The definition of the minimum time trajectory in a track is not obvious, since it is directly dependent on the acceleration limits that the vehicle can withstand. This paper presents an optimization method based on Genetic Algorithms that identifies the path that a car must follow in order to complete a given circuit in minimum time. By considering an Oriented Particle model, the method optimizes the acceleration profiles that drive the vehicle along the trajectory in minimum time. In addition, a fuzzy controller is designed to emulate the behavior of a human driver controlling a high speed car along the optimized trajectory. Two different error generation procedures were tested as controller inputs: the Present Trajectory Error and the Future-based Trajectory Error (FBTE), which gives information on the car’s tendency of movement. Results obtained with other controllers in the same application, such as the PDD, are compared to those provided by the fuzzy controller fed by the FBTE procedure.