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

By Fabian Poggenhans, Jan-Hendrik Pauls, Johannes Janosovits, Stefan Orf, Maximilian Naumann, Florian Kuhnt, Matthias Mayr. International Conference on Intelligent Transportation Systems, 2018

312 citations recorded by the source corpus.

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.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/c8c501ba33c17c56d45ad71b76001bbc2547f92e

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In Automotive Engineering

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Citations in the corpus

The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections (2019, methodology): “The digital map is provided in the Lanelet2 Format [11] for all locations (see example in Fig.”
LGSVL Simulator: A High Fidelity Simulator for Autonomous Driving (2020, methodology): “Map tools are provided to import and export HD maps for autonomous driving in formats such as Lanelet2 [10], OpenDRIVE, and Apollo HD Map.”
INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps (2019, methodology): “Thus, in order to allow for a thorough analysis of the recorded trajectories, we provide centimeter-accurate high definition maps in the lanelet2 format [34].”