OpenEMMA
Open source end-to-end autonomous driving multi-modal model
Product Details
OpenEMMA is an open source project that reproduces Waymo's EMMA model and provides an end-to-end framework for motion planning of autonomous vehicles. The model leverages pre-trained visual language models (VLMs) such as GPT-4 and LLaVA to integrate text and forward-looking camera input to achieve accurate predictions of its own future waypoints and provide reasons for decision-making. The goal of OpenEMMA is to provide researchers and developers with easily accessible tools to advance autonomous driving research and applications.
Main Features
How to Use
Target Users
The target audience is researchers and developers in the field of autonomous driving. They need an end-to-end framework to implement and test autonomous driving algorithms. The open source tools provided by OpenEMMA can help them quickly build their own autonomous driving systems and accelerate the development process through pre-trained models.
Examples
Researchers use OpenEMMA to test new autonomous driving algorithms on the nuScenes dataset.
Developers use the framework provided by OpenEMMA to develop their own autonomous driving decision-making systems.
Educational institutions use OpenEMMA as a teaching tool to show students the practical applications of autonomous driving technology.
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