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 are available, both vehicles and edge servers are equipped with a set of camera-based vision sensors, also known as Visual IoT (V-IoT) techniques, for sensing and perception. Tremendous efforts have been made for achieving programmable communication, computation, and control. However, they are conducted mainly in the 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 the co-design of communication, computation, and control. This paper presents our vision of the end-to-end design principle for CAVs, called 4C, which extends the V-IoT 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.
翻译:连接和自主车辆(CAV)具有潜在的安全和效率效益,吸引了政府机构、工业和学术界的大量投资和兴趣,具有更大的计算和通信资源,车辆和边缘服务器都配备了一套基于摄像的视觉传感器,也称为Vibal IoT(V-IoT)技术,用于感知和感知; 为实现可编程的通信、计算和控制作出了巨大的努力; 然而,它们主要在筒仓模式下进行,限制了处理现实世界中具有挑战性的情景的响应和效率; 为了改善终端到终端的绩效,我们设想未来的CAV需要共同设计通信、计算和控制; 本文介绍了我们对CAVAV终端到终端设计原则的设想,称为4C,通过提供统一的通信、计算和控制共同设计框架,扩展了V-IOT系统; 在4C的可编程通信、精细的混合计算和高效的车辆控制方面,CAVAV可以处理关键情景并实现节能4驱动框架。