A flexibly linkable meta layer of geographic features supplementary for driving automation and simulation

Rüdiger Ebendt

A flexibly linkable meta layer of geographic features supplementary for driving automation and simulation

Authors: Rüdiger Ebendt
Keywords: driving automation, driving simulation, data model, geographic feature, meta layer
Abstract:

Ebendt R. A flexibly linkable meta layer of geographic features supplementary for driving automation and simulation In: Proceedings of the Driving Simulation Conference 2020 Europe VR, Driving Simulation Association, Antibes, France, 2020, pp. 19-26

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@inproceedings{Ebendt2020,
title = {A flexibly linkable meta layer of geographic features supplementary for driving automation and simulation},
author = {Rüdiger Ebendt},
editor = {Andras Kemeny and Jean-Rémy Chardonnet and Florent Colombet},
year  = {2020},
date = {2020-09-09},
booktitle = {Proceedings of the Driving Simulation Conference 2020 Europe VR},
pages = {19-26},
address = {Antibes, France},
organization = {Driving Simulation Association},
abstract = {In this paper, a data model named “Road2Automation” is introduced, aiming at supplementing road information in today’s digital road maps with (georeferenced) features which are relevant to driving automation and driving simulation. It addresses maps of diverse levels of detail, precision and format (ranging from High Definition (HD) maps to crowd-sourced data from OpenStreetMap (OSM)), and facilitates transfer of the features between maps. To this end, each feature is annotated by a logical link to its source map and by map-agnostic OpenLRreferences. Runtime modules for location referencing like OpenLR and a map-independent geometrical inter-map matching algorithm are needed which match georeferenced features between an arbitrary pair of source and target map. In effect, a meta layer on top of all source and target maps is realized. The meta layer addresses use cases ranging from localization, global path planning, driving simulation, and safety of autonomous transport to route planning and navigation. The model has an extendible design where new, arbitrarily complex composite keys for the logical links can be added. Existing keys or components of existing composite keys are reused, whenever new keys are constructed. On the persistence layer, this keeps the number of required database columns small.},
keywords = {data model, driving automation, driving simulation, geographic feature, meta layer},
}

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TY  - CONF
TI  - A flexibly linkable meta layer of geographic features supplementary for driving automation and simulation
AU  - Ebendt, Rüdiger
C1  - Antibes, France
C3  - Proceedings of the Driving Simulation Conference 2020 Europe VR
DA  - 2020/09/09
PY  - 2020
SP  - 19
EP  - 26
LA  - en-US
PB  - Driving Simulation Association
L2  - https://proceedings.driving-simulation.org/proceeding/dsc-2020/a-flexibly-linkable-meta-layer-of-geographic-features-supplementary-for-driving-automation-and-simulation
ER  -

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