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（AV）和联网及自动化车辆（CAV）中最关键的挑战之一，对于车辆安全、乘客舒适性、交通效率和节能具有至关重要的作用。本文旨在全面深入地概述车辆控制技术的当前发展状况，重点关注从微观层面自主车辆中的车辆状态估计和轨迹跟踪控制到宏观层面联网及自动化车辆中的协同控制的演变过程。首先，本文从车辆关键状态估计入手，特别是作为车辆轨迹控制中最关键状态的车辆侧偏角，讨论了代表性方法。然后，我们介绍了用于自主车辆的代表性车辆轨迹跟踪控制方法。在此基础上，我们进一步综述了联网及自动化车辆的协同控制框架及其相应应用。最后，本文以对未来研究方向和挑战的讨论作为总结。本综述旨在对自主车辆和联网及自动化车辆领域车辆控制的最新技术进行情境化且深入的审视，确定关键研究重点，并指出未来可进一步探索的潜在领域。