Connected and autonomous vehicles (CAVs) are promising due to their potential safety and efficiency benefits, and have attracted massive investment and interest from government agencies, industry, and academia. With more computing and communication resources available, both vehicles and edge servers are equipped with a set of cam-era-based vision sensors, also known as Visual IoT (VIoT) techniques, for sensing and perception. Tremendous efforts have been made to achieve programmable communication, computation, and control. However, they are conducted mainly in silo mode, limiting the responsiveness and efficiency of handling challenging scenarios in the real world. To improve the end-to-end performance, we envision that future CAVs require co-design of communication, computation, and control. This article presents our vision of the end-to-end design principle for CAVs, called 4C, which extends the VIoT system by providing a unified communication, computation, and control co-design framework. With programmable communications, fine-grained heterogeneous computation, and efficient vehicle controls in 4C, CAVs can handle critical scenarios and achieve energy-efficient autonomous driving. Finally, we present several challenges to achieving the vision of the 4C framework.

中文翻译：

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4C：CAV 的计算、通信和控制协同设计框架


联网自动驾驶汽车 (CAV) 因其潜在的安全性和效率优势而前景广阔，并吸引了政府机构、工业界和学术界的大量投资和兴趣。随着更多的计算和通信资源可用，车辆和边缘服务器都配备了一组基于摄像头的视觉传感器，也称为视觉物联网（VIoT）技术，用于传感和感知。为了实现可编程通信、计算和控制，人们付出了巨大的努力。然而，它们主要以筒仓模式进行，限制了处理现实世界中具有挑战性的场景的响应能力和效率。为了提高端到端性能，我们预计未来的 CAV 需要通信、计算和控制的协同设计。本文介绍了我们对 CAV 端到端设计原则（称为 4C）的愿景，它通过提供统一的通信、计算和控制协同设计框架来扩展 VIoT 系统。凭借 4C 中的可编程通信、细粒度异构计算和高效车辆控制，CAV 可以处理关键场景并实现节能自动驾驶。最后，我们提出了实现 4C 框架愿景的几个挑战。