Lanelet2: A high-definition map framework for the future of automated driving

Although accurate and comprehensive maps are indispensable for highly automated driving, especially in complex urban scenarios, there are hardly any publications in which requirements for these maps are discussed. In our opinion, such maps must meet high demands in terms of accuracy, completeness, v...

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Bibliographic Details
Published in:Proceedings (IEEE Conference on Intelligent Transportation Systems) pp. 1672 - 1679
Main Authors: Poggenhans, Fabian, Pauls, Jan-Hendrik, Janosovits, Johannes, Orf, Stefan, Naumann, Maximilian, Kuhnt, Florian, Mayr, Matthias
Format: Conference Proceeding
Language:English
Published: IEEE 01.11.2018
Subjects:
Complexity theory
Planning
Roads
Routing
Sensors
Software
Urban areas
ISBN:9781728103211, 1728103215
ISSN:2153-0017
Online Access:Get full text
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Summary:Although accurate and comprehensive maps are indispensable for highly automated driving, especially in complex urban scenarios, there are hardly any publications in which requirements for these maps are discussed. In our opinion, such maps must meet high demands in terms of accuracy, completeness, verifiability and extensibility, so that the resulting complexity can only be handled by an enclosing, carefully designed software framework. In this paper we therefore introduce the open-source map framework Lanelet2 implemented in C++ and explain the underlying concept. The goal of Lanelet2 is not only to be usable for typical, isolated applications such as localization or motion planning, but for various potential applications of maps for highly automated driving. On the basis of both abstract and real examples we show the concrete structure of Lanelet2 maps and its use for automated driving.
ISBN:9781728103211
1728103215
ISSN:2153-0017
DOI:10.1109/ITSC.2018.8569929