Parallel Data and Foundation Model Driven Closed-Loop of Autonomous Driving
文献类型：会议论文
| 作者 | Bin Tian2 ; Tingting Yao2; Yisheng Lv2; Shichao Chen2; Yang Sun1; Ruiqi Song2
|
| 出版日期 | 2024 |
| 会议日期 | SEP 24-27, 2024 |
| 会议地点 | Edmonton, Canada |
| 英文摘要 | Data closed loop plays a crucial role in autonomous
driving for application in real world. The research for data closed
loop on autonomous driving in urban scene have been conducted
in the past few decades. But there is not unified framework for
data closed loop related to autonomous driving in surface mine.
The scenes in surface mine, which are unstructured, complex,
changeable, and the objects in surface mine like rockfalls, which
are differ in thousands of ways, not only put forward high
generalization requirements for our perception system, but also
bring many unpredictable risk for autonomous driving. In this
work, we proposed a uniform framework of data closed loop
driven by large-scale foundation model for autonomous driving
in surface mine. Corner cases are predicted through hard scenes
in simulation system, which is a parallel system with real scene.
In addition, high quality data selection and deployment model
distillation are conducted by method base on foundation model.
This framework can not only improve the generalization ability
of the perception but also promote the efficiency for corner
case mining and has achieved good application for autonomous
driving in surface mine. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/58530]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
| 通讯作者 | Tingting Yao; Ruiqi Song |
| 作者单位 | 1.Hebei University of Engineering 2.Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Bin Tian,Tingting Yao,Yisheng Lv,et al. Parallel Data and Foundation Model Driven Closed-Loop of Autonomous Driving[C]. 见:. Edmonton, Canada. SEP 24-27, 2024. |
入库方式： OAI收割
来源：自动化研究所
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