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http://dx.doi.org/10.22640/lxsiri.2021.51.1.39

A Study on Data Model Conversion Method for the Application of Autonomous Driving of Various Kinds of HD Map  

Lee, Min-Hee (Department of Computer Engineering, Daejeon University)
Jang, In-Sung (Urban and Spatial ICT Research Laboratory, ETRI)
Kim, Min-Soo (Department of Computer Engineering, Daejeon University)
Publication Information
Journal of Cadastre & Land InformatiX / v.51, no.1, 2021 , pp. 39-51 More about this Journal
Abstract
Recently, there has been much interest in practical use of standardized HD map that can effectively define roads, lanes, junctions, road signs, and road facilities in autonomous driving. Various kinds of de jure or de facto standards such as ISO 22726-1, ISO 14296, HERE HD Live map, NDS open lane model, OpenDRIVE, and NGII HD map are currently being used. However, there are lots of differences in data modeling among these standards, it makes difficult to use them together in autonomous driving. Therefore, we propose a data model conversion method to enable an efficient use of various kinds of HD map standards in autonomous driving in this study. Specifically, we propose a conversion method between the NGII HD map model, which is easily accessible in the country, and the OpenDRIVE model, which is commonly used in the autonomous driving industry. The proposed method consists of simple conversion of NGII HD map layers into OpenDRIVE objects, new OpenDRIVE objects creation corresponding to NGII HD map layers, and linear transformation of NGII HD map layers for OpenDRIVE objects creation. Finally, we converted some test data of NGII HD map into OpenDRIVE objects, and checked the conversion results through Carla simulator. We expect that the proposed method will greatly contribute to improving the use of NGII HD map in autonomous driving.
Keywords
Autonomous Driving; High Definition Map; Road Data Model; Data Conversion;
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