This study analyzes front wheels steering (FWS) vehicles using results obtained from two unmanned cars: Unmanned Car I (UCI) and Unmanned Car II (UCII). The vehicle model integrates the lane angle derived from the translational system such that data on the lateral position, the lateral velocity and the lateral acceleration are comprehensively obtained. The main function of each block in the two newly developed structures is described as follows. Two angle controllers were used to eliminate the redundant components of the front-wheel steering angles. A lane scheduled gain (LSG) in each system was used to improve the lane angle deflection in UCI and UCII while the feed-forward controller simulates the behavior of a driver. The use of an empirical pre-filter reduces the lane angle error for UCI and UCII hence enhancing the performance of the system. Finally, the numerical calculation has shown that the two proposed systems are capable of tracking the desired course accurately.