Cloud-Edge-Terminal Collaborative AIGC for Autonomous Driving

TL;DR

This paper introduces a collaborative cloud-edge-terminal architecture that leverages AIGC technology to enhance perception, decision-making, and planning in autonomous driving environments, focusing on system support and resource management.

Contribution

It proposes a novel architecture integrating AIGC with autonomous driving systems, including resource allocation schemes and system design strategies.

Findings

AIGC enhances perception and decision-making in autonomous driving.

Proposed resource allocation schemes optimize system performance.

Framework supports mutual support between AIGC services and network systems.

Abstract

In 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 initiates the 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 leveraging AIGC to assist system design and resource management.