臺灣博碩士論文加值系統

在未來，自動駕駛車輛會出現在人們的日常生活中，這些車輛被設計滿足人們通勤中的舒適性、安全性以及交通的通暢，為了要因應各種路況，自動駕駛車輛配備著許多像是光達、雷達、聲納、視覺等等的感測器，每種感測器都有各自不同的優缺點，因此將各種感測器組合在一起也就是所稱的感測器融合可以帶來許多好處，本論文在感測器部分融合了雷達與影像感測器，用以感知其他車輛的位置與速度。
對人們而言，在駕駛時做出切換車道或是超車等動作是相當常見的狀況，然而在從事這些行為時增加了出意外的風險，為了讓自駕車能夠解決這些問題，關於讓自動駕駛車輛切換車道的研究相當重要，這些研究主題包含了定位、感知、決策和控制等技術。
許多關於高速公路上讓自駕車執行切換車道的研究並未考慮相反車流的交通環境，本論文的目標為解決在相反車流交通環境下讓自駕車執行超車行為的問題，由於有了現有關於讓自駕車在高速公路執行切換車道的研究的幫助下，本篇論文提出了讓自駕車執行超車的新方法，並且透過模擬測試確保其可靠性。

The autonomous driving vehicle is the technology that will appear in daily life in the future. These vehicles are designed to assist the human driver in the task of lateral and longitudinal control with guaranteed comfort, safety, and throughput. In order to perform well in all kinds of the road environment, the autonomous vehicle is equipped with sensors such as LIDAR, radar, sonar, vision, and so on, Each sensor has different strength and weakness. As a result, combining them which is called sensor fusion will give an advantage. In this thesis, we fuse radar and vision sensors to get the position and velocity of other non-ego vehicles.
For human drivers, performing a lane change or overtake maneuver is common when driving. However, when performing these steps it increases the risk of accidents. We need autonomous vehicles to solve these problems so that the research on performing lane change maneuvers for autonomous vehicles is crucial. They consisted of localization, perception, decision-making, and control.
Most of the research on highway lane change doesn’t consider the two-way traffic environment. This thesis aims to solving the overtaking maneuver problems for autonomous vehicles in the two-way traffic environment. This thesis proposes a new method of performing overtake maneuvers for autonomous vehicles. It is tested by some simulations to show it's feasibility.

摘要 I
Abstract III
Acknowledgements V
Contents VI
List of Tables IX
List of Figures X
List of Abbreviations XII
Chapter 1 Introduction 1
1.1 Motivation and Objectives 1
1.2 Literature Review 1
1.3 Contributions 2
1.4 Thesis Overview 2
Chapter 2 Lane Change Maneuver 4
2.1 Coordinate Systems 4
2.2 Vehicle Model 6
2.3 Sensor Model 7
2.3.1 Vision sensor 8
2.3.2 Radar Sensor 10
2.4 Road Geometry 13
Chapter 3 Lane Change Algorithm 14
3.1 Review of Previous Research 14
3.1.1 Case A 14
3.1.2 Case B 15
3.1.3 Case C 16
3.1.4 Case D 18
3.2 Algorithms Overview 18
3.3 The Initialization of Lane Change Maneuver 20
3.4 Selecting Traffic Gap 21
3.5 Trajectory Planning 22
Chapter 4 Simulation and Results 27
4.1 Scenario Setup 27
4.2 Parameters 28
4.3 Driving Scenario Designer 29
4.4 Simulation and Analysis 33
4.4.1 Case 1 33
4.4.2 Case 2 40
4.4.3 Case 3 46
4.4.4 Case 4 51
Chapter 5 Conclusions and Future Works 56
5.1 Conclusions 56
5.2 Future Work 57
References 58

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