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name: navsim description: "Use NAVSIM v2 for autonomous-driving agent development, OpenScene data setup, learned-agent training, EPDMS evaluation, traffic-policy experiments, visualization, and leaderboard submission preparation." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

NAVSIM v2 operating guide

Use this skill when a task names NAVSIM, OpenScene, EPDMS/PDM score, pseudo closed-loop driving evaluation, TransFuser/LTF, Trajectory, SensorConfig, NAVSIM split names, or the NAVSIM submission pickle. This is a self-contained operating graph: use its bundled references and safe helpers rather than reopening a NAVSIM checkout.

Route by task

• Install, workspace, maps, logs, sensors, split choice, or loader/data layout: read setup-and-data.
• Create/debug a planner agent, sensor history, trajectory, checkpoint, or TransFuser/LTF configuration: read agents.
• Train a learned agent, build/reuse feature caches, or diagnose Lightning and Hydra training configuration: read training.
• Build metric caches, run one-/two-stage EPDMS, select traffic policies, or diagnose score CSVs: read evaluation.
• Plot camera/BEV/LiDAR data or prepare/validate a warmup/challenge pickle: read visualization-and-submission.

For a request that spans routes, start with setup-and-data, then follow the links from agents into training or evaluation; use visualization-and-submission only for plotting and submission artifacts.

Installation baseline

NAVSIM v2.0.0 documents Python 3.9+, a nuPlan devkit dependency, PyTorch 2.0.1, Hydra, PyTorch Lightning, NumPy, OpenCV, geospatial libraries, and optional visualization/Jupyter packages. Use a fresh environment and the package's versioned requirements rather than mutating an unrelated environment. For a public source installation, use a compatible Python 3.9+ environment and pin this source revision:

python -m pip install "navsim @ git+https://github.com/autonomousvision/navsim.git@0a380a9063d7162ec93d0f51e9990ebac585f720"
python -m pip check

If a user already has a source checkout, editable installation is equivalent: python -m pip install -e . from that checkout. A minimal public import check is:

python -c "import navsim; from navsim.common.dataclasses import SensorConfig, Trajectory; print('NAVSIM import OK')"

GPU is not required for metadata/API inspection, but learned TransFuser training and realistic sensor/evaluation workloads should use a compatible CUDA Torch installation. Never call a CPU import proof of GPU capability.

Workspace contract

Before any data-backed command, define these public variables and validate the selected roots with the bundled workspace validator from the setup-and-data route:

• NUPLAN_MAP_VERSION=nuplan-maps-v1.0
• NUPLAN_MAPS_ROOT: readable nuPlan map database
• NAVSIM_EXP_ROOT: experiment outputs and metric cache
• NAVSIM_DEVKIT_ROOT: the NAVSIM installation/project root used by the user's command context
• OPENSCENE_DATA_ROOT: OpenScene logs, sensor blobs, and two-stage bundles

Do not create empty directories to satisfy the checker. Logs, sensor paths, map data, synthetic scenes, and metric caches are separate resources.

Cross-cutting guardrails

• Keep agent trajectories in local rear-axle BEV (x, y, heading) form with a matching TrajectorySampling; the default model output is 4 seconds at 0.5-second intervals, while proposal evaluation commonly samples 4 seconds at 0.1 seconds.
• Keep the metric-cache split, scene-filter split, synthetic roots, proposal sampling, and traffic policy aligned. Treat missing/unused token warnings or invalid pseudo-closed-loop aggregation as failed evaluation evidence.
• Do not train challenge/test splits. navtrain/trainval/mini are training candidates; test, navtest, navhard_two_stage, warmup_two_stage, and private challenge splits are evaluation/submission surfaces.
• Submission agents receive AgentInput, not an annotated Scene; a requires_scene=True privileged agent cannot generate a valid server pickle.
• Dataset downloads, large cache creation, training, benchmark scoring, private-data access, uploads, and notebook rendering are explicit operations, not default smoke checks.

For a package/API/backend smoke, run the shared runtime inspector with --help, --json, or the explicitly requested --cuda probe. Read troubleshooting.md for cross-cutting install/import, environment-variable, split/cache, backend, Hydra, and output failures. Read repo-provenance.md before refreshing this graph against a newer NAVSIM source version.