Automated driving has been gained increasing attention. However, many problems still need to be solved to achieve safe and efficient driverless technology. In this talk, we will discuss three difficulties: how to establish a rigid analysing framework to test data-driven machine learning models for automated vehicles, how to use virtual-real integrated testing techniques to accelerate testing, and how to automatically evaluate the performance of automated vehicles and seek the challenging scenarios.