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http://dx.doi.org/10.11108/kagis.2019.22.3.099

Evaluating a Positioning Accuracy of Roadside Facilities DB Constructed from Mobile Mapping System Point Cloud  

KIM, Jae-Hak (Geo-Spatial Information Planing Team, Geostory Co. Ltd.)
LEE, Hong-Sool (Geo-Spatial Information Planing Team, Geostory Co. Ltd.)
ROH, Su-Lae (Geo-Spatial Information Planing Team, Geostory Co. Ltd.)
LEE, Dong-Ha (Dept. of Civil Engineering, Kangwon National University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.22, no.3, 2019 , pp. 99-106 More about this Journal
Abstract
Technology that cannot be excluded from 4th industry is self-driving sector. The self-driving sector can be seen as a key set of technologies in the fourth industry, especially in the DB sector is getting more and more popular as a business. The DB, which was previously produced and managed in two dimensions, is now evolving into three dimensions. Among the data obtained by Mobile Mapping System () to produce the HD MAP necessary for self-driving, Point Cloud, which is LiDAR data, is used as a DB because it contains accurate location information. However, at present, it is not widely used as a base data for 3D modeling in addition to HD MAP production. In this study, MMS Point Cloud was used to extract facilities around the road and to overlay the location to expand the usability of Point Cloud. Building utility poles and communication poles DB from Point Cloud and comparing road name address base and location, it is believed that the accuracy of the location of the facility DB extracted from Point Cloud is also higher than the basic road name address of the road, It is necessary to study the expansion of the facility field sufficiently.
Keywords
3D geo-spatial model; MMS; Point Cloud; Road; Facility; Road Name Address MAP;
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