| | --- |
| | 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. |
| |
|
