| --- |
| license: mit |
| task_categories: |
| - robotics |
| tags: |
| - autonomous-driving |
| - carla |
| --- |
| |
| # MVAdapt Dataset |
|
|
| This repository contains the dataset for the paper [MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving](https://huggingface.co/papers/2604.11854). |
|
|
| MVAdapt is a physics-conditioned adaptation framework for multi-vehicle end-to-end (E2E) autonomous driving. The dataset includes driving data for 27 different vehicles in the CARLA simulator, covering a wide range of physical properties such as size, mass, and drivetrain characteristics. |
|
|
| [GitHub Repository](https://github.com/hae-sung-oh/MVAdapt) |
|
|
| ## Dataset Description |
|
|
| The dataset provides annotations and sensor data used to train and evaluate the MVAdapt model. It includes the following fields: |
|
|
| - `vehicle_id`: Vehicle model ids |
| - `gt_waypoint`: Ground truth waypoint for vehicle model |
| - `bs_waypoint`: Predicted waypoint from baseline model for default vehicle model |
| - `gt_control`: Ground truth control for vehicle model |
| - `bs_control`: Predicted control from baseline model for default vehicle model |
| - `scene_features`: Features that extracted by backbone model (TransFuser) |
| - `physics_params`: Physical properties for vehicle model |
| - `gear_params`: Gear properties for vehicle model |
| - `rgb`: RGB image |
| - `lidar_bev`: LiDAR BEV image |
| - `target_point`: Target heading point |
| - `ego_vel`: Speed for ego vehicle |
| - `command`: Command for ego vehicle |
|
|
| ## Citation |
|
|
| If you find this work or dataset useful, please consider citing: |
|
|
| ```bibtex |
| @misc{oh2026mvadaptzeroshotmultivehicleadaptation, |
| title={MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving}, |
| author={Haesung Oh and Jaeheung Park}, |
| year={2026}, |
| eprint={2604.11854}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.RO}, |
| url={https://arxiv.org/abs/2604.11854}, |
| } |
| ``` |
