本研究之控制架構主要由兩大系統組成，分別為FPGA嵌入式平台建構出的四輪獨立驅動電動車行車控制系統以及使用筆記型電腦為處理核心，針對影像處理與雷射測距儀兩種數據進行分析的駕駛決策系統，兩系統之間以UART通訊方式溝通，實現多車道無人車自動駕駛之路徑追隨控制。本研究行車處理流程可以分為三大部分：首先車輛透過影像鏡頭拍攝車輛前方道路情況，經由影像前置處理獲得多車道標線之影像座標資訊，再使用電腦視覺Homography Matrix技術將此資訊轉換到世界座標系統當作目標軌跡；並使用四輪輪轂馬達與方向盤之編碼器迴授，搭配車輛運動模型以估測車輛現在狀態，進而得知目標軌跡與現在車輛位置相對之誤差；最後應用Pure Pursuit幾何軌跡追蹤控制演算法來計算車輛方向盤轉向角命令，完成閉迴路車輛軌跡追蹤控制。除此之外，如果車輛行車路徑前方出現障礙物，將會以上述第一部份影像多車道資訊結合雷射測距儀進行障礙物迴避之路徑規劃，最後將所有理論結合應用於實驗室所開發之四輪獨立驅動電動車，來驗證此架構穩定性與完整性。

The control architecture of this visual guided electric vehicle is consisted of a FPGA embedded system for the electric vehicle driving control and a PC for the image processing and data analyzing of laser ranger finder called driving decision
making system. Two systems are communicated with a UART interfere.
In this study, the vehicle visual guided driving process can be classified into three parts. Firstly, the road image ahead of vehicle is captured by using camera. The image pre-processing schemes are used to obtain multi-lane marking image coordinates information. Then, the Homography Matrix technology is used to convert the information into the world coordinate system for target trajectory tracking. Secondly, the vehicle current location is estimated by using the car kinematic model with four-wheels and steering encoders as feedback signals. Then the relative position error between target point and the vehicle current position can be founded. Finally, the pure pursuit geometric tracking control algorithm is used to calculate the steering angle correction command for closed loop trajectory tracking control purpose.
If there is an obstacle in front of the vehicle-driving path, the obstacle avoidance path planning will be generated based on acquired multi-lane image information and the laser ranger finder data. These image processing schemes, lane following algorithm, driving decision making and obstacle avoidance strategy are implemented on a lab made four- wheel drive electric vehicle for campus playground driving test.

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