51 citations · 86 across the 4 of their papers we have counts for
6 papers
CARLA Real Traffic Scenarios -- novel training ground and benchmark for autonomous driving
Błażej Osiński, Piotr Miłoś, Adam Jakubowski +6
This work introduces interactive traffic scenarios in the CARLA simulator, which are based on real-world traffic. We concentrate on tactical tasks lasting several seconds, which ar…
openDD: A Large-Scale Roundabout Drone Dataset
Antonia Breuer, Jan-Aike Termöhlen, Silviu Homoceanu +1
Analyzing and predicting the traffic scene around the ego vehicle has been one of the key challenges in autonomous driving. Datasets including the trajectories of all road users pr…
Planning on the fast lane: Learning to interact using attention mechanisms in path integral inverse reinforcement learning
Sascha Rosbach, Xing Li, Simon Großjohann +2
General-purpose trajectory planning algorithms for automated driving utilize complex reward functions to perform a combined optimization of strategic, behavioral, and kinematic fea…
Driving Style Encoder: Situational Reward Adaptation for General-Purpose Planning in Automated Driving
Sascha Rosbach, Vinit James, Simon Großjohann +3
General-purpose planning algorithms for automated driving combine mission, behavior, and local motion planning. Such planning algorithms map features of the environment and driving…
Simulation-based reinforcement learning for real-world autonomous driving
Błażej Osiński, Adam Jakubowski, Piotr Miłoś +4
We use reinforcement learning in simulation to obtain a driving system controlling a full-size real-world vehicle. The driving policy takes RGB images from a single camera and thei…
Driving with Style: Inverse Reinforcement Learning in General-Purpose Planning for Automated Driving
Sascha Rosbach, Vinit James, Simon Großjohann +2
Behavior and motion planning play an important role in automated driving. Traditionally, behavior planners instruct local motion planners with predefined behaviors. Due to the high…