Klitzke, Lars und Gimm, Kay und Koch, Carsten und Köster, Frank (2022) Extraction and Analysis of Highway On-Ramp Merging Scenarios from Naturalistic Trajectory Data. In: 25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022. IEEE International Conference on Intelligent Transportation Systems, 2022-10-08 - 2022-10-12, Macau, China. doi: 10.1109/ITSC55140.2022.9922191. ISBN 978-1-6654-6880-0. ISSN 2153-0009.
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Kurzfassung
Connected and Automated Vehicles (CAVs) are envisioned to transform the future industrial and private transportation sectors. However, due to the system's enormous complexity, functional verification and validation of safety aspects are essential before the technology merges into the public domain. Therefore, in recent years, a scenario-driven approach has gained acceptance, emphasizing the requirement of a solid data basis of scenarios. The large-scale research facility Test Bed Lower Saxony (TFNDS) enables the provision of ample information for a database of scenarios on highways. For that purpose, however, the scenarios of interest must be identified and extracted from the collected Naturalistic Trajectory Data (NTD). This work addresses this problem and proposes a methodology for onramp scenario extraction, enabling scenario categorization and assessment. An Hidden Markov Model (HMM) and Dynamic Time Warping (DTW) is utilized for extraction and a decision tree with the Surrogate Measure of Safety (SMoS) Post Enroachment Time (PET) for categorization and assessment. The efficacy of the approach is shown with a dataset of NTD collected on the TFNDS
elib-URL des Eintrags: | https://elib.dlr.de/186929/ | ||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||
Titel: | Extraction and Analysis of Highway On-Ramp Merging Scenarios from Naturalistic Trajectory Data | ||||||||||||||||||||
Autoren: |
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Datum: | 2022 | ||||||||||||||||||||
Erschienen in: | 25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022 | ||||||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||
In ISI Web of Science: | Ja | ||||||||||||||||||||
DOI: | 10.1109/ITSC55140.2022.9922191 | ||||||||||||||||||||
ISSN: | 2153-0009 | ||||||||||||||||||||
ISBN: | 978-1-6654-6880-0 | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | Highway On-Ramp Merging, Naturalistic Trajectory Data, Scenario Extraction, Connected and Automated Vehicles | ||||||||||||||||||||
Veranstaltungstitel: | IEEE International Conference on Intelligent Transportation Systems | ||||||||||||||||||||
Veranstaltungsort: | Macau, China | ||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||
Veranstaltungsbeginn: | 8 Oktober 2022 | ||||||||||||||||||||
Veranstaltungsende: | 12 Oktober 2022 | ||||||||||||||||||||
Veranstalter : | IEEE | ||||||||||||||||||||
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 - NGC KoFiF (alt) | ||||||||||||||||||||
Standort: | Braunschweig | ||||||||||||||||||||
Institute & Einrichtungen: | Institut für Verkehrssystemtechnik > Informationsgewinnung und Modellierung, BS Institut für KI-Sicherheit | ||||||||||||||||||||
Hinterlegt von: | Klitzke, Lars | ||||||||||||||||||||
Hinterlegt am: | 20 Jun 2022 11:06 | ||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:48 |
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