98 citations · 162 across the 12 of their papers we have counts for
17 papers
Cooperative Automated Driving for Bottleneck Scenarios in Mixed Traffic
M. V. Baumann, J. Beyerer, H. S. Buck +10
Connected automated vehicles (CAV), which incorporate vehicle-to-vehicle (V2V) communication into their motion planning, are expected to provide a wide range of benefits for indivi…
LDFA: Latent Diffusion Face Anonymization for Self-driving Applications
Marvin Klemp, Kevin Rösch, Royden Wagner +2
In order to protect vulnerable road users (VRUs), such as pedestrians or cyclists, it is essential that intelligent transportation systems (ITS) accurately identify them. Therefore…
High-level Decisions from a Safe Maneuver Catalog with Reinforcement Learning for Safe and Cooperative Automated Merging
Danial Kamran, Yu Ren, Martin Lauer
Reinforcement learning (RL) has recently been used for solving challenging decision-making problems in the context of automated driving. However, one of the main drawbacks of the p…
Efficient Sampling in POMDPs with Lipschitz Bandits for Motion Planning in Continuous Spaces
Ömer Şahin Taş, Felix Hauser, Martin Lauer
Decision making under uncertainty can be framed as a partially observable Markov decision process (POMDP). Finding exact solutions of POMDPs is generally computationally intractabl…
Fast Lane-Level Intersection Estimation using Markov Chain Monte Carlo Sampling and B-Spline Refinement
Annika Meyer, Jonas Walter, Martin Lauer
Estimating the current scene and understanding the potential maneuvers are essential capabilities of automated vehicles. Most approaches rely heavily on the correctness of maps, bu…
Risk-Aware High-level Decisions for Automated Driving at Occluded Intersections with Reinforcement Learning
Danial Kamran, Carlos Fernandez Lopez, Martin Lauer +1
Reinforcement learning is nowadays a popular framework for solving different decision making problems in automated driving. However, there are still some remaining crucial challeng…