Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger comfort, transportation efficiency, and energy saving. This survey attempts to provide a comprehensive and thorough overview of the current state of vehicle control technology, focusing on the evolution from vehicle state estimation and trajectory tracking control in AVs at the microscopic level to collaborative control in CAVs at the macroscopic level. First, this review starts with vehicle key state estimation, specifically vehicle sideslip angle, which is the most pivotal state for vehicle trajectory control, to discuss representative approaches. Then, we present symbolic vehicle trajectory tracking control approaches for AVs. On top of that, we further review the collaborative control frameworks for CAVs and corresponding applications. Finally, this survey concludes with a discussion of future research directions and the challenges. This survey aims to provide a contextualized and in-depth look at state of the art in vehicle control for AVs and CAVs, identifying critical areas of focus and pointing out the potential areas for further exploration.

翻译：车辆控制是自主车辆（AVs）与网联自动驾驶车辆（CAVs）领域最关键的技术挑战之一，对车辆安全性、乘客舒适度、交通效率及节能降耗具有决定性作用。本综述旨在全面深入梳理车辆控制技术的当前发展态势，重点阐释从微观层面AVs的状态估计与轨迹跟踪控制，到宏观层面CAVs的协同控制这一演进脉络。首先，本文从车辆关键状态估计切入，以对车辆轨迹控制最具决定性的车辆侧偏角为典型对象，系统论述代表性方法。继而，我们展示了面向AVs的典型车辆轨迹跟踪控制方法。在此基础上，进一步综述了CAVs的协同控制框架及其对应应用场景。最后，本文探讨了未来研究方向与现存挑战。本综述旨在为AVs与CAVs的车辆控制领域提供具有情境认知的深度分析，识别关键研究领域，并指明潜在的拓展探索空间。