自動駕駛車輛藉由縱向和橫向車輛控制以改善舒適性，安全性和運輸吞吐量。 為了完成其任務，自動駕駛汽車安裝了多個傳感器，如激光雷達，雷達，聲納，視覺等。 每個傳感器具有不同的特性和功能，因此相互結合將帶來優勢。 在本文中，我們融合了雷達和視覺傳感器，以獲得引導車輛的相對位置和相對速度。 自動駕駛汽車之一項能力為自適應巡航控制系統（ACC）。 本文關注協同自適應巡航控制（CACC），每輛車將通過無線通信與其他車輛共享其信息。 它具有以下優點：車輛將知道來自其他車輛的信息，並且如果發生最壞情況有足夠的時間來處理。 本論文將使用由不同類型的車輛（客車和重型車輛）組成的異構排隊車輛進行弦穩定性之探討。 在CACC中，每輛車都會進行通信。 但此一設計會受限於傳輸故障，車輛之間的通信故障以及在車輛之間的通信期間處理數據延遲的問題。 另外，傾斜道路，空氣動力學等環境因素亦造成挑戰。 本論文同時考慮傳感器的噪音會影響排隊車輛的性能。 由於上述困難，排的弦穩定性可能導致不穩定，會引發碰撞之風險。 為克服上述問題，本論文選擇L1-AC控制器作為CACC控制器。 控制器必須仔細設計，考慮到不同的車輛。 在由於傳輸失敗而丟失數據的情況下，我們使用來自L1-AC的自適應估計來替換丟失的數據。 另一種情況是通信故障，我們提出了一種自適應信息流拓撲（IFT），以在通信故障下保持弦穩定性。 本論文利用模擬方式以評估所提方法之效能。

The autonomous vehicle is designed to assist the human driver in the task of longitudinal and lateral vehicle control with guaranteed comfort, safety, and throughput. In order to perform its task, the autonomous vehicle is equipped with sensors such as LIDAR, radar, sonar, vision and so on. Each sensor has different characteristics and capabilities so that combined each other will give an advantage. In this thesis, we fuse radar and vision sensor to get the relative position and velocity of the lead vehicle. The autonomous vehicle strongly depends on the sensor measurement. Nonetheless, we never acquire free noise sensor measurements.
At this time, the autonomous vehicle is marketable and produced by many companies with its ability, one of them, Adaptive Cruise Control (ACC). This thesis is concerned with the evolution of ACC called Cooperative Adaptive Cruise Control (CACC). The word cooperative on CACC refers to connect all vehicle. In CACC, each vehicle will share its information with other vehicles via wireless communication (vehicle-to-vehicle, vehicle-to-x). It is given the advantage that the vehicle will know information from other vehicle and has enough time to handle if the worst condition occurs. One of the most popular applications of CACC is platooning vehicle. This thesis will use a heterogeneous platooning vehicle which is platoon consisting of different type of vehicle (passenger car and heavy vehicle).
It was mentioned before that, in CACC, each vehicle will communicate. It also raises a problem such as transmission failure, communication fault between vehicles, and deal with data latency during communication between vehicles. The changing environment such as inclined road, aerodynamics force and so on give a challenge. We also take account noise from the sensor will affect the performance of platooning vehicle. Due to the above difficulty, the string stability of platoon may lead to unstable, thus the crash potential between vehicles in platoon increase.
To overcome the above problem, the L1-AC controller is chosen as CACC controller. The controller must be designed carefully which is taking account for a different vehicle. In the case of lost data due to transmission failure, we used the adaptive estimates from L1-AC to replace the lost data. Another case, communication fault, we proposed an adaptive Information Flow Topology (IFT) to keep string stability stable under communication fault. The efficacy of proposed methods for each case is shown in a computer simulation.

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