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http://dx.doi.org/10.7848/ksgpc.2020.38.4.391

Study on Automated Error Detection Method for Enhancing High Definition Map  

Hong, Song Pyo (Spatial Information Industry Promotion Institute)
Oh, Jong Min (Department of Geoinformatics Engineering, University of Seoul, Spatial Information Industry Promotion Institute)
Song, Yong Hyun (Spatial Information Industry Promotion Institute)
Shin, Young Min (Department of Geoinformatics Engineering, University of Seoul, Spatial Information Industry Promotion Institute)
Sung, Dong Ki (Spatial Information Industry Promotion Institute)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.38, no.4, 2020 , pp. 391-399 More about this Journal
Abstract
Autonomous driving can be limited by only using sensors if the sensor is blocked by sudden changes in surrounding environments or large features such as heavy vehicles. In order to overcome the limitations, the precise road-map has been used additionally. In korea, the NGII (National Geographic Information Institute) produces and supplies high definition map for autonomous vehicles. Accordingly, in this study, errors occurring in the process of e data editing and dtructured esditing of high definition map are systematically typed providing by the National Geographic Information Institute. In addition, by presenting the error search process and solution for each situation, we conducted a study to quickly correct errors in high definition map, and largely classify the error items for shape integrity, spatial relationship, and reference relationship, and examine them in detail. The method was derived.
Keywords
Autonomous Driving; High Definition Map; Shape Integrity; Spatial Relationship; Reference Relationship;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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