Ebendt, Rüdiger
(2020)
A flexibly linkable meta layer of geographic features supplementary for driving automation and simulation.
In: Driving Simulation Conference (DSC), Seiten 19-26.
19th Driving Simulation & Virtual Reality Conference & Exhibition (DSC 2020 EUROPE VR), 9.-11. Sept. 2020, Antibes, Frankreich.
Offizielle URL: https://proceedings.driving-simulation.org/proceeding/dsc-2020/a-flexibly-linkable-meta-layer-of-geographic-features-supplementary-for-driving-automation-and-simulation/
Kurzfassung
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 OpenLR references. 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.
elib-URL des Eintrags: | https://elib.dlr.de/136011/ |
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Dokumentart: | Konferenzbeitrag (Vortrag) |
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Titel: | A flexibly linkable meta layer of geographic features supplementary for driving automation and simulation |
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Autoren: | |
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Datum: | 2020 |
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Erschienen in: | Driving Simulation Conference (DSC) |
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Referierte Publikation: | Ja |
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Open Access: | Ja |
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Gold Open Access: | Nein |
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In SCOPUS: | Nein |
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In ISI Web of Science: | Nein |
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Seitenbereich: | Seiten 19-26 |
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Herausgeber: | Herausgeber | Institution und/oder E-Mail-Adresse der Herausgeber | Herausgeber-ORCID-iD | ORCID Put Code |
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Kemeny, Andras | Driving Simulation Association | NICHT SPEZIFIZIERT | NICHT SPEZIFIZIERT |
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Status: | veröffentlicht |
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Stichwörter: | driving automation, driving simulation, data model, geographic feature, meta layer |
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Veranstaltungstitel: | 19th Driving Simulation & Virtual Reality Conference & Exhibition (DSC 2020 EUROPE VR) |
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Veranstaltungsort: | Antibes, Frankreich |
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Veranstaltungsart: | internationale Konferenz |
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Veranstaltungsdatum: | 9.-11. Sept. 2020 |
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Veranstalter
: | Driving Simulation Association |
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HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr |
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HGF - Programm: | Verkehr |
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HGF - Programmthema: | Straßenverkehr |
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DLR - Schwerpunkt: | Verkehr |
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DLR - Forschungsgebiet: | V ST Straßenverkehr |
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DLR - Teilgebiet (Projekt, Vorhaben): | V - NGC KoFiF (alt) |
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Standort: |
Berlin-Adlershof
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Institute & Einrichtungen: | Institut für Verkehrssystemtechnik > Datenerfassung und Informationsgewinnung |
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Hinterlegt von: |
Ebendt, Dr.rer.nat. Rüdiger
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Hinterlegt am: | 11 Sep 2020 11:47 |
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Letzte Änderung: | 11 Sep 2020 11:47 |
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