由於智慧型載具的蓬勃發展，對於載具動態穩定系統、防撞系統、道路偏移系統，甚至於自動導航系統的需求，精準的載具狀態是不可或缺的要素。一般而言，可以藉由全球定位系統(Global Positioning System, GPS)得到載具的位置、方向與速度。然而，當GPS受到干擾以至於定位精準度不夠可信的情況下，可藉由慣性導航系統(Inertial Navigation System, INS)和影像感測器來增加載具狀態的精準度。本論文利用車輛運動模型與擴展式卡爾曼濾波器發展多感知融合之精準定位演算法。隨著行車紀錄器的普及，幾乎所有車輛皆裝有行車紀錄器，因此本研究整合慣性感測元件（IMU），GNSS接收機和影像感測器進行載具狀態估測。此外，利用影像感測器偵測前方車輛，並於與前車太過相近時，給予駕駛警告。影像處理法則將實現於LabVIEW平台之人機界面（UMI）可進行即時觀察。而所提出之多感知融合定位演算法使用真實蒐集之資料於Matlab平台驗證。實驗結果不僅顯示所提出之多感知融合定位演算法可改善載具之定位精準度，此外亦說明所提出之前方防撞警示系統之可行性。

Due to the vigorous development of intelligent vehicles, the accurate vehicle state is an indispensable element for vehicle dynamic stability system, collision avoidance systems, lane departure warning system, and even the automatic navigation system. Generally, the global positioning system (Global Positioning System, GPS) can be used to obtain the vehicle position, direction and speed. However, the positioning accuracy becomes not credible enough when GPS is disturbed, the accuracy of vehicle status can be increased by an inertial navigation system (Inertial Navigation System, INS) and image sensors. In this thesis, the vehicle kinematic model and the extended Kalman filter algorithm are adopted to develop a multi-sensors fusion algorithm for precise positioning. With the popularity of driving recorder, almost every vehicle is equipped with a driving recorder. The aim of this research is to estimate vehicle state by fusing the measurements gathered from inertial measurement unit (IMU), GNSS receiver and image sensors. In addition, the vision-based collision warning system can warn the driver according to the forward vehicle width while the inter-vehicle distance gets too close. Image processing technique is implemented in LabVIEW user machine interface (UMI), which can be observed in real time. The proposed algorithm is verified by using real gathered data in Matlab platform. The experimental results demonstrate not only that the accuracy of the vehicle state is improved by the proposed positioning algorithm in GPS challenging environments, but also the proposed forward collision warning system is feasible.

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