In this episode we discuss Planning-oriented Autonomous Driving
by Authors:
- Yihan Hu
- Jiazhi Yang
- Li Chen
- Keyu Li
- Chonghao Sima
- Xizhou Zhu
- Siqi Chai
- Senyao Du
- Tianwei Lin
- Wenhai Wang
- Lewei Lu
- Xiaosong Jia
- Qiang Liu
- Jifeng Dai
- Yu Qiao
- Hongyang Li
Affiliations:
- Yihan Hu, Jiazhi Yang, Li Chen, Keyu Li, Chonghao Sima, Xizhou Zhu, and Xiaosong Jia: OpenDriveLab and OpenGVLab, Shanghai AI Laboratory
- Siqi Chai, Senyao Du, Tianwei Lin, and Qiang Liu: Wuhan University
- Wenhai Wang and Hongyang Li: OpenDriveLab and OpenGVLab, Shanghai AI Laboratory (†Project lead)
- Lewei Lu: SenseTime Research. The paper discusses how current autonomous driving systems use standalone modules or a multi-task paradigm, which can lead to errors or poor task coordination. The authors propose a framework called Unified Autonomous Driving (UniAD) that prioritizes tasks based on their contribution to planning and incorporates full-stack driving tasks in one network. They tested UniAD on the nuScenes benchmark and showed it outperformed previous state-of-the-art methods in all aspects. The code and models are publicly available.
view more