{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T13:02:38Z","timestamp":1780923758096,"version":"3.54.1"},"reference-count":248,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T00:00:00Z","timestamp":1705276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Spatial Algorithms Syst."],"published-print":{"date-parts":[[2024,3,31]]},"abstract":"<jats:p>\n            The rapid advancements in sensing techniques, networking, and artificial intelligence (AI) algorithms in recent years have brought autonomous driving vehicles closer to common use in vehicular transportation. One of the fundamental components to enable autonomous driving functionalities are\n            <jats:italic>High-Definition<\/jats:italic>\n            (HD) maps \u2013 a type of map that carries highly accurate and much richer information than conventional maps. The creation and use of HD maps rely on advances in multiple disciplines, such as computer vision\/object perception, geographic information systems, sensing, simultaneous localization and mapping, machine learning, etc.\n          <\/jats:p>\n          <jats:p>To date, several survey papers have been published describing the literature related to HD maps and their use in specialized contexts. In this survey, we aim to provide (1) a comprehensive overview of the issues and solutions related to HD maps and their use without attachment to a particular context; (2) a detailed coverage of the important domain knowledge of HD map furniture, from acquisition techniques and extraction approaches, through HD map\u2013related datasets, to furniture quality assessment metrics, for the purpose of providing a comprehensive understanding of the entire workflow of HD map furniture generation, as well as its use.<\/jats:p>","DOI":"10.1145\/3627160","type":"journal-article","created":{"date-parts":[[2023,10,12]],"date-time":"2023-10-12T14:55:20Z","timestamp":1697122520000},"page":"1-37","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Data Issues in High-Definition Maps Furniture \u2013 A Survey"],"prefix":"10.1145","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7161-9615","authenticated-orcid":false,"given":"Andi","family":"Zang","sequence":"first","affiliation":[{"name":"Northwestern University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7375-9833","authenticated-orcid":false,"given":"Runsheng","family":"Xu","sequence":"additional","affiliation":[{"name":"University of California, Los Angeles, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8839-6278","authenticated-orcid":false,"given":"Goce","family":"Trajcevski","sequence":"additional","affiliation":[{"name":"Iowa State University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8038-8150","authenticated-orcid":false,"given":"Fan","family":"Zhou","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology, PR China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,1,15]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Federal Highway Administration. 2013. Highway Statistics 2013. (2013). https:\/\/www.fhwa.dot.gov\/policyinformation\/statistics\/2013\/hm220.cf"},{"key":"e_1_3_2_3_2","article-title":"Automated Vehicles for Safety","author":"Administration National Highway Traffic Safety","unstructured":"National Highway Traffic Safety Administration. Automated Vehicles for Safety. https:\/\/www.nhtsa.gov\/technology-innovation\/automated-vehicles-safety##topic-road-self-driving. (n.d.).","journal-title":"https:\/\/www.nhtsa.gov\/technology-innovation\/automated-vehicles-safety##topic-road-self-driving"},{"key":"e_1_3_2_4_2","volume-title":"Proc. 8th Int. Workshop Intell. Transp.","author":"Aeberhard Michael","year":"2011","unstructured":"Michael Aeberhard and Nico Kaempchen. 2011. High-level sensor data fusion architecture for vehicle surround environment perception. In Proc. 8th Int. Workshop Intell. Transp., Vol. 665."},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2807385"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2975643"},{"key":"e_1_3_2_7_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-20801-5_57"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/1753326.1753531"},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2892405"},{"key":"e_1_3_2_10_2","first-page":"113816","article-title":"Self-driving cars: A survey","author":"Badue Claudine","year":"2020","unstructured":"Claudine Badue, R\u00e2nik Guidolini, Raphael Vivacqua Carneiro, Pedro Azevedo, Vinicius Brito Cardoso, Avelino Forechi, Luan Jesus, Rodrigo Berriel, Thiago Meireles Paixao, Filipe Mutz, et\u00a0al. 2020. Self-driving cars: A survey. Expert Systems with Applications (2020), 113816.","journal-title":"Expert Systems with Applications"},{"key":"e_1_3_2_11_2","volume-title":"History of Cartography","author":"Bagrow Leo","year":"2017","unstructured":"Leo Bagrow. 2017. History of Cartography. Routledge."},{"key":"e_1_3_2_12_2","article-title":"Digital elevation model (DEM) in GIS","author":"Balasubramanian A.","year":"2017","unstructured":"A. Balasubramanian. 2017. Digital elevation model (DEM) in GIS. University of Mysore (2017).","journal-title":"University of Mysore"},{"key":"e_1_3_2_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2798607"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1541-0420.2005.00320.x"},{"key":"e_1_3_2_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00138-011-0404-2"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1088\/1757-899X\/252\/1\/012096"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2016.7795600"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2014.2336271"},{"key":"e_1_3_2_19_2","volume-title":"CARS 2015-Critical Automotive Applications: Robustness & Safety","author":"Bergenhem Carl","year":"2015","unstructured":"Carl Bergenhem, Rolf Johansson, Andreas S\u00f6derberg, Jonas Nilsson, J\u00f6rgen Tryggvesson, Martin T\u00f6rngren, and Stig Ursing. 2015. How to reach complete safety requirement refinement for autonomous vehicles. In CARS 2015-Critical Automotive Applications: Robustness & Safety."},{"key":"e_1_3_2_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2013.2263460"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2019.2926573"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.3390\/ijgi4042842"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2020.101766"},{"key":"e_1_3_2_24_2","article-title":"The future of maps: Technologies, processes, and ecosystem","author":"Bonte Dominique","year":"2018","unstructured":"Dominique Bonte and James Hodgson. 2018. The future of maps: Technologies, processes, and ecosystem. https:\/\/www.here.com\/sites\/g\/files\/odxslz166\/files\/2019-01\/THE%20FUTURE%20OF%20MAPS.pdf. (2018).","journal-title":"https:\/\/www.here.com\/sites\/g\/files\/odxslz166\/files\/2019-01\/THE%20FUTURE%20OF%20MAPS.pdf"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.12720\/jcm.13.1.8-14"},{"key":"e_1_3_2_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/3447866"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-00318-9_2"},{"key":"e_1_3_2_28_2","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1007\/978-3-642-03798-6_7","volume-title":"Joint Pattern Recognition Symposium","author":"Brenner Claus","year":"2009","unstructured":"Claus Brenner. 2009. Global localization of vehicles using local pole patterns. In Joint Pattern Recognition Symposium. Springer, 61\u201370."},{"issue":"3","key":"e_1_3_2_29_2","first-page":"139","article-title":"Vehicle localization using landmarks obtained by a LIDAR mobile mapping system","volume":"38","author":"Brenner Claus","year":"2010","unstructured":"Claus Brenner. 2010. Vehicle localization using landmarks obtained by a LIDAR mobile mapping system. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences [PCV 2010-Photogrammetric Computer Vision and Image Analysis, Pt I] 38 (2010), Nr. Part 3A 38, Part 3A (2010), 139\u2013144.","journal-title":"International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences [PCV 2010-Photogrammetric Computer Vision and Image Analysis, Pt I] 38 (2010), Nr. Part 3A"},{"key":"e_1_3_2_30_2","article-title":"Total Construction Spending: Highway and street","author":"Bureau US Census","year":"2020","unstructured":"US Census Bureau. 2020. Total Construction Spending: Highway and street. https:\/\/fred.stlouisfed.org\/series\/TLHWYCONS. (2020).","journal-title":"https:\/\/fred.stlouisfed.org\/series\/TLHWYCONS"},{"key":"e_1_3_2_31_2","unstructured":"United States Census Bureau. 2010. Urban and Rural. (2010). https:\/\/www.census.gov\/geo\/reference\/urban-rural.html"},{"key":"e_1_3_2_32_2","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2014.2369522"},{"key":"e_1_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1190\/INT-2014-0257.1"},{"key":"e_1_3_2_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2013.10.008"},{"key":"e_1_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"e_1_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1098\/rsta.2010.0110"},{"key":"e_1_3_2_37_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISSC.2018.8585340"},{"key":"e_1_3_2_38_2","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3339815"},{"key":"e_1_3_2_39_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10846-011-9594-0"},{"key":"e_1_3_2_40_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00895"},{"key":"e_1_3_2_41_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-39469-1_10"},{"key":"e_1_3_2_42_2","doi-asserted-by":"publisher","DOI":"10.1109\/CRV.2018.00043"},{"key":"e_1_3_2_43_2","doi-asserted-by":"publisher","DOI":"10.3390\/s19040810"},{"key":"e_1_3_2_44_2","article-title":"Rethinking Maps for Self-Driving","author":"Chellapilla Kumar","year":"2018","unstructured":"Kumar Chellapilla. 2018. Rethinking Maps for Self-Driving. https:\/\/medium.com\/lyftlevel5\/https-medium-com-lyftlevel5-rethinking-maps-for-self-driving-a147c24758d6. (2018).","journal-title":"https:\/\/medium.com\/lyftlevel5\/https-medium-com-lyftlevel5-rethinking-maps-for-self-driving-a147c24758d6"},{"key":"e_1_3_2_45_2","doi-asserted-by":"publisher","DOI":"10.1145\/3274895.3284782"},{"key":"e_1_3_2_46_2","unstructured":"Xin Chen and Andi Zang. 2016. Method and apparatus for determining a building location based on a building image. (Aug. 16 2016). US Patent 9 418 446."},{"key":"e_1_3_2_47_2","doi-asserted-by":"publisher","DOI":"10.1109\/SPW.2019.00033"},{"issue":"2","key":"e_1_3_2_48_2","first-page":"14","article-title":"Introduction to machine learning, neural networks, and deep learning","volume":"9","author":"Choi Rene Y.","year":"2020","unstructured":"Rene Y. Choi, Aaron S. Coyner, Jayashree Kalpathy-Cramer, Michael F. Chiang, and J. Peter Campbell. 2020. Introduction to machine learning, neural networks, and deep learning. Translational Vision Science & Technology 9, 2 (2020), 14\u201314.","journal-title":"Translational Vision Science & Technology"},{"key":"e_1_3_2_49_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2018.2791533"},{"key":"e_1_3_2_50_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3037705"},{"key":"e_1_3_2_51_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISAR.2000.880928"},{"key":"e_1_3_2_52_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"e_1_3_2_53_2","article-title":"Deep learning for image and point cloud fusion in autonomous driving: A review","author":"Cui Yaodong","year":"2020","unstructured":"Yaodong Cui, Ren Chen, Wenbo Chu, Long Chen, Daxin Tian, and Dongpu Cao. 2020. Deep learning for image and point cloud fusion in autonomous driving: A review. arXiv preprint arXiv:2004.05224 (2020).","journal-title":"arXiv preprint arXiv:2004.05224"},{"issue":"4","key":"e_1_3_2_54_2","first-page":"119","article-title":"Lateral tilting in road vehicles\u2013a review","volume":"5","author":"Dacova Diana","year":"2020","unstructured":"Diana Dacova and Nikolay Pavlov. 2020. Lateral tilting in road vehicles\u2013a review. Trans Motauto World 5, 4 (2020), 119\u2013120.","journal-title":"Trans Motauto World"},{"key":"e_1_3_2_55_2","unstructured":"T. Dahlstrom. 2020. How Accurate Are HD Maps for Autonomous Driving and ADAS Simulation. (2020). https:\/\/atlatec.de\/en\/blog\/how-accurate-are-hd-maps-for-autonomous-driving-and-adas-simulation\/"},{"key":"e_1_3_2_56_2","doi-asserted-by":"publisher","DOI":"10.1109\/5.554206"},{"key":"e_1_3_2_57_2","article-title":"Perception: How Self-Driving Cars \u201cSee\u201d the World","author":"Dholakia Swarit","year":"2019","unstructured":"Swarit Dholakia. 2019. Perception: How Self-Driving Cars \u201cSee\u201d the World. https:\/\/swarit.medium.com\/perception-how-self-driving-cars-see-the-world-ae630636f4## (2019).","journal-title":"https:\/\/swarit.medium.com\/perception-how-self-driving-cars-see-the-world-ae630636f4##"},{"key":"e_1_3_2_58_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2011.2122334"},{"key":"e_1_3_2_59_2","article-title":"Disengagement Reports","author":"DMV California","year":"2020","unstructured":"California DMV. 2020. Disengagement Reports. https:\/\/www.dmv.ca.gov\/portal\/vehicle-industry-services\/autonomous-vehicles\/disengagement-reports\/. (2020).","journal-title":"https:\/\/www.dmv.ca.gov\/portal\/vehicle-industry-services\/autonomous-vehicles\/disengagement-reports\/"},{"key":"e_1_3_2_60_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISDA.2011.6121753"},{"key":"e_1_3_2_61_2","first-page":"1","volume-title":"Conference on Robot Learning","author":"Dosovitskiy Alexey","year":"2017","unstructured":"Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun. 2017. CARLA: An open urban driving simulator. In Conference on Robot Learning. PMLR, 1\u201316."},{"key":"e_1_3_2_62_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2016.10.017"},{"key":"e_1_3_2_63_2","article-title":"Semantic Maps for Autonomous Vehicles","author":"Efland Kris","year":"2019","unstructured":"Kris Efland and Holger Rapp. 2019. Semantic Maps for Autonomous Vehicles. https:\/\/medium.com\/lyftself-driving\/semantic-maps-for-autonomous-vehicles-470830ee28b6 (2019).","journal-title":"https:\/\/medium.com\/lyftself-driving\/semantic-maps-for-autonomous-vehicles-470830ee28b6"},{"key":"e_1_3_2_64_2","unstructured":"Hiroshi Endo Hiroshige Fukuhara and Motoki Hirano. 1988. Positioning system for a vehicle. (March 15 1988). US Patent 4 731 613."},{"key":"e_1_3_2_65_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00957"},{"key":"e_1_3_2_66_2","doi-asserted-by":"publisher","DOI":"10.3390\/s20154220"},{"key":"e_1_3_2_67_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.2972974"},{"issue":"2","key":"e_1_3_2_68_2","article-title":"A comprehensive survey of vision based vehicle intelligent front light system","volume":"7","author":"Feng Luo","year":"2017","unstructured":"Luo Feng and H. U. Fengjian. 2017. A comprehensive survey of vision based vehicle intelligent front light system. International Journal on Smart Sensing and Intelligent Systems 7, 2 (2017).","journal-title":"International Journal on Smart Sensing and Intelligent Systems"},{"key":"e_1_3_2_69_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2016.10.009"},{"key":"e_1_3_2_70_2","article-title":"Maps are key to safe, comfortable hands-off driving","author":"Frei Erwin A.","year":"2020","unstructured":"Erwin A. Frei. 2020. Maps are key to safe, comfortable hands-off driving. https:\/\/www.geospatialworld.net\/blogs\/maps-are-key-to-safe-comfortable-hands-off-driving\/ (2020).","journal-title":"https:\/\/www.geospatialworld.net\/blogs\/maps-are-key-to-safe-comfortable-hands-off-driving\/"},{"key":"e_1_3_2_71_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICWAPR.2010.5576425"},{"key":"e_1_3_2_72_2","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"e_1_3_2_73_2","doi-asserted-by":"publisher","DOI":"10.5555\/2354409.2354978"},{"key":"e_1_3_2_74_2","unstructured":"Jakob Geyer Yohannes Kassahun Mentar Mahmudi Xavier Ricou Rupesh Durgesh Andrew S. Chung Lorenz Hauswald Viet Hoang Pham Maximilian M\u00fchlegg Sebastian Dorn Tiffany Fernandez Martin J\u00e4nicke Sudesh Mirashi Chiragkumar Savani Martin Sturm Oleksandr Vorobiov Martin Oelker Sebastian Garreis and Peter Schuberth. 2020. A2D2: Audi autonomous driving dataset. (2020). arXiv:cs.CV\/2004.06320https:\/\/www.a2d2.audi"},{"key":"e_1_3_2_75_2","unstructured":"Kirk Patrick Goldsberry. 2007. Real-time traffic maps. University of California Santa Barbara."},{"key":"e_1_3_2_76_2","doi-asserted-by":"publisher","DOI":"10.3390\/s20216070"},{"key":"e_1_3_2_77_2","doi-asserted-by":"publisher","DOI":"10.3390\/electronics8010089"},{"key":"e_1_3_2_78_2","doi-asserted-by":"publisher","DOI":"10.1002\/rob.21918"},{"key":"e_1_3_2_79_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.arcontrol.2017.09.012"},{"key":"e_1_3_2_80_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3005434"},{"key":"e_1_3_2_81_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.array.2021.100057"},{"key":"e_1_3_2_82_2","doi-asserted-by":"publisher","DOI":"10.3389\/feart.2018.00233"},{"key":"e_1_3_2_83_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2972865"},{"key":"e_1_3_2_84_2","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8814205"},{"key":"e_1_3_2_85_2","article-title":"HERE HD Live Map","year":"2017","unstructured":"HERE. 2017. HERE HD Live Map. https:\/\/www.here.com\/sites\/g\/files\/odxslz166\/files\/2018-11\/HERE_HD_Live_Map_one_pager.pdf (2017).","journal-title":"https:\/\/www.here.com\/sites\/g\/files\/odxslz166\/files\/2018-11\/HERE_HD_Live_Map_one_pager.pdf"},{"key":"e_1_3_2_86_2","article-title":"Disengagement Report 2017 \u2013 The Good, The Bad, The Ugly","author":"Herger Mario","year":"2018","unstructured":"Mario Herger. 2018. Disengagement Report 2017 \u2013 The Good, The Bad, The Ugly. https:\/\/thelastdriverlicenseholder.com\/2018\/02\/01\/disengagement-report-2017-the-good-the-bad-the-ugly\/ (2018).","journal-title":"https:\/\/thelastdriverlicenseholder.com\/2018\/02\/01\/disengagement-report-2017-the-good-the-bad-the-ugly\/"},{"key":"e_1_3_2_87_2","doi-asserted-by":"publisher","DOI":"10.1068\/p090183"},{"key":"e_1_3_2_88_2","doi-asserted-by":"publisher","DOI":"10.1145\/1653771.1653854"},{"key":"e_1_3_2_89_2","article-title":"Naver open sources high definition map dataset for autonomous driving","author":"Hong Sung-yong","year":"2019","unstructured":"Sung-yong Hong and Minu Kim. 2019. Naver open sources high definition map dataset for autonomous driving. https:\/\/pulsenews.co.kr\/view.php?year=2019&no=889827 (2019).","journal-title":"https:\/\/pulsenews.co.kr\/view.php?year=2019&no=889827"},{"key":"e_1_3_2_90_2","article-title":"One thousand and one hours: Self-driving motion prediction dataset","author":"Houston John","year":"2020","unstructured":"John Houston, Guido Zuidhof, Luca Bergamini, Yawei Ye, Long Chen, Ashesh Jain, Sammy Omari, Vladimir Iglovikov, and Peter Ondruska. 2020. One thousand and one hours: Self-driving motion prediction dataset. arXiv preprint arXiv:2006.14480 (2020).","journal-title":"arXiv preprint arXiv:2006.14480"},{"key":"e_1_3_2_91_2","article-title":"One Thousand and One Hours: Self-driving Motion Prediction Dataset","author":"Houston J.","year":"2020","unstructured":"J. Houston, G. Zuidhof, L. Bergamini, Y. Ye, A. Jain, S. Omari, V. Iglovikov, and P. Ondruska. 2020. One Thousand and One Hours: Self-driving Motion Prediction Dataset. https:\/\/level-5.global\/level5\/data\/ (2020).","journal-title":"https:\/\/level-5.global\/level5\/data\/"},{"key":"e_1_3_2_92_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01112"},{"key":"e_1_3_2_93_2","volume-title":"Proceedings of Doctoral Symposium, 18th International Semantic Web Conference","author":"Huang Weimin","year":"2019","unstructured":"Weimin Huang. 2019. Knowledge-based geospatial data integration and visualization with semantic web technologies. In Proceedings of Doctoral Symposium, 18th International Semantic Web Conference."},{"key":"e_1_3_2_94_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00141"},{"key":"e_1_3_2_95_2","doi-asserted-by":"publisher","DOI":"10.1109\/QRS-C51114.2020.00045"},{"key":"e_1_3_2_96_2","volume-title":"Proceedings of XI EVU (European Association for Accident Research and Accident Analysis) Annual Meeting","volume":"32","author":"Hugemann Wolfgang","year":"2002","unstructured":"Wolfgang Hugemann. 2002. Driver reaction times in road traffic. In Proceedings of XI EVU (European Association for Accident Research and Accident Analysis) Annual Meeting, Vol. 32."},{"key":"e_1_3_2_97_2","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8813809"},{"issue":"4","key":"e_1_3_2_98_2","first-page":"41","article-title":"Understanding coordinate reference systems, datums and transformations","volume":"5","author":"Janssen V.","year":"2009","unstructured":"V. Janssen. 2009. Understanding coordinate reference systems, datums and transformations. International Journal of Geoinformatics 5, 4 (2009), 41\u201353.","journal-title":"International Journal of Geoinformatics"},{"key":"e_1_3_2_99_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.iatssr.2018.05.001"},{"key":"e_1_3_2_100_2","first-page":"21","volume-title":"Proc. of 26th ITS World Congress, Singapore","author":"Jenssen Gunnar Deinboll","year":"2019","unstructured":"Gunnar Deinboll Jenssen, Terje Moen, and Stig Ole Johnsen. 2019. Accidents with automated vehicles\u2014do self-driving cars need a better sense of self?. In Proc. of 26th ITS World Congress, Singapore. 21\u201325."},{"key":"e_1_3_2_101_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eng.2018.11.032"},{"key":"e_1_3_2_102_2","doi-asserted-by":"publisher","DOI":"10.1109\/COMPSAC.2018.00058"},{"key":"e_1_3_2_103_2","doi-asserted-by":"publisher","DOI":"10.1177\/001872087101300104"},{"key":"e_1_3_2_104_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2018.2886678"},{"key":"e_1_3_2_105_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trf.2018.03.021"},{"key":"e_1_3_2_106_2","article-title":"HERE introduces HD maps for highly automated vehicle testing","author":"Kent Leo","year":"2015","unstructured":"Leo Kent. 2015. HERE introduces HD maps for highly automated vehicle testing. https:\/\/360.here.com\/2015\/07\/20\/here-introduces-hd-maps-for-highly-automated-vehicle-testing\/ (2015).","journal-title":"https:\/\/360.here.com\/2015\/07\/20\/here-introduces-hd-maps-for-highly-automated-vehicle-testing\/"},{"key":"e_1_3_2_107_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8667.2007.00529.x"},{"key":"e_1_3_2_108_2","doi-asserted-by":"publisher","DOI":"10.1108\/02602280310468206"},{"key":"e_1_3_2_109_2","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1109\/TELFOR.2018.8612054","volume-title":"2018 26th Telecommunications Forum (TELFOR)","author":"Koci\u0107 Jelena","year":"2018","unstructured":"Jelena Koci\u0107, Nenad Jovi\u010di\u0107, and Vujo Drndarevi\u0107. 2018. Sensors and sensor fusion in autonomous vehicles. In 2018 26th Telecommunications Forum (TELFOR). IEEE, 420\u2013425."},{"key":"e_1_3_2_110_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-26250-1_26"},{"key":"e_1_3_2_111_2","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2016.2583491"},{"key":"e_1_3_2_112_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-58039-5_5"},{"key":"e_1_3_2_113_2","first-page":"2139","volume-title":"Proceedings of the 27th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2014)","author":"Kumar Rakesh","year":"2014","unstructured":"Rakesh Kumar and Mark G. Petovello. 2014. A novel GNSS positioning technique for improved accuracy in urban canyon scenarios using 3D city model. In Proceedings of the 27th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS+ 2014). 2139\u20132148."},{"key":"e_1_3_2_114_2","doi-asserted-by":"publisher","DOI":"10.1109\/ISKE.2015.35"},{"key":"e_1_3_2_115_2","doi-asserted-by":"publisher","DOI":"10.3390\/su12187817"},{"key":"e_1_3_2_116_2","doi-asserted-by":"publisher","DOI":"10.1109\/3.910448"},{"key":"e_1_3_2_117_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs2030641"},{"key":"e_1_3_2_118_2","article-title":"A Brief History of GPS In-Car Navigation","author":"Leite Jo\u00e3o Pedro","year":"2018","unstructured":"Jo\u00e3o Pedro Leite. 2018. A Brief History of GPS In-Car Navigation. https:\/\/ndrive.com\/brief-history-gps-car-navigation\/l (2018).","journal-title":"https:\/\/ndrive.com\/brief-history-gps-car-navigation\/l"},{"key":"e_1_3_2_119_2","article-title":"Vehicle detection from 3D lidar using fully convolutional network","author":"Li Bo","year":"2016","unstructured":"Bo Li, Tianlei Zhang, and Tian Xia. 2016. Vehicle detection from 3D lidar using fully convolutional network. arXiv preprint arXiv:1608.07916 (2016).","journal-title":"arXiv preprint arXiv:1608.07916"},{"key":"e_1_3_2_120_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2019.06.001"},{"key":"e_1_3_2_121_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3070251"},{"key":"e_1_3_2_122_2","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1109\/IVS.2016.7535492","volume-title":"Intelligent Vehicles Symposium (IV), 2016 IEEE","author":"Li Liang","year":"2016","unstructured":"Liang Li, Ming Yang, Chunxiang Wang, and Bing Wang. 2016. Road DNA based localization for autonomous vehicles. In Intelligent Vehicles Symposium (IV), 2016 IEEE. IEEE, 883\u2013888."},{"key":"e_1_3_2_123_2","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2013.2281199"},{"key":"e_1_3_2_124_2","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2973615"},{"key":"e_1_3_2_125_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3015992"},{"key":"e_1_3_2_126_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11390-020-0476-4"},{"key":"e_1_3_2_127_2","article-title":"Simaug: Learning robust representations from 3D simulation for pedestrian trajectory prediction in unseen cameras","volume":"2","author":"Liang Junwei","year":"2020","unstructured":"Junwei Liang, Lu Jiang, and Alexander Hauptmann. 2020. Simaug: Learning robust representations from 3D simulation for pedestrian trajectory prediction in unseen cameras. arXiv preprint arXiv:2004.02022 2 (2020).","journal-title":"arXiv preprint arXiv:2004.02022"},{"key":"e_1_3_2_128_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0373463319000638"},{"key":"e_1_3_2_129_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0373463319000638"},{"key":"e_1_3_2_130_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04791-6_8"},{"key":"e_1_3_2_131_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2848705"},{"key":"e_1_3_2_132_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs10101531"},{"key":"e_1_3_2_133_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8968122"},{"key":"e_1_3_2_134_2","doi-asserted-by":"publisher","DOI":"10.1177\/0278364916679498"},{"key":"e_1_3_2_135_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2003.08.006"},{"key":"e_1_3_2_136_2","doi-asserted-by":"publisher","DOI":"10.5555\/1060039.1060043"},{"key":"e_1_3_2_137_2","first-page":"6A\u20131","volume-title":"2018 IEEE International Reliability Physics Symposium (IRPS)","author":"Mariani Riccardo","year":"2018","unstructured":"Riccardo Mariani. 2018. An overview of autonomous vehicles safety. In 2018 IEEE International Reliability Physics Symposium (IRPS). IEEE, 6A\u20131."},{"key":"e_1_3_2_138_2","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2014.6856428"},{"key":"e_1_3_2_139_2","doi-asserted-by":"publisher","DOI":"10.1515\/auto-2014-1136"},{"key":"e_1_3_2_140_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.197"},{"key":"e_1_3_2_141_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.393"},{"key":"e_1_3_2_142_2","doi-asserted-by":"publisher","DOI":"10.1029\/2010GC003026"},{"key":"e_1_3_2_143_2","doi-asserted-by":"publisher","DOI":"10.1088\/1748-9326\/aabd42"},{"key":"e_1_3_2_144_2","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2004.1398899"},{"key":"e_1_3_2_145_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967762"},{"key":"e_1_3_2_146_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2012.2209421"},{"key":"e_1_3_2_147_2","doi-asserted-by":"publisher","DOI":"10.5194\/isprsannals-I-3-245-2012"},{"key":"e_1_3_2_148_2","article-title":"Estimated service life of wood poles","author":"Morrell Jeffrey J.","year":"2008","unstructured":"Jeffrey J. Morrell. 2008. Estimated service life of wood poles. Technical Bulletin, North American Wood Pole Council, http:\/\/www. woodpoles. org\/documents\/TechBulletin_EstimatedServiceLifeofWoodPole_12-08. pdf (Last accessed 5 April 2013) (2008).","journal-title":"Technical Bulletin, North American Wood Pole Council, http:\/\/www. woodpoles. org\/documents\/TechBulletin_EstimatedServiceLifeofWoodPole_12-08. pdf (Last accessed 5 April 2013)"},{"key":"e_1_3_2_149_2","article-title":"Deep learning for safe autonomous driving: Current challenges and future directions","author":"Muhammad Khan","year":"2020","unstructured":"Khan Muhammad, Amin Ullah, Jaime Lloret, Javier Del Ser, and Victor Hugo C. de Albuquerque. 2020. Deep learning for safe autonomous driving: Current challenges and future directions. IEEE Transactions on Intelligent Transportation Systems (2020).","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"e_1_3_2_150_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2017.08.014"},{"key":"e_1_3_2_151_2","article-title":"The Story of DIME: A Progress Report","year":"1997","unstructured":"NCGIA-Buffalo. 1997. The Story of DIME: A Progress Report. http:\/\/www.ncgia.buffalo.edu\/ncgia\/gishist\/DIME_story.html (1997).","journal-title":"http:\/\/www.ncgia.buffalo.edu\/ncgia\/gishist\/DIME_story.html"},{"key":"e_1_3_2_152_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.534"},{"key":"e_1_3_2_153_2","article-title":"The Why and How of Making HD Maps for Automated Vehicles","author":"Newsroom Intel","year":"2019","unstructured":"Intel Newsroom. 2019. The Why and How of Making HD Maps for Automated Vehicles. https:\/\/newsroom.intel.com\/articles\/why-how-making-hd-maps-automated-vehicles\/ (2019).","journal-title":"https:\/\/newsroom.intel.com\/articles\/why-how-making-hd-maps-automated-vehicles\/"},{"key":"e_1_3_2_154_2","article-title":"NVIDIA DRIVE Sim","year":"2021","unstructured":"NVIDIA. 2021. NVIDIA DRIVE Sim. https:\/\/developer.nvidia.com\/drive\/drive-sim (2021).","journal-title":"https:\/\/developer.nvidia.com\/drive\/drive-sim"},{"key":"e_1_3_2_155_2","article-title":"Transportation structure, highway and street industry gross output in the United States from 2008 to 2018","author":"Analysis Bureau of Economic","year":"2018","unstructured":"Bureau of Economic Analysis. 2018. Transportation structure, highway and street industry gross output in the United States from 2008 to 2018. https:\/\/www.statista.com\/statistics\/319593\/gross-output-of-us-highway-and-street-construction-industry\/ (2018).","journal-title":"https:\/\/www.statista.com\/statistics\/319593\/gross-output-of-us-highway-and-street-construction-industry\/"},{"key":"e_1_3_2_156_2","article-title":"Estimated U.S. Roadway Lane-Miles by Functional System","author":"Transportation U.S. Department of","year":"2021","unstructured":"U.S. Department of Transportation. 2021. Estimated U.S. Roadway Lane-Miles by Functional System. https:\/\/www.bts.gov\/content\/estimated-us-roadway-lane-miles-functional-system (2021).","journal-title":"https:\/\/www.bts.gov\/content\/estimated-us-roadway-lane-miles-functional-system"},{"key":"e_1_3_2_157_2","article-title":"Pavement Markings on Challenging Surfaces","author":"MN Department of Transportation","year":"2007","unstructured":"Department of Transportation MN. 2007. Pavement Markings on Challenging Surfaces. https:\/\/www.dot.state.mn.us\/trafficeng\/safety\/docs\/pavementmarkings.pdf (2007).","journal-title":"https:\/\/www.dot.state.mn.us\/trafficeng\/safety\/docs\/pavementmarkings.pdf"},{"key":"e_1_3_2_158_2","unstructured":"U.S. Department of Transportation Federal Highway Administration Office of Highway Policy Information. 2014. Public Road Length \u2014 2013 Miles By Functional System. (2014). https:\/\/www.fhwa.dot.gov\/policyinformation\/statistics\/2013\/hm20.cfm"},{"key":"e_1_3_2_159_2","volume-title":"Lidar for Maintenance of Pavement Reflective Markings and Retroreflective Signs","author":"Olsen Michael J.","year":"2018","unstructured":"Michael J. Olsen, Christopher Parrish, Erzhuo Che, Jaehoon Jung, Joseph Greenwood, et\u00a0al. 2018. Lidar for Maintenance of Pavement Reflective Markings and Retroreflective Signs. Technical Report. Oregon. Dept. of Transportation."},{"key":"e_1_3_2_160_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9196730"},{"key":"e_1_3_2_161_2","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2006.888394"},{"key":"e_1_3_2_162_2","unstructured":"S. O\u2019Haram. 2018. In-Vehicle Change Detection for Self Healing HD Maps. (2018). https:\/\/on-demand.gputechconf.com\/gtc\/2018\/presentation\/s8834-in-vehicle-change-detection-closing-loop-car.pdf"},{"key":"e_1_3_2_163_2","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.3004325"},{"key":"e_1_3_2_164_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12301"},{"key":"e_1_3_2_165_2","article-title":"A Milestone in Digital Mapping","author":"Partyka Janice","year":"2015","unstructured":"Janice Partyka. 2015. A Milestone in Digital Mapping. https:\/\/www.gpsworld.com\/a-milestone-in-digital-mapping\/l (2015).","journal-title":"https:\/\/www.gpsworld.com\/a-milestone-in-digital-mapping\/l"},{"key":"e_1_3_2_166_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793925"},{"key":"e_1_3_2_167_2","unstructured":"Joel Pazhayampallil and Kai Yuan Kuan. 2013. Deep learning lane detection for autonomous vehicle localization. (2013)."},{"issue":"2015","key":"e_1_3_2_168_2","first-page":"995","article-title":"Remote attacks on automated vehicles sensors: Experiments on camera and LiDAR","volume":"11","author":"Petit Jonathan","year":"2015","unstructured":"Jonathan Petit, Bas Stottelaar, Michael Feiri, and Frank Kargl. 2015. Remote attacks on automated vehicles sensors: Experiments on camera and LiDAR. Black Hat Europe 11, 2015 (2015), 995.","journal-title":"Black Hat Europe"},{"key":"e_1_3_2_169_2","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2010.5625276"},{"issue":"2","key":"e_1_3_2_170_2","first-page":"4","article-title":"PointNet: Deep learning on point sets for 3D classification and segmentation","volume":"1","author":"Qi Charles R.","year":"2017","unstructured":"Charles R. Qi, Hao Su, Kaichun Mo, and Leonidas J. Guibas. 2017. PointNet: Deep learning on point sets for 3D classification and segmentation. Proc. Computer Vision and Pattern Recognition (CVPR), IEEE 1, 2 (2017), 4.","journal-title":"Proc. Computer Vision and Pattern Recognition (CVPR), IEEE"},{"key":"e_1_3_2_171_2","doi-asserted-by":"publisher","DOI":"10.3390\/electronics9050741"},{"key":"e_1_3_2_172_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0097-8493(01)00090-5"},{"key":"e_1_3_2_173_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.352"},{"key":"e_1_3_2_174_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0373463301001503"},{"key":"e_1_3_2_175_2","doi-asserted-by":"publisher","DOI":"10.3390\/app9194093"},{"key":"e_1_3_2_176_2","article-title":"A survey on deep learning methods for robot vision","author":"Solar Javier Ruiz-del","year":"2018","unstructured":"Javier Ruiz-del Solar, Patricio Loncomilla, and Naiomi Soto. 2018. A survey on deep learning methods for robot vision. arXiv preprint arXiv:1803.10862 (2018).","journal-title":"arXiv preprint arXiv:1803.10862"},{"key":"e_1_3_2_177_2","doi-asserted-by":"publisher","DOI":"10.1109\/34.790428"},{"key":"e_1_3_2_178_2","article-title":"Millimeter precision HD Vector Maps","author":"Santos Thiago","year":"2018","unstructured":"Thiago Santos. 2018. Millimeter precision HD Vector Maps. https:\/\/blog.mapbox.com\/millimeter-precision-hd-vector-maps-874327d8327c (2018).","journal-title":"https:\/\/blog.mapbox.com\/millimeter-precision-hd-vector-maps-874327d8327c"},{"key":"e_1_3_2_179_2","doi-asserted-by":"crossref","unstructured":"Alexander Schaefer et\u00a0al. 2019. Long-term urban vehicle localization using pole landmarks extracted from 3-D lidar scans. European Conference on Mobile Robots (ECMR\u201919) . IEEE 1\u20139.","DOI":"10.1109\/ECMR.2019.8870928"},{"key":"e_1_3_2_180_2","doi-asserted-by":"crossref","unstructured":"Andreas Schindler. 2013. Vehicle self-localization with high-precision digital maps. In 2013 IEEE Intelligent Vehicles Symposium workshops (IV Workshops) . IEEE 134\u2013139.","DOI":"10.1109\/IVWorkshops.2013.6615239"},{"key":"e_1_3_2_181_2","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2014.6856460"},{"key":"e_1_3_2_182_2","article-title":"Why we\u2019re mapping down to 20cm accuracy on roads","author":"Schumann Stefanie","year":"2014","unstructured":"Stefanie Schumann. 2014. Why we\u2019re mapping down to 20cm accuracy on roads. https:\/\/360.here.com\/2014\/02\/12\/why-were-mapping-down-to-20cm-accuracy-on-roads\/ (2014).","journal-title":"https:\/\/360.here.com\/2014\/02\/12\/why-were-mapping-down-to-20cm-accuracy-on-roads\/"},{"key":"e_1_3_2_183_2","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2017.7995692"},{"key":"e_1_3_2_184_2","doi-asserted-by":"publisher","DOI":"10.1016\/J.ENG.2016.02.010"},{"key":"e_1_3_2_185_2","doi-asserted-by":"publisher","DOI":"10.1145\/2424321.2424401"},{"key":"e_1_3_2_186_2","first-page":"012013","volume-title":"IOP Conference Series: Materials Science and Engineering","volume":"386","author":"Shadrin S. S.","year":"2018","unstructured":"S. S. Shadrin. 2018. Geoinformation Support of Ground Vehicles\u2019 Autonomous Driving. In IOP Conference Series: Materials Science and Engineering, Vol. 386. IOP Publishing, 012013."},{"key":"e_1_3_2_187_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66787-4_22"},{"key":"e_1_3_2_188_2","article-title":"Taking Self-Driving Safety Standards Beyond ISO 26262","author":"Shuler Kurt","year":"2019","unstructured":"Kurt Shuler. 2019. Taking Self-Driving Safety Standards Beyond ISO 26262. https:\/\/semiengineering.com\/taking-self-driving-safety-standards-beyond-iso-26262\/ (2019).","journal-title":"https:\/\/semiengineering.com\/taking-self-driving-safety-standards-beyond-iso-26262\/"},{"key":"e_1_3_2_189_2","first-page":"79","article-title":"On the concept of total highway management","volume":"1229","author":"Sinha Kumares C.","year":"1989","unstructured":"Kumares C. Sinha and Tien F. Fwa. 1989. On the concept of total highway management. Transportation Research Record 1229 (1989), 79\u201388.","journal-title":"Transportation Research Record"},{"key":"e_1_3_2_190_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2008.2011712"},{"key":"e_1_3_2_191_2","first-page":"656","volume-title":"Advances in Neural Information Processing Systems","author":"Socher Richard","year":"2012","unstructured":"Richard Socher, Brody Huval, Bharath Bath, Christopher D. Manning, and Andrew Y. Ng. 2012. Convolutional-recursive deep learning for 3D object classification. In Advances in Neural Information Processing Systems. 656\u2013664."},{"key":"e_1_3_2_192_2","volume-title":"Navigation Data Standard \u2014 Open Lane Model Documentation","author":"Standard Navigation Data","year":"2016","unstructured":"Navigation Data Standard. 2016. Navigation Data Standard \u2014 Open Lane Model Documentation. Technical Report. Navigation Data Standard."},{"key":"e_1_3_2_193_2","article-title":"Building maps for a self-driving car","author":"Team Waymo","year":"2016","unstructured":"Waymo Team. 2016. Building maps for a self-driving car. https:\/\/medium.com\/waymo\/building-maps-for-a-self-driving-car-723b4d9cd3f4 (2016).","journal-title":"https:\/\/medium.com\/waymo\/building-maps-for-a-self-driving-car-723b4d9cd3f4"},{"key":"e_1_3_2_194_2","unstructured":"Roadtraffic Technology. 2014. The world\u2019s biggest road networks. (2014). http:\/\/www.roadtraffic-technology.com\/features\/featurethe-worlds-biggest-road-networks-4159235"},{"key":"e_1_3_2_195_2","article-title":"HD vector maps open standard","author":"Thompson Blake","year":"2018","unstructured":"Blake Thompson. 2018. HD vector maps open standard. https:\/\/blog.mapbox.com\/hd-vector-maps-open-standard-335a49a45210. (2018). Online.","journal-title":"https:\/\/blog.mapbox.com\/hd-vector-maps-open-standard-335a49a45210"},{"key":"e_1_3_2_196_2","article-title":"NCHRP report 713: Estimating life expectancies of highway assets","author":"Thompson P. D.","year":"2012","unstructured":"P. D. Thompson, K. M. Ford, M. H. R. Arman, S. Labi, K. Sinha, and A. Shirol\u00e9. 2012. NCHRP report 713: Estimating life expectancies of highway assets. Transportation Research Board of the National Academies, Washington, DC (2012).","journal-title":"Transportation Research Board of the National Academies, Washington, DC"},{"key":"e_1_3_2_197_2","unstructured":"Yuduo Tian. 2018. The Golden Age of HD Mapping for Autonomous Driving. (2018). https:\/\/medium.com\/syncedreview\/the-golden-age-of-hd-mapping-for-autonomous-driving-b2a2ec4c11"},{"key":"e_1_3_2_198_2","article-title":"Baidu Driverless Cars Run in Wuzhen, Powered By Four Leading Technologies","year":"2016","unstructured":"TMTpost. 2016. Baidu Driverless Cars Run in Wuzhen, Powered By Four Leading Technologies. https:\/\/medium.com\/@TMTPOST\/baidu-driverless-cars-run-in-wuzhen-powered-by-four-leading-technologies-tmtpost-53c0b3072cec (2016).","journal-title":"https:\/\/medium.com\/@TMTPOST\/baidu-driverless-cars-run-in-wuzhen-powered-by-four-leading-technologies-tmtpost-53c0b3072cec"},{"key":"e_1_3_2_199_2","article-title":"HD Map with RoadDNA","unstructured":"TomTom. HD Map with RoadDNA. https:\/\/download.tomtom.com\/open\/banners\/HD-Map-with-RoadDNA-Product-Sheet.pdf (n.d.).","journal-title":"https:\/\/download.tomtom.com\/open\/banners\/HD-Map-with-RoadDNA-Product-Sheet.pdf"},{"key":"e_1_3_2_200_2","unstructured":"TomTom. 2017. TomTom HD Map with RoadDNA. (2017). https:\/\/automotive.tomtom.com\/automotive-solutions\/automated-driving\/hd-map-roaddna\/"},{"key":"e_1_3_2_201_2","first-page":"218","volume-title":"ICEIS 2002, Proceedings of the 4th International Conference on Enterprise Information Systems","author":"Trajcevski Goce","year":"2002","unstructured":"Goce Trajcevski, Ouri Wolfson, Hu Cao, Hai Lin, Fengli Zhang, and Naphtali Rishe. 2002. Managing uncertain trajectories of moving objects with Domino. In ICEIS 2002, Proceedings of the 4th International Conference on Enterprise Information Systems. 218\u2013225."},{"key":"e_1_3_2_202_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-60934-8_20"},{"issue":"3","key":"e_1_3_2_203_2","first-page":"7","article-title":"A comparison of great circle, great ellipse, and geodesic sailing","volume":"21","author":"Tseng Wei-Kuo","year":"2013","unstructured":"Wei-Kuo Tseng, Jiunn-Liang Guo, and Chung-Ping Liu. 2013. A comparison of great circle, great ellipse, and geodesic sailing. Journal of Marine Science and Technology 21, 3 (2013), 7.","journal-title":"Journal of Marine Science and Technology"},{"key":"e_1_3_2_204_2","article-title":"HD Maps: New age maps powering autonomous vehicles","author":"Vardhan Harsha","year":"2017","unstructured":"Harsha Vardhan. 2017. HD Maps: New age maps powering autonomous vehicles. https:\/\/www.geospatialworld.net\/article\/hd-maps-autonomous-vehicles\/ (2017).","journal-title":"https:\/\/www.geospatialworld.net\/article\/hd-maps-autonomous-vehicles\/"},{"key":"e_1_3_2_205_2","first-page":"178","volume-title":"International Conference on Operations Excellence and Service Engineering","author":"Varghese Jaycil Z.","year":"2015","unstructured":"Jaycil Z. Varghese, Randy G. Boone, et\u00a0al. 2015. Overview of autonomous vehicle sensors and systems. In International Conference on Operations Excellence and Service Engineering. sn, 178\u2013191."},{"key":"e_1_3_2_206_2","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2301.10673"},{"key":"e_1_3_2_207_2","doi-asserted-by":"publisher","DOI":"10.1179\/sre.1975.23.176.88"},{"key":"e_1_3_2_208_2","doi-asserted-by":"publisher","DOI":"10.3390\/s19092093"},{"key":"e_1_3_2_209_2","doi-asserted-by":"publisher","DOI":"10.15199\/48.2015.12.08"},{"key":"e_1_3_2_210_2","article-title":"Stuck in traffic?","author":"Wang David","year":"2007","unstructured":"David Wang. 2007. Stuck in traffic? https:\/\/googleblog.blogspot.com\/2007\/02\/stuck-in-traffic.html (2007).","journal-title":"https:\/\/googleblog.blogspot.com\/2007\/02\/stuck-in-traffic.html"},{"key":"e_1_3_2_211_2","doi-asserted-by":"publisher","DOI":"10.3390\/mi11050456"},{"key":"e_1_3_2_212_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-012-0250-5"},{"key":"e_1_3_2_213_2","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2005.1505116"},{"key":"e_1_3_2_214_2","doi-asserted-by":"publisher","DOI":"10.1109\/RCAR.2018.8621688"},{"key":"e_1_3_2_215_2","doi-asserted-by":"publisher","DOI":"10.1109\/IRC.2019.00040"},{"key":"e_1_3_2_216_2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2014.6942558"},{"key":"e_1_3_2_217_2","doi-asserted-by":"publisher","DOI":"10.1029\/94WR01971"},{"key":"e_1_3_2_218_2","article-title":"HD maps\u2014the hidden sensors that help autonomous vehicles see round corners","author":"World Automotive","year":"2019","unstructured":"Automotive World. 2019. HD maps\u2014the hidden sensors that help autonomous vehicles see round corners. https:\/\/www.automotiveworld.com\/articles\/hd-maps-the-hidden-sensors-that-help-autonomous-vehicles-see-rou- nd-corners\/ (2019).","journal-title":"https:\/\/www.automotiveworld.com\/articles\/hd-maps-the-hidden-sensors-that-help-autonomous-vehicles-see-rou- nd-corners\/"},{"key":"e_1_3_2_219_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8462926"},{"key":"e_1_3_2_220_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793495"},{"key":"e_1_3_2_221_2","article-title":"A survey of human-in-the-loop for machine learning","author":"Wu Xingjiao","year":"2021","unstructured":"Xingjiao Wu, Luwei Xiao, Yixuan Sun, Junhang Zhang, Tianlong Ma, and Liang He. 2021. A survey of human-in-the-loop for machine learning. arXiv preprint arXiv:2108.00941 (2021).","journal-title":"arXiv preprint arXiv:2108.00941"},{"key":"e_1_3_2_222_2","first-page":"1912","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Wu Zhirong","year":"2015","unstructured":"Zhirong Wu, Shuran Song, Aditya Khosla, Fisher Yu, Linguang Zhang, Xiaoou Tang, and Jianxiong Xiao. 2015. 3D ShapeNets: A deep representation for volumetric shapes. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1912\u20131920."},{"key":"e_1_3_2_223_2","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2018.7511063"},{"key":"e_1_3_2_224_2","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC48978.2021.9564825"},{"key":"e_1_3_2_225_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR48806.2021.9413070"},{"key":"e_1_3_2_226_2","article-title":"V2X-ViT: Vehicle-to-everything cooperative perception with vision transformer","author":"Xu Runsheng","year":"2022","unstructured":"Runsheng Xu, Hao Xiang, Zhengzhong Tu, Xin Xia, Ming-Hsuan Yang, and Jiaqi Ma. 2022. V2X-ViT: Vehicle-to-everything cooperative perception with vision transformer. arXiv preprint arXiv:2203.10638 (2022).","journal-title":"arXiv preprint arXiv:2203.10638"},{"key":"e_1_3_2_227_2","article-title":"OPV2V: An open benchmark dataset and fusion pipeline for perception with vehicle-to-vehicle communication","author":"Xu Runsheng","year":"2021","unstructured":"Runsheng Xu, Hao Xiang, Xin Xia, Xu Han, Jinlong Liu, and Jiaqi Ma. 2021. OPV2V: An open benchmark dataset and fusion pipeline for perception with vehicle-to-vehicle communication. arXiv preprint arXiv:2109.07644 (2021).","journal-title":"arXiv preprint arXiv:2109.07644"},{"key":"e_1_3_2_228_2","doi-asserted-by":"publisher","DOI":"10.1109\/70.466602"},{"key":"e_1_3_2_229_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.optlastec.2015.09.017"},{"key":"e_1_3_2_230_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00798"},{"key":"e_1_3_2_231_2","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2019.1900120"},{"key":"e_1_3_2_232_2","doi-asserted-by":"publisher","DOI":"10.1145\/2522968.2522970"},{"key":"e_1_3_2_233_2","doi-asserted-by":"publisher","DOI":"10.3390\/s21062140"},{"key":"e_1_3_2_234_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00502-018-0635-2"},{"issue":"5","key":"e_1_3_2_235_2","first-page":"6","article-title":"Bdd100k: A diverse driving video database with scalable annotation tooling","volume":"2","author":"Yu Fisher","year":"2018","unstructured":"Fisher Yu, Wenqi Xian, Yingying Chen, Fangchen Liu, Mike Liao, Vashisht Madhavan, and Trevor Darrell. 2018. Bdd100k: A diverse driving video database with scalable annotation tooling. arXiv preprint arXiv:1805.04687 2, 5 (2018), 6.","journal-title":"arXiv preprint arXiv:1805.04687"},{"key":"e_1_3_2_236_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cag.2021.07.003"},{"key":"e_1_3_2_237_2","doi-asserted-by":"publisher","DOI":"10.1145\/2835022.2835024"},{"key":"e_1_3_2_238_2","doi-asserted-by":"publisher","DOI":"10.1145\/3231541.3231546"},{"key":"e_1_3_2_239_2","doi-asserted-by":"publisher","DOI":"10.1145\/3149092.3149094"},{"key":"e_1_3_2_240_2","doi-asserted-by":"publisher","DOI":"10.1145\/3347146.3359353"},{"key":"e_1_3_2_241_2","doi-asserted-by":"publisher","DOI":"10.1145\/3149092.3149093"},{"key":"e_1_3_2_242_2","doi-asserted-by":"publisher","DOI":"10.1109\/MDM55031.2022.00029"},{"key":"e_1_3_2_243_2","doi-asserted-by":"publisher","DOI":"10.1109\/MVT.2019.2892497"},{"key":"e_1_3_2_244_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/271"},{"key":"e_1_3_2_245_2","article-title":"Hierarchical road topology learning for urban map-less driving","author":"Zhang Li","year":"2021","unstructured":"Li Zhang, Faezeh Tafazzoli, Gunther Krehl, Runsheng Xu, Timo Rehfeld, Manuel Schier, and Arunava Seal. 2021. Hierarchical road topology learning for urban map-less driving. arXiv preprint arXiv:2104.00084 (2021).","journal-title":"arXiv preprint arXiv:2104.00084"},{"key":"e_1_3_2_246_2","doi-asserted-by":"publisher","DOI":"10.1109\/BigDataService.2017.42"},{"key":"e_1_3_2_247_2","article-title":"Deep learning in lane marking detection: A survey","author":"Zhang Youcheng","year":"2021","unstructured":"Youcheng Zhang, Zongqing Lu, Xuechen Zhang, Jing-Hao Xue, and Qingmin Liao. 2021. Deep learning in lane marking detection: A survey. IEEE Transactions on Intelligent Transportation Systems (2021).","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"key":"e_1_3_2_248_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCIS.2017.8274856"},{"key":"e_1_3_2_249_2","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2766768"}],"container-title":["ACM Transactions on Spatial Algorithms and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627160","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3627160","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:45:39Z","timestamp":1750178739000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3627160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,15]]},"references-count":248,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,3,31]]}},"alternative-id":["10.1145\/3627160"],"URL":"https:\/\/doi.org\/10.1145\/3627160","relation":{},"ISSN":["2374-0353","2374-0361"],"issn-type":[{"value":"2374-0353","type":"print"},{"value":"2374-0361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,15]]},"assertion":[{"value":"2022-07-25","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-10-03","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-01-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}