This NSF Cyber-Physical Systems (CPS) grant will advance the state-of-the-art of Connected and Automated Vehicle (CAV) systems by innovating in the three key areas of networking, sensing, and computation, as well as the synergy among them. This work leverages several emerging technology trends that are expected to transform the ground transportation system: much higher-speed wireless connectivity, improved on-vehicle and infrastructure based sensing capabilities, and advances in machine learning algorithms. So far, most related research and development focused on individual technologies, leading to limited benefits. This project will develop an integrated platform that jointly handles networking, sensing, and computation, by addressing key challenges associated with the operating conditions of the CAVs: e.g., safety-critical, high mobility, scarce on-board computing resources, fluctuating network conditions, limited sensor capabilities. The research team will study how to use the integrated platform to enable real-world CAV applications, such as enhancement of public service personnel's safety, alleviation of congestion at bottleneck areas, and protection of vulnerable road users (VRUs). Given its interdisciplinary nature, this project will yield a broad impact in multiple research communities including transportation engineering, mobile/edge computing, and machine learning. The outcome of this research will benefit multiple stakeholders in the CAV ecosystem: drivers, pedestrians, CAV manufacturers, transportation government agencies, mobile network carriers, etc., ultimately improving the safety and mobility of the nation's transportation system. This project will also provide a platform to conduct various education and outreach activities.