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A Simulation-Based Reinforcement Learning Approach for Long-Term Maneuver Planning in Highway Traffic Scenarios

Augustin, David ; Schucker, Jeremias ; Tschirner, Jeremy ; Hofmann, Marius ; Konigorski, Ulrich (2019):
A Simulation-Based Reinforcement Learning Approach for Long-Term Maneuver Planning in Highway Traffic Scenarios.
VDI-Berichte 2349, pp. 47-60, Mannheim, Germany, VDI/VDE-Fachtatung AUTOREG 2019: Regelungstechnik für autonomes Fahren und vernetzte Mobilität, Mannheim, Germany, 02-03.07.2019, ISSN 00835560,
[Conference or Workshop Item]

Item Type: Conference or Workshop Item
Erschienen: 2019
Creators: Augustin, David ; Schucker, Jeremias ; Tschirner, Jeremy ; Hofmann, Marius ; Konigorski, Ulrich
Title: A Simulation-Based Reinforcement Learning Approach for Long-Term Maneuver Planning in Highway Traffic Scenarios
Language: English
Volume: VDI-Berichte 2349
Place of Publication: Mannheim, Germany
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Systems and Mechatronics
Event Title: VDI/VDE-Fachtatung AUTOREG 2019: Regelungstechnik für autonomes Fahren und vernetzte Mobilität
Event Location: Mannheim, Germany
Event Dates: 02-03.07.2019
Date Deposited: 19 Aug 2019 08:46
Official URL: https://www.researchgate.net/publication/334745733_A_Simulat...
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