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This letter introduces an intelligent Real-time Dual-functionalRadar-Communication (iRDRC) system for autonomous vehicles (AVs). This systemenables an AV to perform both radar and data communications functions tomaximize bandwidth utilization as well as significantly enhance safety. Inparticular, the data communications function allows the AV to transmit data,e.g., of current traffic, to edge computing systems and the radar function isused to enhance the reliability and reduce the collision risks of the AV, e.g.,under bad weather conditions. The problem of the iRDRC is to decide when to usethe communication mode or the radar mode to maximize the data throughput whileminimizing the miss detection probability of unexpected events given theuncertainty of surrounding environment. To solve the problem, we develop a deepreinforcement learning algorithm that allows the AV to quickly obtain theoptimal policy without requiring any prior information about the environment.Simulation results show that the proposed scheme outperforms baseline schemesin terms of data throughput, miss detection probability, and convergence rate.

iRDRC: An Intelligent Real-time Dual-functional Radar-Communication System for Automotive Vehicles