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Lane Extraction through UAV Mapping and Its Accuracy Assessment
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 Title & Authors
Lane Extraction through UAV Mapping and Its Accuracy Assessment
Park, Chan Hyeok; Choi, Kyoungah; Lee, Impyeong;
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 Abstract
Recently, global companies are developing the automobile technologies, converged with state-of-the-art IT technologies for the commercialization of autonomous vehicles. These autonomous vehicles are required the accurate lane information to enhance its reliability by controlling the vehicles safely. Hence, the study planned to examine possibilities of applying UAV photogrammetry of high-resolution images, obtained from the low altitudes. The high-resolution DSM and the ortho-images were generated from the GSD 7cm-level digital images that were obtained and based on the generated data, when the positions information of the roads including the lanes were extracted. In fact, the RMSE of verifying the extracted data was shown to be about 15cm. Through the results from the study, it could be concluded that the low alititude UAV photogrammetry can be applied for generating and updating a high-accuracy map of road areas.
 Keywords
UAV;Mapping;Lane Extraction;Precision Road Map;Autonomous Vehicle;Advanced Driver Assistant System;
 Language
Korean
 Cited by
1.
고도가 다른 저사양 UAV 영상을 이용한 정사영상 및 DEM 제작,이기림;이원희;

한국측량학회지, 2016. vol.34. 5, pp.535-544 crossref(new window)
2.
저가형 UAV 영상의 영상향상기법에 따른 결과 분석,성지훈;이원희;

한국지형공간정보학회지, 2017. vol.25. 3, pp.3-12 crossref(new window)
 References
1.
Cho, J.H. (2014), Accuracy and Economic Feasibility Study of Orthoimage Map Production using UAV, Master's thesis, University of Seoul, Seoul, Korea, 66p. (in Korean with English abstract)

2.
Choi, M.W. (2010), Strategy of Development for Korea type-Unmanned Air Vehicle, Master's thesis, Kangwon National University, Chuncheon, Korea, 66p. (in Korean)

3.
Go, J.J. (2013), Design and implementation of ontology based context-awareness platform using driver intent information in the smart car environment, Ph.D. dissertation, Kwangwoon University, Seoul, Korea, 111p. (in Korean with English abstract)

4.
Hechri, A., Hmida, R., and Mtibaa, A. (2015), Robust road lanes and traffic signs recognition for driver assistance system, International Journal of Computational Science, Vol. 10, No.1-2, pp. 202–206.

5.
Heo, W.Y. (2015), Create a high-precision maps for autonomous cars, DigitalTimes, Seoul, http://m.news.naver.com/read.nhn?mode=LSD&mid=sec&sid1=101&oid=029&aid=0002303975 (last date accessed: 18 December 2015)

6.
Im, H.M. (2010), Construction and Updating of 3D Spatial Information for Small Areas using UAV, Ph.D. dissertation, Chungbuk National University, Cheongju, Korea, 123p. (in Korean with English abstract)

7.
Jeong, E.B. and Oh, C. (2013), Methodology for estimating safety benefits of advanced driver assistant systems, The Journal of the Korea Institute of Intelligent Transport System, Vol. 12, No. 3, pp. 65–77. (in Korean with English abstract) crossref(new window)

8.
Jeong, I.W. (2014), A Study on Autonomous Driving for Unmanned Vehicles, Master's thesis, Keimyung University, Daegu, Korea, 40p. (in Korean with English abstract)

9.
Jin, H., Feng, Y., and Li, Z. (2009), Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement, IEEE Transactions on Digital Image Computing, pp. 271–276.

10.
Kang, I.G. (2013), The Method for Improving the Integrity of the Data from Land-based Mobile Mapping System to Create Multipurpose, Ph.D. dissertation, University of Seoul, Seoul, Korea, 99p. (in Korean with English abstract)

11.
Kim, D.I., Song, Y.S., Kim, G.H., and Kim, C.W. (2014), A study on the application of UAV for Korean land monitoring, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 32, No. 1, pp. 29–38. (in Korean with English abstract) crossref(new window)

12.
Kim, S.G. (2014), A Study on Construction and Application of Spatial Information Utilizing Unmanned Aerial Vehicle System, Ph.D. dissertation, Mokpo National University, Muan, Korea, 161p. (in Korean with English abstract)

13.
Lin, Z. (2011), Chinese academy of surveying and mapping, GIScience & Remote Sensing, Vol 48, No. 1, pp. 1183-1186.

14.
Ogawa, T. and Takagi, K. (2006), Lane recognition using On-vehicle LIDAR, IEEE Transactions on Intelligent Vehicles Symposium, pp. 540–545.

15.
Park, J.H. (2013), Robust Lane Detection Algorithm Using Adaptive Set Region of Interest and Contrast Improvement, Master's thesis, Chonnam National University, Gwangju, Korea, 42p. (in Korean with English abstract)

16.
Park, T., Cho, J.S., and Cho, T.H. (2009), A study of lane extraction using Sobel intensity profile, The Transactions of the Korean Institute of Electrical Engineers, Vol. 2009, No. 5, pp. 228–230. (in Korean with English abstract)

17.
Seo, Y.W., Urmson, C., and Wettergreen, D. (2012), Ortho-Image Analysis for Producing Lane-Level Highway Maps, SIGSPATIAL '12 Proceedings of the 20th International Conference on Advances in Geographic Information Systems, ACM, 31 August, York, USA, pp. 506-509.

18.
Tahar, K.N. and Ahmad, A. (2012), A simulation study on the capabilities of rotor wing unmanned aerial vehicle in aerial terrain mapping, International Journal of Physical Sciences, Vol. 7, No. 8, pp. 1300–1306.

19.
Zhang, C. (2008), An UAV-based photogrammetric mapping system for road condition assessment, Remote Sensing and Spatial Information Sciences, Vol. XXXVII, Part B1, pp. 627–631.