| --- |
| 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. |
|
|
