/*.parquet, driver models had no map context during closed-loop sim, and lane-aware metrics (wrong_lane) couldn't be computed. This dataset adds them back.

Source