This letter introduces an intelligent Real-time Dual-functional Radar-Communication (iRDRC) system for autonomous vehicles (AVs). This system enables an AV to perform both radar and data communications functions to maximize bandwidth utilization as well as significantly enhance safety. In particular, the data communications function allows the AV to transmit data, e.g., of current traffic, to edge computing systems and the radar function is used 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 use the communication mode or the radar mode to maximize the data throughput while minimizing the miss detection probability of unexpected events given the uncertainty of surrounding environment. To solve the problem, we develop a deep reinforcement learning algorithm that allows the AV to quickly obtain the optimal policy without requiring any prior information about the environment. Simulation results show that the proposed scheme outperforms baseline schemes in terms of data throughput, miss detection probability, and convergence rate.

中文翻译：

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iRDRC：用于汽车的智能实时双功能雷达通信系统

这封信介绍了一种用于自动驾驶汽车 (AV) 的智能实时双功能雷达通信 (iRDRC) 系统。该系统使 AV 能够执行雷达和数据通信功能，以最大限度地提高带宽利用率并显着提高安全性。特别是，数据通信功能允许自动驾驶汽车向边缘计算系统传输数据，例如当前交通的数据，雷达功能用于提高可靠性并降低自动驾驶汽车的碰撞风险，例如在恶劣天气条件下。iRDRC 的问题是决定何时使用通信模式或雷达模式，以在给定周围环境的不确定性的情况下最大化数据吞吐量，同时最小化意外事件的漏检概率。为了解决问题，我们开发了一种深度强化学习算法，使 AV 无需任何有关环境的先验信息即可快速获得最佳策略。仿真结果表明，所提出的方案在数据吞吐量、漏检概率和收敛速度方面均优于基线方案。