---
license: mit
task_categories:
  - robotics
  - image-to-text
tags:
  - autonomous-driving
  - carla
  - simlingo
  - behavioral-cloning
size_categories:
  - 100K<n<1M
---

# SimLingo CARLA Dataset (Raw, 4Hz)

Raw driving data from CARLA simulator. No transformations or derived fields - all original measurements preserved as-is.

## Dataset Summary

- **Source**: [SimLingo](https://huggingface.co/datasets/RenzKa/simlingo) (CVPR 2025)
- **Scale**: 228,757 frames (23 shards)
- **Frame Rate**: 4 FPS
- **Resolution**: 1024x512 RGB
- **Routes**: Complete driving episodes (routes never split across shards)

## Column Schema

### Core Fields
| Column | Type | Description |
|--------|------|-------------|
| `route_id` | string | Route identifier |
| `frame_idx` | int32 | Frame index within route |
| `image` | bytes | Original JPEG image bytes |

### Control Signals (Raw)
| Column | Type | Description |
|--------|------|-------------|
| `steer` | float32 | Steering [-1, 1] |
| `throttle` | float32 | Throttle [0, 1] |
| `brake` | bool | Brake applied |

### Vehicle State
| Column | Type | Description |
|--------|------|-------------|
| `speed` | float32 | Current speed (m/s) |
| `target_speed` | float32 | Target speed |
| `speed_limit` | float32 | Speed limit |
| `theta` | float32 | Heading angle |
| `angle` | float32 | Angle to target |

### Navigation
| Column | Type | Description |
|--------|------|-------------|
| `command` | int32 | Navigation command |
| `next_command` | int32 | Next navigation command |
| `pos_global` | string (JSON) | Global position [x, y] |
| `target_point` | string (JSON) | Target point |
| `target_point_next` | string (JSON) | Next target point |
| `aim_wp` | string (JSON) | Aim waypoint |
| `route` | string (JSON) | Planned route waypoints |
| `route_original` | string (JSON) | Original route waypoints |
| `changed_route` | bool | Route was changed |

### Hazards & Environment
| Column | Type | Description |
|--------|------|-------------|
| `junction` | bool | In junction |
| `vehicle_hazard` | bool | Vehicle hazard detected |
| `vehicle_affecting_id` | int32 | ID of affecting vehicle |
| `walker_hazard` | bool | Pedestrian hazard |
| `walker_affecting_id` | int32 | ID of affecting pedestrian |
| `light_hazard` | bool | Traffic light hazard |
| `stop_sign_hazard` | bool | Stop sign hazard |
| `stop_sign_close` | bool | Stop sign nearby |
| `walker_close` | bool | Pedestrian nearby |
| `walker_close_id` | int32 | ID of nearby pedestrian |
| `speed_reduced_by_obj_type` | string | Object type causing speed reduction |
| `speed_reduced_by_obj_id` | int32 | Object ID causing speed reduction |
| `speed_reduced_by_obj_distance` | float32 | Distance to speed-reducing object |
| `control_brake` | bool | Control brake applied |

### Augmentation (from SimLingo)
| Column | Type | Description |
|--------|------|-------------|
| `augmentation_translation` | float32 | Translation augmentation |
| `augmentation_rotation` | float32 | Rotation augmentation |

### Transforms
| Column | Type | Description |
|--------|------|-------------|
| `ego_matrix` | string (JSON) | 4x4 ego vehicle transform matrix |
| `boxes` | string (JSON) | 3D bounding boxes for all objects |

### Commentary (Optional)
| Column | Type | Description |
|--------|------|-------------|
| `commentary` | string | Natural language commentary |
| `commentary_data` | string (JSON) | Full commentary object with metadata |

## Usage

```python
from datasets import load_dataset
import json

ds = load_dataset("TESS-Computer/carla-simlingo-raw", split="train")

sample = ds[0]
print(sample['route_id'])
print(sample['steer'], sample['throttle'], sample['brake'])
print(sample['speed'])

# Parse JSON fields
pos = json.loads(sample['pos_global'])
boxes = json.loads(sample['boxes']) if sample['boxes'] else []
```

## Data Collection

- **Simulator**: CARLA 0.9.15 (Leaderboard 2.0)
- **Expert**: PDM-Lite (rule-based, 100% route completion)
- **Scenarios**: Single-scenario routes with random weather
- **Towns**: Towns 1-13

## Citation

```bibtex
@inproceedings{renz2025simlingo,
  title={SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment},
  author={Renz, Katrin and Chen, Long and Arani, Elahe and Sinavski, Oleg},
  booktitle={CVPR},
  year={2025},
}
```

## License

MIT (dataset processing code). Original data subject to [SimLingo](https://huggingface.co/datasets/RenzKa/simlingo) and [CARLA](https://carla.org/) licenses.