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---
license: apache-2.0
language:
- en
task_categories:
- visual-question-answering
- robotics
tags:
- DriveFusion
- Robotics
- VLA
- VLM
- MultiModal
- AutonomousDriving
---
# DriveFusion-Data
<div align="center">
<img src="drivefusion_logo.png" alt="DriveFusion Logo" width="300"/>
<h1>DriveFusionQA</h1>
<p><strong>An Autonomous Driving Vision-Language Model for Scenario Understanding & Decision Reasoning.</strong></p>
[](https://opensource.org/licenses/Apache-2.0)
[]()
</div>
---
**DriveFusion-Data** is a large-scale multimodal autonomous driving dataset collected in the CARLA simulator using a privileged rule-based expert policy (PDM-Lite). The dataset contains rich sensor data, vehicle measurements, and language annotations for training vision-language-action (VLA) models.
This dataset is part of the **DriveFusion** project.
---
## Dataset Overview
DriveFusion-Data provides a comprehensive multimodal dataset for autonomous driving research, including:
- RGB camera images from **360° multi-camera coverage** (front, front-left, front-right, back-left, back-right)
- LiDAR point clouds
- Semantic segmentation maps
- Depth maps
- Bounding boxes
- Vehicle and simulator measurements
- Natural language annotations (VQA, commentary, instruction following)
The dataset is generated using a CARLA-based data collection framework with multi-town, multi-scenario, and multi-sensor configurations.
---
## Data Collection Framework
The data was collected using the **DriveFusion CARLA Data Collection Framework**, which provides:
- Rule-based expert driving using **PDM-Lite**
- Multi-camera **360° sensor recording** and LiDAR
- Weather and lighting augmentation
- Scenario-based route execution
- Automated batch data generation on clusters (SLURM)
- Format conversion and dataset validation tools
**Collection code repository:**
[https://github.com/DriveFusion/carla-data-collection](https://github.com/DriveFusion/carla-data-collection)
---
## Dataset Sources and Attribution
DriveFusion-Data builds upon several open-source frameworks and datasets:
**Core Simulation:**
- [CARLA Simulator](https://github.com/carla-simulator/carla)
- [CARLA Leaderboard 2.0](https://github.com/carla-simulator/leaderboard)
- [Scenario Runner](https://github.com/carla-simulator/scenario_runner)
**Reference Methods:**
- [DriveLM](https://github.com/OpenDriveLab/DriveLM) (PDM-Lite autopilot and VQA generation)
**Language Dataset Reference:**
- [SimLingo Dataset](https://huggingface.co/datasets/RenzKa/simlingo)
Users must comply with the licenses of all referenced frameworks and datasets.
---
## Dataset Format
Two main formats are provided:
**Pre-DriveFusion Format**
- Raw sensor data and measurements stored in compressed JSON and sensor files.
**DriveFusion Format**
- Standardized multimodal structure for end-to-end VLA training.
- Includes aligned sensor data and language annotations.
---
## Intended Use
This dataset is designed for:
- Vision-Language-Action (VLA) model training
- Autonomous driving research and benchmarking
- Multimodal perception and planning research
- Language grounding in driving environments
- Embodied AI and robotics research
---
## License and Attribution
This dataset is derived from simulation and public frameworks. Users must comply with:
- CARLA license
- CARLA Leaderboard and Scenario Runner licenses (MIT)
- DriveLM license
- SimLingo license
The DriveFusion framework code is released under **Apache 2.0**. Language annotations and third-party components may have additional license restrictions.
---
## Citation
If you use DriveFusion-Data, please cite:
```bibtex
@misc{drivefusiondata2026,
title={DriveFusion-Data: A Large-Scale Multimodal Dataset for Autonomous Driving},
author={Samir, Omar and DriveFusion Team},
year={2026},
url={https://huggingface.co/datasets/DriveFusion/DriveFusion-Data}
}
``` |