臺灣博碩士論文加值系統

隨著一般民用汽車在社會上的普及率日益增加，智慧運輸系統在近年來成為一項熱門的研究領域，而車輛的智慧自動駕駛更是研究人員多年以來的夢想。自動駕駛系統 (Automated driving systems)與自主車輛 (Autonomous Vehicles) 能有效的提升行車中的安全性，並且降低駕駛對於行車操控時的失誤率，因此自動駕駛系統成為未來車輛產業的熱門趨勢。
在本文中，提出了基於模糊控制實現車道變換之自動駕駛，一種新穎且有效的車道變換方法。我們將運用2D-LiDAR偵測正前、左前、左後方的車道資訊，導入車道變換模糊決策器來決定出是否能安全地進行車道變換。再運用車道線偵測擷取車輛所在的位置與需要變換之車道，使用車道維持模糊控制器作為架構來選定不同車道線進行車道維持來達到車道變換，將可以大幅的增加其安全性。由實驗結果得知，本控制器能及時的將實驗車維持在車道線中，在需要變換車道時。實驗車輛高爾夫球車在保持安全距離的前提下能很好地變換車道。

With the increasing popularity of automobiles, Intelligent transportation systems have gradually become a popular research topic, Among them intelligent and autonomous driving of vehicles is a long-standing dream of men, Autonomous Vehicles or Automated driving systems can effectively improve driving safety and reduce the load on driving when driving. Therefore, autonomous vehicles and autonomous driving systems will become a popular trend in the future vehicle industry.
This paper proposes Implementation of Lane Change behaviors Based on Fuzzy Control a novel and effective lane change method. We will use 2D-LiDAR to detect the front, left front, and left rear lane information and import it into the lane change decision fuzzy controller to decide whether it is safe to change lanes. Then use the lane line detection to capture the position of the vehicle and the preset lane to change, and use the lane keeping fuzzy controller as the framework to select the lane line to maintain the lane and achieve the lane change, which will greatly increase its safety. From the experimental results, it is known that the controller can maintain the experimental vehicle in the lane line in time, when the lane needs to be changed. The experimental vehicle, the golf cart, was able to change lanes well while maintaining a safe distance.

摘要...i
Abstract...ii
誌謝...iii
目錄...iv
表目錄...vii
圖目錄...viii
第一章 緒論...1
1.1 研究背景 ...1
1.2 研究動機與目的...1
1.3 文獻回顧...2
1.3.1 模糊控制...2
1.3.2 自動駕駛...3
1.3.3 光學雷達...4
1.3.4 電腦視覺...4
1.3.5 車道變換...4
1.4 論文架構...5
第二章 自動駕駛系統架構...6
2.1 自動駕駛系統控制硬體架構...6
2.1.1 Jetson AGX Xavier Developer(AGX)...7
2.1.2 CAN Bus...8
2.1.3 搖桿(joystick)...10
2.2 感測器...11
2.2.1 2D LiDAR...12
2.2.2 攝影鏡頭...14
2.3 制動器...14
2.3.1 方向盤電動助力轉向系統(EPS)...15
2.3.2 油門、煞車控制...16
2.4 ROS介紹...17
第三章 模糊控制系統應用於自動駕駛...19
3.1 車道變換模糊決策器之設計...20
3.1.1 模糊控制器結構...21
3.1.2 模糊化(Fuzzifier)...22
3.1.3 模糊規則庫(Fuzzy Rule Base)...23
3.1.4 解模糊化(Defuzzifier)...25
3.2 LaneATT車道線偵測 [30]...28
3.2.1 車道線與錨點的表示...29
3.2.2 注意力機制...29
3.3 模糊控制實現車道維持 [31]...30
3.3.1 模糊化(Fuzzifier)...31
3.3.2 模糊規則庫(Fuzzy Rule Base...32
3.4 模糊控制整合...33
第四章 實驗結果與分析...36
4.1 實驗架設...36
4.2 實驗結果...37
4.2.1 實驗一:左側車道上有緩慢靠近與等速且並排行駛的車輛...37
4.2.2 實驗二:左側車道上有正在遠離的車輛...43
4.2.3 實驗三:左側車道上無任何車輛與障礙物...48
第五章 結論與未來展望...53
5.1 結論...53
5.2 未來展望...54
參考文獻...55
Extended Abstract...58

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