Cloud-Edge-Terminal Collaborative AIGC for Autonomous Driving
Jianan Zhang, Zhiwei Wei, Boxun Liu, Xiayi Wang, Yu Yong, Rongqing Zhang
Abstract
In a dynamic autonomous driving environment, artificial intelligence-generated content (AIGC) technology can supplement vehicle perception and decision making by leveraging models' generative and predictive capabilities, and has the potential to enhance motion planning, trajectory prediction, and traffic simulation. This article proposes a cloud-edge-terminal collaborative architecture to support AIGC for autonomous driving. By delving into the unique properties of AIGC services, this article attempts to construct mutually supportive AIGC and network systems for autonomous driving, including communication, storage, and computation resource allocation schemes to support AIGC services, and leverage AIGC to assist system design and resource management.