Implementing a Cloud Platform for Autonomous Driving
This work addresses the infrastructure needs for autonomous vehicle development, but it is incremental as it focuses on implementing existing service types without introducing new paradigms.
The paper tackles the problem of implementing a unified cloud infrastructure to support autonomous driving services, such as distributed simulation, model training, and HD map generation, by detailing the design and integration of distributed computing, storage, and heterogeneous computing components.
Autonomous driving clouds provide essential services to support autonomous vehicles. Today these services include but not limited to distributed simulation tests for new algorithm deployment, offline deep learning model training, and High-Definition (HD) map generation. These services require infrastructure support including distributed computing, distributed storage, as well as heterogeneous computing. In this paper, we present the details of how we implement a unified autonomous driving cloud infrastructure, and how we support these services on top of this infrastructure.