臺灣博碩士論文加值系統

本研究使用改裝電動車做為實驗平台來進行車道線偵測與辨識系統和具機械視覺之自動停車系統，本文研究重點著重在影像處理分析，而車輛動態控制等等則交由另一位同學所負責。電動車改裝部分主要為方向盤與剎車系統加裝馬達做為控制、油門深淺則是透過可變電阻來控制。首先車道線偵測與辨識的部分是透過電動車前檔風玻璃加裝攝影機做為車輛對外的感測器，透過高階程式語言Python所撰寫的車道線辨識程式碼將感測器所回傳即時影像進行線上處理並將運算結果傳送給做車輛動態控制的同學進行車輛修正。
自動停車系統的停車格偵測部分則是藉由車輛右側與後側加裝廣角攝影機做為感測器回傳即時影像給Python程式碼做影像運算，運算結果將傳給另一位同學做馬達與可變電阻的車輛動態修正。
最終實驗結果顯示車道線偵測與辨識系統能夠透過接收道路即時影像來對車輛進行修正使車輛能夠維持在車道中心行駛，另外具機械視覺之自動停車系統能在環境不複雜的情況下完成自動路邊停車的任務，也證明這兩種系統具備相當的穩定性與可行性。

In this thesis, a modified electric vehicle was used as an experimental platform for lane keeping system and automatic parking system with mechanical vision. The focus of this thesis is on image processing analysis, while vehicle dynamic control is handed over to another student. The modified part of the electric vehicle is mainly controlled by adding a motor to the steering wheel and the brake system, and the depth of the throttle is controlled by a variable resistor.
The first part of the lane detection and identification is to use the electric vehicle front windshield to add a camera as the external sensor of the vehicle. The lane recognition code written by the high-level programming language Python will return the sensor. The image is processed online and the result of the calculation is transmitted to the classmate who performs dynamic control of the vehicle to perform vehicle correction.
The parking compartment detection part of the automatic parking system uses the wide-angle camera which is installed on the right side and the rear side of the vehicle. It can be a sensor returning the real-time image to the Python code for image calculation, and the operation result will be transmitted to another classmate. Vehicle dynamic correction of motor and variable resistance.
The final experimental results show that the lane keeping system can correct the vehicle by receiving the road image to enable the vehicle maintain in the center of the lane. In addition, the automatic parking system with mechanical vision can complete the task of automatic roadside parking without complicated environment. It also proves that these two systems have considerable stability and feasibility.

摘要 I
Abstract III
謝誌 V
目錄 VI
表目錄 IX
圖目錄 X
第一章 緒論 1
1.1研究背景與動機 1
1.2文獻回顧 2
1.3研究內容與方法 4
1.4本文架構 6
第二章 系統架構與影像預處理之相關理論 7
2.1系統架構 7
2.1.1實驗電動車輛(伺服直流馬達、馬達驅動器、下位控制器) 7
2.1.2上位控制器(NVIDIA Jetson TX2 含開發套件) 8
2.1.3車道維持系統鏡頭 (羅技C920e) 10
2.1.4自動路邊停車系統鏡頭 (SONY CCD 鏡頭WB002) 10
2.1.5影像擷取器 11
2.2相機參數校正(計算校正矩陣與失真係數) 12
2.2.1相機模型 13
2.2.2魚眼扭曲失真模型 16
2.2.3求解外、內部參數、失真係數 19
第三章 車道線偵測與辨識之影像處理技術 20
3.1透視轉換(perspective transform) 20
3.2 Sobel Operator 21
3.2.1 Sobel (x direction) operator 22
3.2.2 Sobel (y direction) operator 23
3.2.3 Sobel magnitude operator 25
3.2.4 Sobel direction operator 26
3.3 HSL 色彩空間 28
3.3.1 HSL model 28
3.3.2 HSL color space threshold operator 30
3.4 Combined Thresholding 33
3.5像素分布圖 35
3.6滑動視窗曲線擬合(sliding window polynomial fitting) 37
3.7計算車輛偏移車道中心距離 38
3.8逆透視轉換(inverse perspective transform) 39
第四章 停車格偵測之影像處理技術 40
4.1圖像變形校正 40
4.2透視變换(perspective transform) 41
4.3 HSL 色彩空間 43
4.4圖像形態學處理(侵蝕與膨脹) 44
4.5圖像面積濾波 48
4.6像素分布圖 49
4.7 Canny邊緣檢測(Canny Edge Detector) 50
4.8霍夫變換(Hough Transform) 54
4.9點與直線距離 58
第五章 車道維持系統與自動路邊停車系統實驗結果 61
5.1車道維持系統實驗數據與結果分析討論 61
5.1.1測式地點介紹 61
5.1.2實驗硬體設置 62
5.1.3車道維持系統流程介紹 62
5.1.4車道維持系統結果與討論 63
5.2自動路邊停車系統設計與結果分析討論 73
5.2.1測式地點介紹 73
5.2.2實驗硬體設置 74
5.2.3路邊停車設計流程 74
5.2.4路邊停車結果與討論 81
5.2.5倒車入庫設計流程 83
5.2.6倒車入庫結果與討論 90
第六章 結論與未來展望 93
6.1車道維持系統結論 93
6.2自動路邊停車系統結論 94
6.3未來展望 96
參考文獻 97
作者簡介 101

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