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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.

4C: A Computation, Communication, and Control Co-Design Framework for CAVs