1 citations · 1 across the 3 of their papers we have counts for
3 papers
Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making
M. Youssef Abdelhamid, Lennart Vater, Zlatan Ajanovic
Developing decision-making algorithms for highly automated driving systems remains challenging, since these systems have to operate safely in an open and complex environments. Rein…
Determining the Tactical Challenge of Scenarios to Efficiently Test Automated Driving Systems
Lennart Vater, Sven Tarlowski, Michael Schuldes +1
The selection of relevant test scenarios for the scenario-based testing and safety validation of automated driving systems (ADSs) remains challenging. An important aspect of the re…
The inD Dataset: A Drone Dataset of Naturalistic Road User Trajectories at German Intersections
Julian Bock, Robert Krajewski, Tobias Moers +3
Automated vehicles rely heavily on data-driven methods, especially for complex urban environments. Large datasets of real world measurement data in the form of road user trajectori…