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ISPRS Int. J. Geo-Inf. 2018, 7(12), 458;

Towards HD Maps from Aerial Imagery: Robust Lane Marking Segmentation Using Country-Scale Imagery

AUDI AG, 85045 Ingolstadt, Germany
German Aerospace Center, 82234 Oberpfaffenhofen, Germany
Bavarian Agency for Digitisation, High Speed Internet and Surveying, 80538 Munich, Germany
Author to whom correspondence should be addressed.
Received: 7 October 2018 / Revised: 15 November 2018 / Accepted: 22 November 2018 / Published: 26 November 2018
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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. View Full-Text
Keywords: autonomous driving; HD maps; aerial imagery autonomous driving; HD maps; aerial imagery

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Fischer, P.; Azimi, S.M.; Roschlaub, R.; Krauß, T. Towards HD Maps from Aerial Imagery: Robust Lane Marking Segmentation Using Country-Scale Imagery. ISPRS Int. J. Geo-Inf. 2018, 7, 458.

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