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Case Study on Gap Selection for Automated Vehicles Based on Deep Q-Learning

Nichting, Matthias and Lobig, Thomas and Köster, Frank (2021) Case Study on Gap Selection for Automated Vehicles Based on Deep Q-Learning. In: 2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST). 2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST), 29.-30. Jun. 2021, Yogyakarta, Indonesia. doi: 10.1109/ICAICST53116.2021.9497818.

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Item URL in elib:https://elib.dlr.de/142783/
Document Type:Conference or Workshop Item (Speech)
Title:Case Study on Gap Selection for Automated Vehicles Based on Deep Q-Learning
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Nichting, MatthiasMatthias.Nichting (at) dlr.dehttps://orcid.org/0000-0002-2484-4203
Lobig, ThomasThomas.Lobig (at) dlr.deUNSPECIFIED
Köster, FrankFrank.Koester (at) dlr.deUNSPECIFIED
Date:2021
Journal or Publication Title:2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST)
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI :10.1109/ICAICST53116.2021.9497818
Status:Published
Keywords:deep q-learning, gap selection, decision making
Event Title:2021 International Conference on Artificial Intelligence and Computer Science Technology (ICAICST)
Event Location:Yogyakarta, Indonesia
Event Type:international Conference
Event Dates:29.-30. Jun. 2021
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
Location: Berlin-Adlershof
Institutes and Institutions:Institute of Transportation Systems
Institute of Transportation Systems > Cooperative Systems, BA
Institute for AI Safety and Security
Deposited By: Nichting, Matthias
Deposited On:14 Dec 2021 09:41
Last Modified:14 Dec 2021 09:41

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