停車可分為倒車入庫和路邊停車兩種不同的情況，而「自動停車」之重點技術分成三部份，第一部份為使用感測器建立車輛與停車空間的相對位置，第二部份為車輛最佳停車路徑的分析與規劃，第三部份為停車時之實際路徑估測與路徑追蹤控制，結合這三部份之技術才能代替駕駛人執行完整之倒車入庫或路邊停車之任務。對於自動停車系統而言，不同的車速、路面摩擦力，會使得規劃的停車路徑與真實路徑有一定的誤差產生，因此在自動停車時，需能準確的估測車輛與全域座標的相對位置，以利方向盤轉角做正確的修正，進而達到精準的自動停車路徑追隨的效果。本文將針對路邊停車空間進行補助停車系統之停車路徑規劃，並根據人們駕駛經驗，提出智慧型自動停車控制方法，針對路邊停車的情況，設計規劃自組織模糊控制器（SOFC）與輸入輸出回饋線性化控制器和PI控制器法則，並藉由本研究建立自動停車系統之相關策略分析。

Generally, the car parking situations can be divided into garage parking and road side parallel parking two categories. The main automatic parking technology can be classified into three parts. The first one is to construct the relative position of the vehicle and the parking space by using various sensors. The second one is the optimal parking trajectory planning based on the relative parking position. The third one is real-time vehicle moving path estimation and parking trajectory tracking control. The auto parking system must well combine these technologies. For practical car parking operation, the deviation between the planning parking trajectory and the real vehicle moving path will occur due to the speed and road friction difference. Therefore, the relative position of vehicle and the global coordinate must be precisely estimated for correcting the steering angle of steering wheel during the automatic parking path tracking control. In this thesis, the parallel parking space can be used for parking assistance system trajectory planning. Finally, an intelligent auto parking path tracking controllers will be designed for road side parallel parking based on driver experience. Self-Organizing Fuzzy Controller (SOFC) and Input-output feedback linearization controller and PI controller algorithm will be employed to design the path tracking controller.

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