This paper presents a simulation of the automatic steering control system on a vehicle model using particle swarm optimization (PSO) to optimize the parameters of the control system. The control system involves fuzzy logic control (FLC) and proportional-integral-derivative (PID) control working in a cascade; the main control (FLC) is used to control lateral motion, and the secondary control (PID) is an enhancement to control the yaw motion in vehicle models representing 10 degrees of freedom of the vehicle dynamics system. Optimization by PSO is carried out simultaneously on both control systems. On FLC it is done by setting the width and the center point of the membership function (MF) in the input and output FLC so that the optimal composition of the MF parameter is obtained. The optimization process also determines the constants of optimal gain in the PID control. Testing is done through software in the loop simulation. Based on the test results it can be stated that FLC and PID control tuned by PSO can steer the vehicle rate well in accordance with desired trajectory and the vehicle motion can always be maintained at the specified path.