9 citations · 9 across the 4 of their papers we have counts for
4 papers · 1 filter
A Causal Probabilistic Framework for Perception-Informed Closed-Loop Simulation of Autonomous Driving
Zhennan Fei, Rickard Johansson, Mikael Andersson +12
Software-in-the-loop (SIL) simulation is a cornerstone for the validation of modern automotive safety functions. However, many current frameworks utilize ideal sensing, which bypas…
What Did I Learn? Operational Competence Assessment for AI-Based Trajectory Planners
Michiel Braat, Maren Buermann, Marijke van Weperen +1
Automated driving functions increasingly rely on machine learning for tasks like perception and trajectory planning, requiring large, relevant datasets. The performance of these al…
Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems
Erwin de Gelder, Maren Buermann, Olaf Op den Camp
The development of safety validation methods is essential for the safe deployment and operation of Automated Driving Systems (ADSs). One of the goals of safety validation is to pro…
Coverage Metrics for a Scenario Database for the Scenario-Based Assessment of Automated Driving Systems
Erwin de Gelder, Maren Buermann, Olaf Op den Camp
Automated Driving Systems (ADSs) have the potential to make mobility services available and safe for all. A multi-pillar Safety Assessment Framework (SAF) has been proposed for the…