The optimization and further development of automated driving functions offer significant potential for reducing the driver's workload and increasing road safety. Among these functions, vehicle lateral control plays a critical role, especially with regard to its acceptance by end customers. This aspect requires significant development efforts to ensure its effectiveness and reliability in real-world conditions. This article focuses on the analysis of vehicle lateral control using extensive measurement data collected from a dedicated vehicle fleet at the Institute of Automotive Engineering at the Technical University of Braunschweig. Equipped with state-of-the-art measurement technology, the fleet has driven several hundred thousand kilometers, allowing for the collection of detailed information on vehicle trajectories under various driving conditions. These measurements have been classified into different driving environment domains - namely city, country road, and highway - with particular emphasis on the country road domain, which represents a unique challenge for automated driving and customer acceptance. The analysis examines different driving styles in curves, using different clustering methods to calculate characteristic parameters. These parameters are essential to accurately categorize and objectify driving behavior and performance in a systematic method. The insights gained from this analysis will serve as an important basis for future work aimed at developing adaptive trajectory planning in conjunction with automated vehicle lateral control. This research module aims not only to improve driving comfort, but also to foster greater customer acceptance, thereby further ensuring overall driving safety. Ultimately, this work will help provide the necessary foundation for the successful integration of automated driving functions into everyday road traffic in a manner that meets both user expectations and safety standards.