Rösch, Kevin und Heidecker, Florian und Truetsch, Julian und Kowol, Kamil und Schicktanz, Clemens und Bieshaar, Maarten und Sick, Bernhard und Stiller, Christoph (2022) Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving. In: 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022. IEEE SSCI 2022, 2022-12-05 - 2022-12-07, Singapur. doi: 10.1109/SSCI51031.2022.10022241. ISBN 978-166548768-9.
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Kurzfassung
Trajectory data analysis is an essential component for highly automated driving. Complex models developed with these data predict other road users' movement and behavior patterns. Based on these predictions — and additional contextual information such as the course of the road, (traffic) rules, and interaction with other road users — the highly automated vehicle (HAV) must be able to reliably and safely perform the task assigned to it, e.g., moving from point A to B. Ideally, the HAV moves safely through its environment, just as we would expect a human driver to do. However, if unusual trajectories occur, so-called trajectory corner cases, a human driver can usually cope well, but an HAV can quickly get into trouble. In the definition of trajectory corner cases, which we provide in this work, we will consider the relevance of unusual trajectories with respect to the task at hand. Based on this, we will also present a taxonomy of different trajectory corner cases. The categorization of corner cases into the taxonomy will be shown with examples and is done by cause and required data sources. To illustrate the complexity between the machine learning (ML) model and the corner case cause, we present a general processing chain underlying the taxonomy.
elib-URL des Eintrags: | https://elib.dlr.de/188337/ | ||||||||||||||||||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||||||||||||||||||
Titel: | Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving | ||||||||||||||||||||||||||||||||||||
Autoren: |
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Datum: | 2022 | ||||||||||||||||||||||||||||||||||||
Erschienen in: | 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 | ||||||||||||||||||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||||||||||||||||||
DOI: | 10.1109/SSCI51031.2022.10022241 | ||||||||||||||||||||||||||||||||||||
ISBN: | 978-166548768-9 | ||||||||||||||||||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||||||||||||||||||
Stichwörter: | taxonomy, corner case, trajectory data | ||||||||||||||||||||||||||||||||||||
Veranstaltungstitel: | IEEE SSCI 2022 | ||||||||||||||||||||||||||||||||||||
Veranstaltungsort: | Singapur | ||||||||||||||||||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||||||||||||||||||
Veranstaltungsbeginn: | 5 Dezember 2022 | ||||||||||||||||||||||||||||||||||||
Veranstaltungsende: | 7 Dezember 2022 | ||||||||||||||||||||||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||||||||||||||||||||||
HGF - Programm: | Verkehr | ||||||||||||||||||||||||||||||||||||
HGF - Programmthema: | Straßenverkehr | ||||||||||||||||||||||||||||||||||||
DLR - Schwerpunkt: | Verkehr | ||||||||||||||||||||||||||||||||||||
DLR - Forschungsgebiet: | V ST Straßenverkehr | ||||||||||||||||||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | V - V&V4NGC - Methoden, Prozesse und Werkzeugketten für die Validierung & Verifikation von NGC | ||||||||||||||||||||||||||||||||||||
Standort: | Berlin-Adlershof | ||||||||||||||||||||||||||||||||||||
Institute & Einrichtungen: | Institut für Verkehrssystemtechnik > Informationsgewinnung und Modellierung, BA | ||||||||||||||||||||||||||||||||||||
Hinterlegt von: | Schicktanz, Clemens | ||||||||||||||||||||||||||||||||||||
Hinterlegt am: | 10 Jan 2023 13:23 | ||||||||||||||||||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:49 |
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