HiP-AD

HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder

arxiv paper project page

Introduction

• We propose a multi-granularity planning query representation that integrates various characteristics of waypoints to enhance the diversity and receptive field of the planning trajectory, enabling additional supervision and precise control in a closed-loop system.
• We propose a planning deformable attention mechanism that explicitly utilizes the geometric context of the planning trajectory, enabling dynamic retrieving image features from the physical neighborhoods of waypoints to learn sparse scene representations.
• We propose a unified decoder where a comprehensive interaction is iteratively conducted on planning-perception and planning-images, making an effective exploration of end-to-end driving in both BEV and perspective view, respectively.

Citation

@article{tang2025hipad,
  title={HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decoder},
  author={Yingqi Tang and Zhuoran Xu and Zhaotie Meng and Erkang Cheng},
  journal={arXiv preprint arXiv:2503.08612},
  year={2025}
}