PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving

ArXi:2507.17596v3 Announce Type: replace-cross While end-to-end autonomous driving models show promising results, their practical deployment is often hindered by large model sizes, a reliance on expensive LiDAR sensors and computationally intensive BEV feature representations. This limits their scalability, especially for mass-market vehicles equipped only with cameras. To address these challenges, we propose PRIX (Plan from Raw Pixels