Aiming at the problem of mixed traffic flow control in the context of development of cooperative vehicle infrastructure systems and autonomous driving technology, a speed control method of controlled connected autonomous vehicle based on road side unit(RSUs) to regulate the speed of macroscopic traffic flow is proposed. Firstly, this paper describes the adjustment process of a single controlled connected autonomous vehicle to the traffic state as a Markov decision process. A dynamic grid is designed to measure the influence of the controlled vehicle on the overall traffic flow. Considering the influence of the controlled vehicle on the traffic flow in the dynamic grid, the response speed to the expected target and the safety factor of the overall traffic flow, the reward function is constructed. The deep deterministic policy gradient(DDPG) algorithm is adopted for policy optimization. Considering the diversity of the traffic environment around the controlled connected autonomous vehicle, a control strategy model cluster based on key parameters is proposed for RSUs to select in real time according to traffic flow states. Secondly, for the real-time adjustment of traffic average speed, the division method of vehicle clusters in road sections and the timing handover strategy of control rights for multiple roadside units to control the particular vehicle cluster are proposed. The RSUs track vehicles within the signal coverage area in a vehicle cluster, and calculate the expected control signal in real time, then send it to the controlled vehicles. Finally, the proposed method is verified in different scenarios, which can smoothly and efficiently regulate the speed of traffic in multiple scenarios.