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| extra_gated_heading: You must agree to the TruckDrive Dataset License Agreement to access this dataset. | |
| extra_gated_prompt: >- | |
| ### TruckDrive Dataset NONCOMMERCIAL License Agreement | |
| TORC ROBOTICS TRUCKDRIVE DATASET | |
| NON-COMMERCIAL LICENSE | |
| Version 1.0 — Effective May 1, 2026 | |
| Copyright (c) 2026 TORC ROBOTICS, INC. All rights reserved. | |
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| SECTION 1 — DEFINITIONS | |
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| "Commercial Use" has the meaning set forth in Section 2. | |
| "Licensed Material" means the autonomous vehicle sensor data, | |
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| "TruckDrive, provided by Torc Robotics, Inc., available at torc-ai.github.io/TruckDrive, | |
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| SECTION 5 — DATA CONTENT NOTICE | |
| The Licensed Material consists of annotated autonomous vehicle driving | |
| data collected on public roads in the United States, excluding footage | |
| collected in Illinois and California. The Licensed Material includes | |
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| SECTION 8 — TERM AND TERMINATION | |
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| SECTION 9 — COMMERCIAL LICENSING | |
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| chooses. To inquire about a commercial license, contact | |
| licensing@torc.ai. | |
| See LICENSE-COMMERCIAL.txt for further information. | |
| SECTION 10 — OTHER TERMS AND CONDITIONS | |
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| POLICY.txt, constitutes the entire | |
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| conflict with this License. | |
| ### TruckDrive Dataset COMMERCIAL License Agreement | |
| Commercial Licensing | |
| TORC ROBOTICS TRUCKDRIVE DATASET | |
| Is a Commercial License Required? | |
| If Your use of the Dataset constitutes Commercial Use as defined in | |
| LICENSE-NONCOMMERCIAL.txt, You must obtain a commercial license before | |
| accessing or using any data. | |
| See COMMERCIAL-USE-POLICY.txt for a plain-language guide to determining | |
| whether Your use qualifies as commercial. | |
| What a Commercial License Covers | |
| A commercial license grants rights beyond those available under the | |
| Torc Robotics Non-Commercial License v1.0, including: | |
| - Use of the Dataset in connection with commercial products, services, | |
| or internal R&D at autonomous vehicle and related technology companies | |
| - Training, fine-tuning, or evaluating commercial machine learning | |
| models using the Dataset | |
| - Integration of the Dataset or Adapted Material into commercial | |
| software or data pipelines | |
| - Use by contractors and consultants working on behalf of commercial | |
| entities | |
| Commercial license terms are negotiated based on the nature, scope, | |
| and duration of use. | |
| How to Obtain a Commercial License | |
| Email: licensing@torc.ai | |
| Please include the following in your initial inquiry: | |
| 1. Your organization's name and primary business description | |
| 2. A description of your intended use of the Dataset | |
| 3. The anticipated scope and duration of use | |
| 4. Whether you intend to distribute Adapted Material | |
| Existing Non-Commercial Users | |
| If You are currently using the Dataset under the Non-Commercial License | |
| and Your circumstances change such that Your use becomes Commercial Use, | |
| You must cease commercial use immediately and contact the Licensor to | |
| obtain appropriate licensing before continuing. | |
| Contact licensing@torc.ai | |
| Copyright (c) 2026 Torc Robotics, Inc. All rights reserved. | |
| extra_gated_button_content: "I accept the terms of the TruckDrive Dataset License Agreement" | |
| license: other | |
| license_name: truckdrive-dataset | |
| license_link: https://huggingface.co/datasets/Torc-Robotics/TruckDrive/blob/main/LICENSE-NONCOMMERCIAL.txt | |
| viewer: false | |
| <div align="center"> | |
| # TruckDrive: Long-Range Autonomous Highway Driving Dataset | |
| **Torc Robotics · Princeton University · CVPR 2026** | |
| [](https://torc-ai.github.io/TruckDrive/static/TruckDriveMain.pdf) | |
| [](https://torc-ai.github.io/TruckDrive/static/TruckDriveSupplementary.pdf) | |
| [](https://arxiv.org/abs/2603.02413) | |
| [](http://torc-ai.github.io/TruckDrive) | |
| [](https://github.com/torc-ai/TruckDrive) | |
| **Filippo Ghilotti, Edoardo Palladin, Samuel Brucker, Adam Sigal, Mario Bijelic, Felix Heide** | |
| </div> | |
| <div align="center"> | |
| TruckDrive is a long-range autonomous highway driving dataset designed for heavy-truck safety, perception, prediction, and planning research. It targets high-speed highway operation, where reliable scene understanding hundreds of meters ahead is required for anticipatory planning and safe braking. | |
| This repository hosts the **TruckDrive Devkit** together with release documentation. | |
| </div> | |
| ## License | |
| See [`LICENSE-NONCOMMERCIAL.txt`](./LICENSE-NONCOMMERCIAL.txt) for the full non commercial license text. | |
| See [`LICENSE-COMMERCIAL`](./LICENSE-COMMERCIAL.txt) for the full commercial license text. | |
| ## Downloading the TruckDrive Dataset | |
| To download the dataset from Hugginfg Face use the provided [python script](./download_truckdrive.py). | |
| Download the full dataset: | |
| ```bash | |
| python download_truckdrive.py \ | |
| --out /PATH/TO/TruckDrive \ | |
| --all-scenes \ | |
| --all-modalities | |
| ``` | |
| To download only one scene: | |
| ```bash | |
| python download_truckdrive.py \ | |
| --out /PATH/TO/TruckDrive \ | |
| --scene scene_28_1 \ | |
| --all-modalities | |
| ``` | |
| To download only specific folders, replace --all-modalities with options such as: | |
| --camera --lidar --radar --poses --calibration --annotations --accumulated-gt-depth | |
| To automatically unzip the downloaded files add: --unzip. | |
| To automatically remove the downloaded files after unzipping add: --remove-zips-after-unzip. | |
| ## Highlights | |
| - **475k** synchronized multimodal samples | |
| - **165k** densely annotated frames | |
| - up to **1,000 m** for 2D benchmark annotations | |
| - up to **400 m** for 3D benchmark annotations | |
| - **7** long-range FMCW LiDARs, **3** short-range LiDARs, **10** 4D radars, and **11-15** cameras | |
| - supports perception, tracking, depth estimation, prediction, planning, and end-to-end driving | |
| ## Dataset Overview | |
| TruckDrive targets long-range, highway-scale autonomous driving for semi-trucks and other heavy commercial vehicles. It is designed to stress perception and planning systems beyond the short-range assumptions common in urban autonomous-driving benchmarks. | |
| | Item | Paper-reported description | | |
| |---|---| | |
| | Domain | Long-range highway and commercial-vehicle driving | | |
| | Platform | Semi-truck-mounted multimodal sensor suite | | |
| | Synchronized samples | **475k** | | |
| | Densely annotated frames | **165k** | | |
| | Unlabeled synchronized samples | **310k** | | |
| | Sequences | **3,828** sequences recorded over 2 years | | |
| | Sequence duration | **15-25 seconds** | | |
| | Average ego trajectory | **500 m** per sequence | | |
| | 2D annotation range | Up to **1,000 m** | | |
| | 3D annotation range | Up to **400 m** | | |
| | Primary operating regime | Highway-speed, long-range truck autonomy | | |
| ## Devkit | |
| You can find the devkit for the TruckDrive data in the [Devkit GitHub Page](https://github.com/torc-ai/TruckDrive) | |
| ## Citation | |
| If you find our dataset useful in your work, please cite us! | |
| ```bibtex | |
| @inproceedings{ghilotti2026truckdrive, | |
| title = {TruckDrive: Long-Range Autonomous Highway Driving Dataset}, | |
| author = {Ghilotti, Filippo and Palladin, Edoardo and Brucker, Samuel and Sigal, Adam and Bijelic, Mario and Heide, Felix}, | |
| booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, | |
| year = {2026} | |
| } | |
| ``` |