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Extraction and Analysis of Highway On-Ramp Merging Scenarios from Naturalistic Trajectory Data

Klitzke, Lars and Gimm, Kay and Koch, Carsten and 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, 08. - 12. Okt. 2022, Macau, China. doi: 10.1109/ITSC55140.2022.9922191. ISBN 978-1-6654-6880-0. ISSN 2153-0009.

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Abstract

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

Item URL in elib:https://elib.dlr.de/186929/
Document Type:Conference or Workshop Item (Speech)
Title:Extraction and Analysis of Highway On-Ramp Merging Scenarios from Naturalistic Trajectory Data
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Klitzke, LarsUNSPECIFIEDhttps://orcid.org/0000-0001-9362-707XUNSPECIFIED
Gimm, KayUNSPECIFIEDhttps://orcid.org/0000-0002-5136-685X137550562
Koch, CarstenUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Köster, FrankUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:2022
Journal or Publication Title:25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI:10.1109/ITSC55140.2022.9922191
ISSN:2153-0009
ISBN:978-1-6654-6880-0
Status:Published
Keywords:Highway On-Ramp Merging, Naturalistic Trajectory Data, Scenario Extraction, Connected and Automated Vehicles
Event Title:IEEE International Conference on Intelligent Transportation Systems
Event Location:Macau, China
Event Type:international Conference
Event Dates:08. - 12. Okt. 2022
Organizer:IEEE
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - NGC KoFiF (old)
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems > Information Gathering and Modelling, BS
Institute for AI Safety and Security
Deposited By: Klitzke, Lars
Deposited On:20 Jun 2022 11:06
Last Modified:20 Nov 2023 08:10

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