The millimeter-wave radar in automobiles has the advantages of all-weather, miniaturization, and high integration, which can provide indispensable perception capabilities for vehicles and has gradually become the focus of car manufacturers’ research. However, the increasing performance requirements have brought many challenges to the signal processing of automotive millimeter-wave radar. The driving environment is highly complex, dynamic, and uncertain, so simulation and verification simulation technology is regarded as the key technology to effectively solve the bottlenecks of long test cycles, high costs, and insufficient safety in traditional road and site testing. Millimeter-wave radar is an indispensable environmental perception sensor for advanced autonomous driving, so conducting modeling research on millimeter-wave radar and other environmental sensors is efficient, safe, and reliable, and is a key research topic that urgently needs to be solved for intelligent driving system research. It has urgent and important significance. Based on this goal, this chapter conducts a systematic study on millimeter-wave radar modeling and simulation for automotive intelligent driving, starting from the actual application of millimeter-wave radar, and aims to deepen the research. Based on radar signal modulation, this chapter summarizes the literature on range velocity estimation and angle estimation, compares their advantages and disadvantages, and discusses the algorithm optimization.