本論文主旨在於實現具有自動路邊停車功能之智慧型代步車。在載具操控方面，以嵌入式系統作為系統之運算及控制核心，並透過控制器區域網路(Controller Area Network, CAN)匯流排接收感測器的資訊，即時下達控制指令給前輪轉向模組與後輪速度接收和驅動模組來達到控制智慧型代步車的目的。在定位方面，則使用可變磁阻感測器(Variable Reluctance Sensor, VRS)量測載具之速度資訊，並透過測距模型(Odometry Model)估測車子相對於起始點在任意時刻的姿態來達到即時定位的目的，並且同時利用型式A和型式B兩種校正方法來降低測距法的系統誤差以提升定位之精確性。此外；我們研發一套路邊停車演算法來自動導引載具進行路邊停車之功能。首先，演算法會使用超音感測器偵測停車空間大小是否合適。其次，車子在到達倒車地點後立即規劃合適的倒車路徑，最後，我們利用路經追蹤(Path Tracking)的方法設計基因模糊控制器來控制車子平穩地在倒車路徑上行駛。並由模擬和實驗結果證明本論文提出的路邊停車演算法之可行性與有效性。

The main focus of this thesis is to develop a genetic fuzzy controller for guiding steering of an intelligent vehicle to assist parallel parking. In the vehicle control, an embedded system is used as the central computing and control unit for receiving the information from sensors by a controller area network (CAN) bus. Based on the received information, the embedded system sends the commands to the front wheel driving circuit to steer the orientation of the vehicle, and to the rear driving circuit to control the vehicle speed. In the vehicle localization, a variable reluctance sensor (VRS) is employed to measure the speed of the vehicle. Based on this information, an odometry model is used to estimate the attitude of the vehicle to achieve real-time localization. In order to reduce the errors caused by the model uncertainty and improve the localization accuracy, two calibration methods—Type A and Type B have been proposed in this thesis. In addition, a parallel parking algorithm has been developed for guiding steer to assist parallel parking. The algorithm first uses ultrasonic sensors to scan the size of a parking space. If the size of the parking space fits in with the pre-specified parking requirements, the algorithm will indentify an appropriate ready-to-reverse position automatically. After the vehicle reaches the position, the reverse path will be generated from the ready-to-reverse position to the target parking position by the algorithm immediately. Finally, a path tracking system implemented by a genetic fuzzy controller is designed to control the vehicle to follow the reverse path smoothly. The simulation and experimental results have successfully validated the applicability and effectiveness of the proposed approaches.

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