車道偏移警示系統是防範交通事故的主要駕駛輔助系統之一。本研究設計了一個嵌入式車道偏移警示系統，其作法包含影像前置處理、車道標記特徵分析、和左右車道線擷取、車道偏移判斷等四個主要功能模組。其中，車道標記特徵分析採用決策樹特徵分析，來篩選出候選車道標記，候選車道可進一步透過最小平方差進行直線參數偵測，以取得候選車道之直線模型，再以幾何特徵配對方式來找出最終車道線標記，最後再根據左右車道線來估計目前偏移量，在偏移量超過設定門檻值時，系統判定即將發生偏移，將發出警示提醒駕駛。對於真實環境的高雜訊道路影像，此一方法具有良好的強健性。本研究將系統實現於Raspberry Pi3嵌入式平台，以各種不同道路場景實際錄製之連續影像進行測試，實驗結果顯示出我們系統具有良好的可靠度，車道偵測正確率平均有84%以上，並且運作效能可達每秒30張即時需求。

The lane departure warning system is one of the main driving assistance systems to prevent traffic accidents. This study designed an embedded lane departure warning system, including image pre-processing, lane mark feature analysis, and left and right lane line extract, lane offset judgment and other four main functional modules. In this paper, the feature analysis of the lane mark is used to analyze the characteristics of the decision tree to select the candidate lane mark. The candidate lane can be further detected by the minimum squared difference to obtain the linear model of the candidate lane, and then the geometric characteristic pairing method The final lane mark, and finally according to the left and right lane line to estimate the current offset, the offset exceeds the set threshold, the system is about to be offset, the system will issue a warning to remind the driver. This method is robust in the real environment of high noise road image. In this study, the system is implemented on the Raspberry Pi3 embedded platform. The experimental results show that our system has good reliability, and the average correct rate of lane detection is more than 84% and operational efficiency of up to 30 real-time requirements per second.

[1] 世界衛生組織-道路安全全球現況報導[Online].Available: http://www.who.int/entity/violence_injury_prevention/road_safety_status/2015/zh/index.html
[2] 104年道路交通事故原因及車輛損(A1)[Online].Available: http://talas-pub.iot.gov.tw/TBfiles/Download/104_D_Table3.pdf
[3] 國道交通事故統計及特性分析. [Online].Available: http://www.freeway.gov.tw/Publish.aspx?cnid=516&p=2849
[4] J. C. McCall and M. M. Trivedi, "Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation," IEEE Transactions on Intelligent Transportation Systems, vol. 7, no. 1, pp. 20-37, 2006.
[5] V. Gaikwad and S. Lokhande, "Lane departure identification for advanced driver assistance," IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 2, pp. 910-918, 2015.
[6] M. Aly, "Real time detection of lane markers in urban streets," in Proceedings of IEEE Intelligent Vehicles Symposium, Jun. 2008, pp. 7–12.
[7] S.-Y. Kim and S.-Y. Oh, "A driver adaptive lane departure warning system based on image processing and a fuzzy evolutionary technique," in Proceedings of IEEE Intelligent Vehicles Symposium, Columbus, OH, June 2003, pp. 361-365.
[8] C. Mu and X. Ma, "Lane detection based on object segmentation and piecewise fitting," Indonesian Journal of Electrical Engineering and Computer Science, vol. 12, no. 5, pp. 3491-3500, 2014.
[9] A. Parajuli, M. Celenk, and H. B. Riley, "Robust lane detection in shadows and low illumination conditions using local gradient features," Open Journal of Applied Sciences, vol. 3, no. 01, p. 68, 2013.
[10] A. Borkar, M. Hayes, and M. T. Smith, "Robust lane detection and tracking with ransac and kalman filter," Proc. IEEE Int. Conf. Image Process., pp. 3261-3264, 2009.
[11] A. Borkar, M. Hayes, and M. T. Smith, "A novel lane detection system with efficient ground truth generation," IEEE Transactions on Intelligent Transportation Systems, vol. 13, no. 1, pp. 365-374, 2012.
[12] J. P. Gonzalez and U. Ozguner, "Lane detection using histogram-based segmentation and decision trees," Proc. IEEE Conf. Intell. Transp. Syst., pp. 346-351, 2000.
[13] N. R. Pal and S. K. Pal, "A review on image segmentation techniques," Pattern recognition, vol. 26, no. 9, pp. 1277-1294, 1993.
[14] A. K. Wong and P. K. Sahoo, "A gray-level threshold selection method based on maximum entropy principle," IEEE Transactions on Systems, Man, and Cybernetics, vol. 19, no. 4, pp. 866-871, 1989.
[15] Y. L. Chang and X. Li, "Adaptive image region-growing," IEEE transactions on image processing, vol. 3, no. 6, pp. 868-872, 1994.
[16] L. S. Davis, "A survey of edge detection techniques," Computer graphics and image processing, vol. 4, no. 3, pp. 248-270, 1975.
[17] T. Pavlidis and Y. T. Liow, "Integrating region growing and edge detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 3, pp. 225-233, 1990.
[18] R. Adams and L. Bischof, "Seeded region growing," IEEE Transactions on pattern analysis and machine intelligence, vol. 16, no. 6, pp. 641-647, 1994.
[19] F. Chang, C. J. Chen, and C. J. Lu, "A linear-time component-labeling algorithm using contour tracing technique," computer vision and image understanding, vol. 93, no. 2, pp. 206-220, 2004.
[20] R. Lumia, L. Shapiro, and O. Zuniga, "A new connected components algorithm for virtual memory computers," Computer Vision, Graphics, and Image Processing, vol. 22, no. 2, pp. 287-300, 1983.
[21] A. Rosenfeld and J. L. Pfaltz, "Sequential operations in digital picture processing," Journal of the ACM (JACM), vol. 13, no. 4, pp. 471-494, 1966.
[22] M. Kearns and Y. Mansour, "On the boosting ability of top-down decision tree learning algorithms," Proceedings of the twenty-eighth annual ACM symposium on Theory of computing, pp. 459-468, 1996.
[23] D. W. Marquardt, "An algorithm for least-squares estimation of nonlinear parameters," Journal of the society for Industrial and Applied Mathematics, vol. 11, no. 2, pp. 431-441, 1963.
[24] R. Risack, N. Mohler, and W. Enkelmann, "A video-based lane keeping assistant," in Proceedings of IEEE Intelligent Vehicles Symposium, pp. 506-511, 2000-Oct.
[25] D. C. Tseng, "Monocular computer vision aided road vehicle driving for safety," US Patents, US6765480 ,2004.
[26] 林君威, "以 3D 幾何為基礎的車道偏離警示系統與車道偏離誤差分析," 國立中央大學資訊工程學系博士論文, 2013.
[27] R. J. Mayer, "IDEF0 function modeling," A Reconstruction of the Original Air Force Wright Aeronautical Laboratory Technical Report, AFWAL-TR-81-4023 (The IDEF0 Yellow Book), Knowledge-Based System Inc, College Station, TX, 1992.
[28] A. Presley and D. H. Liles, "The Use of IDEF0 for the Design and Specification of Methodologies," Proceedings of the 4 Industrial Engineering Research Conference (May 1995), pp. 442-448. Norcross, GA: Institute of Industrial Engineers.
[29] C. H. Chen and J. H. Dai, "Design and high-level synthesis of hybrid controller," Proceedings of the IEEE International Conference on Networking, Sensing, and Control, Taipei, Taiwan, pp. 433-438, March 2004.
[30] C. H. Chen, C. M. Kuo, C. Y. Chen, and J. H. Dai, "The design and synthesis using hierarchical robotic discrete-event modeling," Journal of Vibration and Control, vol. 19, no. 11, pp. 1603-1613, 2013.
[31] 樹梅派基金會RASPBERRY PI FOUNDATION. [Online].Available: https://www.raspberrypi.org/
[32] 樹莓派 , Wiki. [Online].Available: https://zh.wikipedia.org/wiki/%E6%A0%91%E8%8E%93%E6%B4%BE