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<h1>RAP</h1>
<h3>Rasterization Augmented Planning for End-to-End Autonomous Driving</h3>

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## Introduction
RAP introduces a lightweight **3D rasterization pipeline** for generating millions of synthetic driving views, combined with a **Raster-to-Real (R2R) alignment** module to bridge the sim-to-real gap in feature space.  
This enables scalable pretraining of end-to-end planners without costly photorealistic rendering.  
RAP achieves **1st place** on multiple leaderboards: Waymo Open E2E, NAVSIM v1/v2, and Bench2Drive.  


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## Getting Started
- [Environment Setup](https://github.com/autonomousvision/navsim)  
- [Training and Evaluation](docs/train_eval.md)  

