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.

[1]中華民國內政部警政署警政治安全球資訊網，歷史交通事故資料，
https://www.npa.gov.tw/NPAGip/wSite/mp?mp=1
[2]美國公路安全保險協會,交通事故統計, https://m.iihs.org/mobile
[3]Takahashi, A., Y. Ninomiya, M. Ohta, M. Nishida, and M. Takayama, “Rear view lane detection by wide angle camera,” Proc. IEEEIntelligent Vehicles Symposium, Vol. 1, 2002, pp. 148-153.
[4]Bertozzi, M. and A. Broggi, “GOLD: a parallel real-time stereo visionsystem for generic obstacle and lane detection,” IEEE Trans. onImage Processing, Vol.7, Issue: 1, 1998, pp.62-81.
[5]H. Yoo, U. Yang, K. Sohn, “Gradient-enhancing conversion for illumination-robust lane detection,” IEEE Trans. Intell. Transp. Syst., 14 (3) (September 2013), pp. 1083-1094
[6]M.Borkar, M. Hayes, M. Smith, “A novel lane detection system with efficient ground truth generation,” IEEE Trans. Intell. Transp. Syst., 13 (1) (March 2012), pp. 365-374
[7]P.Y. Hsiao, C.W. Yeh, S.S. Huang, L.C. Fu, “A portable vision-based real-time lane departure warning system: day and night,” IEEE Trans. Veh. Technol., 58 (4) (May 2009), pp. 2089-2094
[8]D.P. Argialas, O.D. Mavrantza, “Comparison of edge detection and Hough transform techniques for the extraction of geologic features, ”Int. Arch. Photogram Remote Sens. Spat. Inform. Sci., 34 (2004), pp. 790-795
[9]J. Xiao, S. Li, B. Sun, “A real-time system for lane detection based on FPGA and DSP,” Sens. Imagine, 17 (6) (2016)
[10]J.C. McCall, M.M. Trivedi, “An integrated, robust approach to lane
marking detection and lane tracking,” IEEE Intelligent Vehicles Symposium, Parma, Italy, 2004, pp. 533–5
[11]D.J. LeBlanc, G.E. Johnson, P.J. Venhovens, G. Gerber, R.D. Sonia, R.D. Ervin, C.-F. Lin, A.G. Ulsoy, T.E. PiluttiCAPC, “a road-departure prevention system,” IEEE Control Systems Magazine, 16 (1996), pp. 61-71
[12]R. Risack, N. Mohler, W. Enkelmann, “A video-based lane keeping
assistant, in: Proceedings of IEEE Intelligent Vehicles Symposium,” Dearborn, MI, 2000, pp. 506–511.
[13]B. F. Wu, W. H. Chen, C. W. Chang, C. J. Chen and M. W. Chung, “A New Vehicle Detection with Distance Estimation for Lane Change Warning Systems,” IEEE Intelligent Vehicles Symposium, pp. 698-703, June 2007.
[14]L. Jia, L. Zheying and C. Tingting, “Study on Road Recognition Algorithm,” IEEE Conference Industrial Electronics and Applications (ICIEA), pp. 2539-2541, May 2007
[15]C. Y. Su and G. H. Fan, “An Effective and Fast Lane Detection Algorithm,” Proceedings of the 4th International Symposium on Advances in Visual Computing, vol. 5359, pp.942-948, 2008.
[16]Masayuki Furutani, “Obstacle Detection Systems for Vehicle Safety”, SAE Paper No.: 2004-21-0057.
[17]Ho Gi Jung, Chi Gun Choi, Pal Joo Yoon, and Jaihie Kim, “Novel User Interface for Semi-automatic Parking Assistance System”, 31st FISITA World Automotive Congress, Oct. 22-27, 2006.
[18]Yu Tanaka, Mitsuyoshi Saiki, Masaya Katoh, and Tomohiko Endo, “Development of Image Recognition for a Parking Assist System”, 13th World ongress on Intelligent Transportation Systems and Services, Oct. 8-12, 2006.
[19]Ho Gi Jung, Dong Suk Kim, Pal Joo Yoon, and Jaihie Kim, “Structure Analysis Based Parking Slot Marking Recognition for Semi-automatic Parking System”, Lecture Note in Computer Science Vol. 4109, Aug. 2006, pp. 384-393.
[20]J. Pohl, M. Sethsson, P. Degerman, and J. Larsson, “A Semi-automated Parallel Parking System for Passenger Car”, Proceedings of Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering Vol. 220, Issue 1, Jan.2006, pp. 53-65.
[21]Hisashi Satonaka, Masato Okuda, Syoichi Hyasaka, Tomohiko Endo, Yu Tanaka, and Toru Yoshida, “Development of Parking Space Detection Using an Ultrasonic Sensor”, 13th World Congress on Intelligent Transportation Systems and Services, Oct. 8-12, 2006.
[22]Stefan Görner and Hermann Rohling, “Parking Lot Detection with 24GHz Radar Sensor”, 3rd International Workshop on Intelligent Transportation, Mar. 14-16, 2006.
[23]Nico Kaempchen, Uwe Franke, and Rainer Ott, “Stereo Vision Based Pose Estimation of Parking Lots Using 3D Vehicle Models”, 2002 IEEE Intelligent Vehicle Symposium, Vol. 2, Jun. 17-21, 2002, pp. 459-464.
[24]Ho Gi Jung, Dong Suk Kim, Pal Joo Yoon, and Jaihie Kim, “3D Vision System for the Recognition of Free Parking Site Location”, International Journal of Automotive Technology, Vol. 7, No. 3, May 2006, pp. 361-367.
[25]Ho Gi Jung, Dong Suk Kim, Pal Joo Yoon, and Jaihie Kim, “Light Stripe Projection based Parking Space Detection for Intelligent Parking Assist System”, Proceedings of the 2007 IEEE Intelligent Vehicle Symposium, Jun. 13-15, 2007.
[26]Alexander Schanz, “Fahrerassistenz sum automatischen parken”, http://www.gyrosmafia.de/cms/front_content.php?idcat=74&idart=381, Jul. 23, 2007.
[27]Ho Gi Jung, Young Ha Cho, Pal Joo Yoon, and Jaihie Kim, “Integrated Side/Rear Safety System”, 11th European Automotive Congress, May 30-Jun. 1, 2007.
[28]Ho Gi Jung, Dong Suk Kim, Pal Joo Yoon, and Jaihie Kim, “Pakring Slot markings Recognition for Automatic Parking Assist System”, IEEE Intelligent Vehicles Symposium 2006, Jun. 13-15, 2006, pp. 106-113.
[29]Ho Gi Jung, "Light Stripe Projection Based Parking Space Detection for Intelligent Parking Assist System," IEEE Intelligent Transportation Systems, Volume.11, Issue.4, Dec 2010, pp.942 - 953.
[30]黃俊翰，以雙眼視覺輔助路邊停車，國立中山大學機械與機電工程學系碩士論文，中華民國101 年7 月。
[31]Sobel operator, 1 February 2019, https://en.wikipedia.org/wiki/Sobel_operator#cite_note-1
[32]HSL and HSV, 11 May 2019, https://en.wikipedia.org/wiki/HSL_and_HSV
[33]色彩空間中的HSL、HSV、HSB有什麼區别，中華民國107 年3 月，https://www.zhihu.com/question/22077462
[34]Mathematical morphology, 9 March 2019, https://en.wikipedia.org/wiki/Mathematical_morphology
[35]Canny edge detector, 14 April 2019, https://en.wikipedia.org/wiki/Canny_edge_detector
[36]Hough transform, 13 February 2019, https://en.wikipedia.org/wiki/Hough_transform
[37]Richard O. Duda and Peter E. Hart. Use of the Hough Transformation to Detect Lines and Curves in Pictures (PDF). Artificial Intelligence Center (SRI International). April 1971.