Irizar Da Silva, Imanol und Zhang, Meng und Gimm, Kay (2023) A collaborative framework for semi-automatic scenario-based mining of big road user data. IEEE-ITSC 2023 Bilbao, 2023-09-24 - 2023-09-28, Bilbao, Spanien. (im Druck)
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Kurzfassung
Traffic research has benefited from a significant expansion in the amount of available data. Consequently, the need arises for an automatic and efficient method to extract and analyze relevant traffic situations instead of a more traditional and manual approach like manual video annotation. This paper presents a framework to create such a data pipeline. The user must define the target scenarios and the pipeline will abstract the available trajectory data into candidate scenes (groups of interacting trajectories) and select the matches for the target scenarios. These scenes will be mined and modelled automatically for new valuable information. Furthermore, Surrogate Measures of Safety (SMoS) are applied to identify the critical and atypical scenes of the target scenarios. A set of eight scenarios containing interactions between bicycles and MRUs (Motorized Road Users) at the AIM (Application Platform for Intelligent Mobility) Research Intersection in the city of Braunschweig, Germany, was mined by a team of three researchers using the presented framework to validate it with positive results.
elib-URL des Eintrags: | https://elib.dlr.de/200723/ | ||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||
Titel: | A collaborative framework for semi-automatic scenario-based mining of big road user data | ||||||||||||||||
Autoren: |
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Datum: | 28 Mai 2023 | ||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||
Open Access: | Ja | ||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||
Status: | im Druck | ||||||||||||||||
Stichwörter: | Scenario Mining, Naturalistic Driving Data, Collaborative Data Mining, Map Matching, Interactions, Modelling, Criticality Detection, Anomaly | ||||||||||||||||
Veranstaltungstitel: | IEEE-ITSC 2023 Bilbao | ||||||||||||||||
Veranstaltungsort: | Bilbao, Spanien | ||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||
Veranstaltungsbeginn: | 24 September 2023 | ||||||||||||||||
Veranstaltungsende: | 28 September 2023 | ||||||||||||||||
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 - KoKoVI - Koordinierter kooperativer Verkehr mit verteilter, lernender Intelligenz | ||||||||||||||||
Standort: | Berlin-Adlershof , Braunschweig | ||||||||||||||||
Institute & Einrichtungen: | Institut für Verkehrssystemtechnik > Informationsgewinnung und Modellierung, BS Institut für Verkehrssystemtechnik > Informationsgewinnung und Modellierung, BA | ||||||||||||||||
Hinterlegt von: | Irizar Da Silva, Imanol | ||||||||||||||||
Hinterlegt am: | 11 Dez 2023 12:35 | ||||||||||||||||
Letzte Änderung: | 24 Apr 2024 21:01 |
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