Dataset card
Browse files
README.md
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---
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license: cc-by-4.0
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pretty_name: DrivingBench Simulator
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tags:
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- gaussian-splatting
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- autonomous-driving
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- simulation
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---
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# DrivingBench Simulator
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The Gaussian splats behind the [DrivingBench](https://drivingbench.com) simulator, a drivable twin of
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the v1.1 cone course. They were trained on the Tesla Model 3's own road camera on 27 October 2026,
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from frames taken between 15:30 and 17:00. The simulator itself (the course, its cones, the
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drivable region and the car fitted to the Tesla's logs) is in the
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[DrivingBench harness](https://github.com/aditya-ramabadran/drivingbench_harness_code), under `sim/`.
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| File | Gaussians | Size | Used by | SHA-256 |
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| --- | --- | --- | --- | --- |
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| `oct27-nocones-full.splat` | 2,924,873 | 93.6 MB | the simulated road camera | `c306e7ae33aaa002c138b070ab31710a68827e8a20f0db1610e933a352a17c9c` |
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| `oct27-nocones.splat` | 1,500,000, the most opaque | 48 MB | the lot explorer in a browser | `672709eddd03b05dc93e1f127b21887e31fdd6c5aa2b931ddc16a4ac34d6fa17` |
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Both are `.splat` files (32 bytes per Gaussian: position, scale, colour and opacity, rotation), in
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the course frame in metres. The real cones and the haze along the car's path are removed; the
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simulator places the course's cones back as objects.
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## Use
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From a checkout of the harness at `v1.1`:
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```sh
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uvx --from huggingface_hub hf download drivingbench/simulator --repo-type dataset \
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--include "*.splat" --local-dir runs/sim/explorer
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uv run python -m drivingbench.sim.runtime # the simulator, on 127.0.0.1:8877
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uv run python -m drivingbench.sim.explorer.serve # the lot explorer, on 127.0.0.1:8890
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```
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The harness's `docs/sim.md` describes how the splats were built and how faithful the simulator is.
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## License
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CC BY 4.0. If you use the splats, please link [drivingbench.com](https://drivingbench.com).
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