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Vehicle Platoons consist of a leader vehicle and a group of connected automated vehicles (CAV) that follow the leader at a predetermined inter-vehicle distance and move together at a certain common speed. This topic has been studied extensively in the literature by academicians in recent years. Therefore, a review of the literature on this topic is needed to understand which problems need to be solved and which issues need further study on vehicle platoons. For this reason, this study was conducted to reveal the latest situation on vehicle platoons with existing studies. This paper includes research and evaluation among themselves of artificial intelligence based nonlinear control techniques such as neural network based controllers, sliding mode controllers, back stepping controllers, fuzzy logic based controllers and machine learning, which are primarily used for CAV control. In addition, it consists of reviewing and comparing the methods and techniques used to solve problems related to different problem situations of vehicle platoons such as longitudinal control, lateral control, adding or removing vehicles from vehicle platoons, and communication methods between vehicle platoons. The latest research is reviewed both in examining these methods and techniques used and in applying these control techniques to vehicle platoons' problem situations. In addition, detailed comparisons were made by analyzing the situation of the platoon members, the purpose of the control technique used, and theoretical or practical applications.