為因應自動駕駛無人車之發展，車輛定位技術之精確度與可靠度扮演著相當重要的腳色，無人車若無法得知自身處於何處，就無法進行導航路徑之規劃或者是避障路線之設計。許多習知的技術都可達成精確的車輛定位，即時動態定位技術(Real Time Kinematic; RTK)，是為其中相當成熟且能達成公分等級之定位方法，但此一技術會受限於訊號之遮蔽程度的影響而無法總是取得最佳解。而結合慣性感測元件(IMU)和即時動態定位之耦合式定位技術解決了衛星訊號遭遮蔽時之難題。而使用光達事先建立精密地圖，而後在車輛行駛時透過光達和精密地圖進行匹配，解算車輛位置之即時定位與地圖構建(Simultaneous Localization and Mapping; SLAM)技術也是無人車定位之重要方法之一。雖然現在光達造價依然不斐，但在無人車勢必進入商業產品化的前提之下，可以預期商業化光達的誕生，因此光達定位技術之發展不能因為高價而停下腳步。在前期的計畫中，結合了光達和RTK/IMU耦合定位，發展了一個以光達為主之定位架構，能夠執行建圖和匹配定位。其在低速(10Km/h)下能達到十幾公分等級的定位，但在轉彎和高速(30Km/h以上)之高動態情況下，有著相當顯著的定位誤差。
本論文為研究光達定位技術為基礎之自動駕駛系統，並結合其他感測器如GNSS接收機、IMU和車輛里程計，提出一速度調適機制，協助定位系統於高動態的情況下能夠保持準確的定位結果。另外，也將探討單光達和雙光達對匹配定位之影響，對其定位結果進行比較和分析。而為了探討系統之強健性，在論文中也會針對不同的感測器可能造成的誤差進行分析，並以實車收錄資料進行驗證。

In order to successfully develop autonomous vehicles, the accuracy and reliability of vehicle positioning technology play a very important role. If an autonomous vehicle cannot know where it is, it cannot plan the navigation route or perform obstacle avoidance. Many well-known technologies can achieve accurate vehicle positioning. Real Time Kinematic (RTK) is a positioning method that is quite mature and can achieve a centimeter level accuracy, but this technology cannot always provide best solutions due the effect of signal blocking. The coupled positioning technology combined with inertial measurement unit (IMU) and RTK positioning solves the problem of satellite signal being blocked. With a precise map built in advance, a vehicle mounted with lidar can determine its location by matching the lidar data and the precise map, this kind of technology is so-called Simultaneous Localization and Mapping (SLAM), which is also one of significant localization skills for autonomous vehicles. Although the cost of lidar is still high, but under the premise that autonomous vehicles are bound to enter commercial productization, the birth of low cost lidar can be expected. Therefore, the development of localization algorithm using lidar cannot stop by current high cost of the lidar. In the previous research, combined with the lidar and RTK/IMU coupling positioning, a localization architecture based on lidar is developed, which can perform mapping and matching positioning. It can achieve ten-centimeters level positioning at low speed (10 km/h) but has a significant positioning error in the case of high dynamics of turning and high speed (above 30 km/h).
This thesis develops a lidar based localization system for autonomous vehicles. Combined with other sensors such as GNSS receiver, IMU and vehicle odometer, the thesis proposes a speed adjustment mechanism to help the positioning system maintain accurate positioning results under high dynamic conditions. In addition, the influence of single lidar and double lidars on the matching positioning will be discussed, and the positioning results will be compared and analyzed. For the robustness of the localization system, the thesis will also analyze the errors that may be caused by different sensors. In the end, experiments are conducted in real world to validate the performance of the proposed method.

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