Home Projects WorldEngine
WorldEngine
Python

WorldEngine

WorldEngine: Towards the Era of Post-Training for Autonomous Driving

by OpenDriveLab · GitHub
Stars
Forks
License
Created
Last commit
Category
Language
3dgsend-to-end-autonomous-drivingpost-trainingApache-2.0Python
View on GitHub
In plain words

Develop and test autonomous driving systems using a framework designed for post-training and simulation.

You maintain this project?

Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.

Claim this page →
WorldEngine — GitHub preview card
📈 Star history
466465
2026-07-202026-08-31
📈 Track WorldEngine

Get an email alert on its next release or when it starts trending — never miss the moment.

Free · no card · unsubscribe anytime
Get email alerts →
📄 About

WorldEngine: Towards the Era of Post-Training for Autonomous Driving

WorldEngine has 465 stars on GitHub. It has been forked 29 times. WorldEngine is written mainly in Python. It has been in active development since 2026. WorldEngine is available under the Apache-2.0 license. Its main topics are 3dgs, end-to-end-autonomous-driving, post-training, simulation.

Frequently asked questions

What is WorldEngine?

WorldEngine: Towards the Era of Post-Training for Autonomous Driving

Is WorldEngine open source?

WorldEngine is an open-source project. It is released under the Apache-2.0 license.

Is WorldEngine free?

Yes. WorldEngine is free and open source — you can use, modify and self-host it.

What license does WorldEngine use?

WorldEngine is available under the Apache-2.0 license.

What language is WorldEngine written in?

WorldEngine is written mainly in Python.

🏅 Maintainer of this project?
olud.ai badge — WorldEngine

Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.

[![olud.ai](https://olud.ai/badge.php?tool=opendrivelab-worldengine)](https://olud.ai/project/opendrivelab-worldengine.html)
More badge options →
🧬 Shares DNA with🧬 View the DNA map →

Measured from GitHub topics shared by both projects, weighted by how rare each topic is.