A digital twin is a system that maps real objects to the virtual world using real-time simulation technology. The application of digital twin technology can enable the self-driving test of real intelligent cars in virtual road scenarios. A digital twin-based in-the-loop test system for intelligent driving vehicles was designed and applied to the development and validation of the Autonomous Emergency Braking system. A vehicle-in-the-loop test system is formed by combining simulation test tools, vehicle to everything (V2X) communication equipment, real test vehicles, and other functional units under the framework of digital twin technology. This system maps virtual and real environments to each other. A mirror simulation scene of the real driving environment is constructed using Unreal Engine 4. V2X communication technology is utilized to transmit real-time state data from the real vehicle to the virtual AirSim vehicle controller. Additionally, the environment perception data of the simulation scene is fed back to the test vehicle. Considering the impact of signal delay in the test system, the AEB control algorithm is optimized and improved through in-loop testing of the entire vehicle under various operating conditions. Real vehicle tests have verified the effectiveness and superiority of the digital twin-based intelligent vehicle test method. The results demonstrate that this test method maintains the authenticity of real vehicle tests and effectively avoids the risks associated with them.