{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T15:51:52Z","timestamp":1764172312899,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2018,11,26]],"date-time":"2018-11-26T00:00:00Z","timestamp":1543190400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The upraise of autonomous driving technologies asks for maps characterized bya broad range of features and quality parameters, in contrast to traditional navigation maps which in most cases are enriched graph-based models. This paper tackles several uncertainties within the domain of HD Maps. The authors give an overview about the current state in extracting road features from aerial imagery for creating HD maps, before shifting the focus of the paper towards remote sensing technology. Possible data sources and their relevant parameters are listed. A random forest classifier is used, showing how these data can deliver HD Maps on a country-scale, meeting specific quality parameters.<\/jats:p>","DOI":"10.3390\/ijgi7120458","type":"journal-article","created":{"date-parts":[[2018,11,27]],"date-time":"2018-11-27T03:31:33Z","timestamp":1543289493000},"page":"458","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Towards HD Maps from Aerial Imagery: Robust Lane Marking Segmentation Using Country-Scale Imagery"],"prefix":"10.3390","volume":"7","author":[{"given":"Peter","family":"Fischer","sequence":"first","affiliation":[{"name":"AUDI AG, 85045 Ingolstadt, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6084-2272","authenticated-orcid":false,"given":"Seyed Majid","family":"Azimi","sequence":"additional","affiliation":[{"name":"German Aerospace Center, 82234 Oberpfaffenhofen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert","family":"Roschlaub","sequence":"additional","affiliation":[{"name":"Bavarian Agency for Digitisation, High Speed Internet and Surveying, 80538 Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6004-1435","authenticated-orcid":false,"given":"Thomas","family":"Krau\u00df","sequence":"additional","affiliation":[{"name":"German Aerospace Center, 82234 Oberpfaffenhofen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,26]]},"reference":[{"key":"ref_1","unstructured":"Anderson, J.M., Kalra, N., Stanley, K.D., Sorensen, P., Samaras, C., and Oluwatola, O.A. (2014). Autonomous Vehicle Technology: A Guide for Policymakers, RAND Corporation."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1007\/s40534-016-0117-3","article-title":"Autonomous vehicles: Challenges, opportunities, and future implications for transportation policies","volume":"24","author":"Bagloe","year":"2016","journal-title":"J. Mod. Transp."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Geiger, A. (2012, January 16\u201321). Are we ready for autonomous driving? The KITTI vision benchmark suite. Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), CVPR \u201912, Providence, RI, USA.","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/J.ENG.2016.02.010","article-title":"Autonomous driving in the ICity\u2014HD maps as a key challenge of the automotive industry","volume":"2","author":"Seif","year":"2016","journal-title":"Engineering"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Obst, M., Bauer, S., Reisdorf, P., and Wanielik, G. (2012, January 3\u20137). Multipath detection with 3D digital maps for robust multi-constellation GNSS\/INS vehicle localization in urban areas. Proceedings of the 2012 IEEE Intelligent Vehicles Symposium, Alcala de Henares, Spain.","DOI":"10.1109\/IVS.2012.6232285"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Tao, Z., and Bonnifait, P. (2014, January 8\u201311). Tightly coupling GPS with lanemarkings for autonomous vehicle navigation. Proceedings of the 17th International IEEE Conference on Intelligent TransportationSystems (ITSC), Qingdao, China.","DOI":"10.1109\/ITSC.2014.6957729"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Tao, Z., and Bonnifait, P. (October, January 28). Road invariant extended Kalman filter for an enhanced estimation of GPS errors using lane markings. Proceedings of the2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany.","DOI":"10.1109\/IROS.2015.7353808"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"129","DOI":"10.5194\/isprs-archives-XLII-1-W1-129-2017","article-title":"Lane level localization; using images and HD maps to mitigate the lateral error","volume":"XLII-1\/W1","author":"Hosseinyalamdary","year":"2017","journal-title":"ISPRSInt. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Bauer, S., Alkhorshid, Y., and Wanielik, G. (2016, January 1\u20134). Using high definition maps for precise urban vehicle localization. Proceedings of the 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil.","DOI":"10.1109\/ITSC.2016.7795600"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Schreiber, M., Kn\u00f6ppel, C., and Franke, U. (2013, January 23\u201326). Laneloc: Lanemarking based localization using highly accurate maps. Proceedings of the 2013 IEEE Intelligent Vehicles Symposium (IV), Gold Coast, Australia.","DOI":"10.1109\/IVS.2013.6629509"},{"key":"ref_11","unstructured":"Burgard, W., Brock, O., and Stachniss, C. (2008). Map-Based Precision Vehicle Localization in Urban Environments, MIT Press."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Wang, S., Urtason, S., and Filder, S. (2015, January 7\u201312). Holistic 3d scene understanding from a single monocular image. Proceedings of the CVPR 2015 28th IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7299022"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1007\/978-3-642-03991-1_9","article-title":"Team annieway\u2019s autonomous system for the DARPA urban challenge 2007","volume":"Volume 56","author":"Buehler","year":"2009","journal-title":"The DARPA Urban Challenge, Springer Transactions in Advanced Robotics"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/MITS.2014.2306552","article-title":"Making bertha drive\u2014An autonomous journey on a historic route","volume":"6","author":"Ziegler","year":"2014","journal-title":"IEEE Intell. Transp. Syst. Mag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1109\/MITS.2014.2360306","article-title":"Experience, results and lessons learned from automated driving on Germany\u2019s highways","volume":"7","author":"Aeberhard","year":"2015","journal-title":"IEEE Intell. Transp. Syst.Mag."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1145\/3024087.3024092","article-title":"Addressing the uncertainties in autonomous driving","volume":"8","author":"Macfarlane","year":"2016","journal-title":"SIGSPATIAL Spec."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Massow, K., Kwella, B., Pfeifer, N., Husler, F., Pontow, J., Radusch, I., Hipp, J., Dlitzscher, F., and Haueis, M. (2016, January 1\u20134). Deriving HD maps for highly automated driving from vehicular probedata. Proceedings of the 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil.","DOI":"10.1109\/ITSC.2016.7795794"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Dabeer, O., Gowaiker, R., Grzechnik, S.K., Lakshman, M.J., Reitmayr, G., Somasundaram, K., Sukhavasi, R.T., and Wu, X. (arXiv, 2017). An end-to-end system for crowd sourced 3d maps for autonomous vehicles: The mapping component, arXiv.","DOI":"10.1109\/IROS.2017.8202218"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1320","DOI":"10.1139\/l06-069","article-title":"Efficient extraction of road information for car navigation applications using road pavement markings obtained from aerial images","volume":"33","author":"Kim","year":"2006","journal-title":"Can. J. Civil Eng."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Jin, H., Miska, M., Chung, E., Li, M., and Feng, Y. (2012). Road feature extraction from high resolution aerial images upon rural regions based on multi-resolution image analysis and Gabor filters. Remote Sensing-Advanced Techniques and Platforms, IntechOpen.","DOI":"10.5772\/45893"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Jin, H., and Feng, Y. (2010, January 5\u20137). Automated road pavement marking detection from high resolution aerial images based on multi-resolution image analysis and anisotropic Gaussian filtering. Proceedings of the 2010 2nd International Conference onSignal Processing Systems (ICSPS), Dalian, China.","DOI":"10.1109\/ICSPS.2010.5555636"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2747","DOI":"10.1080\/01431161.2011.620031","article-title":"Towards an automatic system for road lane marking extraction in large-scale aerial images acquired over rural areas by hierarchical image analysis and Gabor filter","volume":"33","author":"Jin","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/S0924-2716(03)00019-4","article-title":"Automatic extraction of urban road networks from multi-view aerial imagery","volume":"58","author":"Hinz","year":"2003","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Mnih, V., and Hinton, G.E. (2010). Learning to Detect Roads in High Resolution Aerial Images, Springer.","DOI":"10.1007\/978-3-642-15567-3_16"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Mattyus, G., Wang, S., Fidler, S., and Urtasun, R. (2016, January 27\u201330). HD maps: Fine-grained road segmentation by parsing ground and aerial images. Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.393"},{"key":"ref_26","unstructured":"Gellert, M., Luo, W., and Urtasun, R. (2017, January 21\u201326). DeepRoadMapper: Extracting Road Topology from Aerial Images. Proceedings of the International Conference on Computer Vision (CVPR), Honolulu, Hawaii."},{"key":"ref_27","first-page":"209","article-title":"A test of automatic road extraction approaches","volume":"36","author":"Mayer","year":"2006","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_28","first-page":"271","article-title":"A review of road extraction from remote sensing images","volume":"3","author":"Wang","year":"2016","journal-title":"J. Traffic Transp. Eng. (Engl. Ed.)"},{"key":"ref_29","unstructured":"Greenwalt, C., and Shultz, M. (1965). Principles of Error Theory and Cartographic Applications, Aeronautical Chart and Information Center. ACIC Technical Report."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Javanmardi, M., Javanmardi, E., Gu, Y., and Kamijo, S. (2017). Towards high-definition 3D urban mapping: Road feature-based registration of mobile mapping systems and aerial imagery. Remote Sens., 9.","DOI":"10.3390\/rs9100975"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Huang, J., Liang, H., Wang, Z., Song, Y., and Deng, Y. (2014, January 5\u201310). December. Lane marking detection based on adaptive threshold segmentation and road classification. Proceedings of the 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO), Bali, Indonesia.","DOI":"10.1109\/ROBIO.2014.7090345"},{"key":"ref_32","unstructured":"Tournaire, O., Paparoditis, N., and Lafarge, F. (2007, January 19\u201321). Rectangular road marking detection with marked point processes. Proceedings of theConference on Photogrammetric Image Analysis, Munich, Germany."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Azimi, S.M., Fischer, P., K\u00f6rner, M., and Reinartz, P. (arXiv, 2018). Aerial LaneNet: Lane Marking Semantic Segmentation in Aerial Imagery using Wavelet-Enhanced Cost-sensitive Symmetric Fully Convolutional Neural Networks, arXiv.","DOI":"10.1109\/TGRS.2018.2878510"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Lee, S., Kim, J., Yoon, J.S., Shin, S., Bailo, O., Kim, N., Lee, T.H., Hong, H.S., Han, S.H., and Kweon, I.S. (2017, January 22\u201329). October. Vpgnet: Vanishing point guided network for lane and road marking detection and recognition. Proceedings of the 2017 IEEE International Conference on Computer Vision (ICCV), Venice, Italy.","DOI":"10.1109\/ICCV.2017.215"},{"key":"ref_35","unstructured":"Gurghian, A., Koduri, T., Bailur, S.V., Carey, K.J., and Murali, V.N. (July, January 26). Deeplanes: End-to-end lane position estimation using deep neural networksa. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, Las Vegas, NV, USA."},{"key":"ref_36","first-page":"619","article-title":"TrueDOP\u2014A new quality step for official orthophotos","volume":"XLI-B4","author":"Baltrusch","year":"2016","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_37","unstructured":"Fischer, P., Pla\u00df, B., Kurz, F., Krau\u00df, T., and Runge, H. (2017, January 4\u20136). Validation of HD Maps for autonomous driving. Proceedings of the International Conference on Intelligent Transportation Systems in Theory and Practice mobil.TUM, Munich, Germany."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Kurz, F., Waigand, D., Pekezou-Fouopi, P., Vig, E., Corentin, H., Merkle, N., Rosenbaum, D., Gstaiger, V., Azimi, S.M., and Auer, S. (2018, January 10\u201312). DLRAD\u2014A first look on the new vision and mapping benchmark dataset. Proceedings of the ISPRS TC1 Symposium\u2014Accepted Contribution, Hannover, Germany.","DOI":"10.5194\/isprs-archives-XLII-1-251-2018"}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/7\/12\/458\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:32:12Z","timestamp":1760196732000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/7\/12\/458"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,26]]},"references-count":38,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2018,12]]}},"alternative-id":["ijgi7120458"],"URL":"https:\/\/doi.org\/10.3390\/ijgi7120458","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2018,11,26]]}}}