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Machine-Learning informed simulation-based dynamic traffic assignment with SUMO
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0009-0007-8372-6622
KTH, School of Architecture and the Built Environment (ABE), Civil and Architectural Engineering, Transport planning.ORCID iD: 0000-0002-2141-0389
2024 (English)Conference paper, Poster (with or without abstract) (Refereed)
Place, publisher, year, edition, pages
2024.
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:kth:diva-351185OAI: oai:DiVA.org:kth-351185DiVA, id: diva2:1886683
Conference
SUMO User Conference 2024, 13-15 May 2024, German Aerospace Center (DLR) - Institute of Transportation Systems, Berlin, Germany
Note

QC 20240815

Available from: 2024-08-02 Created: 2024-08-02 Last updated: 2024-08-15Bibliographically approved

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Jostmann, JonasFlötteröd, GunnarMa, Zhenliang
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Total: 261 hits
CiteExportLink to record
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