3 papers
cs.RO2022
Optimizing Trajectories for Highway Driving with Offline Reinforcement Learning
Branka Mirchevska, Moritz Werling, Joschka Boedecker
Implementing an autonomous vehicle that is able to output feasible, smooth and efficient trajectories is a long-standing challenge. Several approaches have been considered, roughly…
cs.LG2020
Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways
Branka Mirchevska, Maria Hügle, Gabriel Kalweit +2
Well-established optimization-based methods can guarantee an optimal trajectory for a short optimization horizon, typically no longer than a few seconds. As a result, choosing the…
cs.LG2019
Dynamic Input for Deep Reinforcement Learning in Autonomous Driving
Maria Hügle, Gabriel Kalweit, Branka Mirchevska +2
In many real-world decision making problems, reaching an optimal decision requires taking into account a variable number of objects around the agent. Autonomous driving is a domain…