# Which control inputs (ego trajectory, steering/speed, agent boxes, map, weather text, camera layout, robot actions, camera pose) do the driving and robot world models accept, and how is each encoded?

- id: art_01M5MC9RMDKATFNV6MMGH8F7YS
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T06, T15, T19 · tags: none
- updated: 2026-10-23T12:38:15.945Z
- url: https://veyrul.com/articles/art_01M5MC9RMDKATFNV6MMGH8F7YS

The driving systems expose a small set of structured controls: ego motion (speed + curvature in GAIA-1/2; angle/speed, trajectory, command or goal point in Vista; yaw + velocity in DriveDreamer; 64-point trajectory in Cosmos), other agents (3D boxes in GAIA-2 and DriveDreamer; LLM-written trajectories in DriveDreamer-2), scene attributes (categorical metadata, CLIP or T5 text), and the camera rig (intrinsics/extrinsics in GAIA-2; per-view captions and view embeddings in Cosmos). Robot systems use gripper-frame action vectors (Cosmos on Bridge, 7-D) or whole-body low-level trajectories (1XWM). Camera-pose control with Plucker rays exists in Cosmos but was trained on static real-estate-style scenes. Most control interfaces were trained on proprietary data, and several are demonstrated only in figures.

The driving systems expose a small set of structured controls: ego motion (speed + curvature in GAIA-1/2; angle/speed, trajectory, command or goal point in Vista; yaw + velocity in DriveDreamer; 64-point trajectory in Cosmos), other agents (3D boxes in GAIA-2 and DriveDreamer; LLM-written trajectories in DriveDreamer-2), scene attributes (categorical metadata, CLIP or T5 text), and the camera rig (intrinsics/extrinsics in GAIA-2; per-view captions and view embeddings in Cosmos). Robot systems use gripper-frame action vectors (Cosmos on Bridge, 7-D) or whole-body low-level trajectories (1XWM). Camera-pose control with Plucker rays exists in Cosmos but was trained on static real-estate-style scenes. Most control interfaces were trained on proprietary data, and several are demonstrated only in figures.

Curator qualifications: Driving controls: ego motion, other-agent boxes or trajectories, text; structured and low-dimensional.

Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

```json
{
  "citations": [
    {
      "url": "https://arxiv.org/abs/2309.17080v1",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://arxiv.org/abs/2503.20523v1",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://arxiv.org/abs/2405.17398v5",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://arxiv.org/abs/2309.09777v2",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://arxiv.org/abs/2403.06845v2",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://arxiv.org/abs/2501.03575v3",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://arxiv.org/abs/2511.00062v2",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://www.1x.tech/discover/redwood-ai-world-model",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://wayve.ai/thinking/gaia-3/",
      "note": "candidate evidence excerpts"
    },
    {
      "url": "https://wayve.ai/thinking/gaia-4/",
      "note": "candidate evidence excerpts"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] The driving systems expose a small set of structured controls: ego motion (speed + curvature in GAIA-1/2; angle/speed, trajectory, command or goal point in Vista; yaw + velocity in DriveDreamer; 64-point trajectory in Cosmos), other agents (3D boxes in GAIA-2 and DriveDreamer; LLM-written trajectories in DriveDreamer-2), scene attributes (categorical metadata, CLIP or T5 text), and the camera rig (intrinsics/extrinsics in GAIA-2; per-view captions and view embeddings in Cosmos). Robot systems use gripper-frame action vectors (Cosmos on Bridge, 7-D) or whole-body low-level trajectories (1XWM). Camera-pose control with Plucker rays exists in Cosmos but was trained on static real-estate-style scenes. Most control interfaces were trained on proprietary data, and several are demonstrated only in figures. · locator: candidate evidence excerpts · source: https://arxiv.org/abs/2309.17080v1

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources.

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