This paper proposed a two-section trajectory planning algorithm. In this trajectory planning, sigmoid function is adopted to fit two tangent arcs to meet limited parking spaces by reducing the radius of turning. Then the transverse preview model is established and the path tracking errors including distance error and angle error are estimated. The weight coefficient is considered to distribute the impact factor of traverse distance error or traverse angle error in the total error. The fuzzy controller is designed to track the two-section trajectory in autonomous intelligent parking system. The fuzzy controller is developed due to its real-time and robustness in the parking process. Traverse errors and its first-order derivative are selected as input variables and the outer wheel steering angle is selected as the output variable in fuzzy controller. They are also divided into seven fuzzy sets. Finally, forty rules are decided to achieve effective trajectory tracking. The detailed description of the proposed trajectory planning is demonstrated. The design aspects of Fuzzy Logic Controller and kinematic/dynamic theories in intelligent parking system are investigated in details. A combination of PreScan and Matlab Simulink is used to develop a numerical simulation model in order to verify the effectiveness of the proposed trajectory planning algorithm and Fuzzy Logic Controller in parking system. A superior performance is demonstrated and concluded for the proposed autonomous intelligent parking system.