1 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
Handling Noise in Search-Based Scenario Generation for Autonomous Driving Systems
Stefan Klikovits, Paolo Arcaini
This paper presents the first evaluation of k-nearest neighbours-Averaging (kNN-Avg) on a real-world case study. kNN-Avg is a novel technique that tackles the challenges of noisy m…
On the Need for Multi-Level ADS Scenarios
Stefan Klikovits, Paolo Arcaini
Currently, most existing approaches for the design of Automated Driving System (ADS) scenarios focus on the description at one particular abstraction level typically the most detai…
KNN-Averaging for Noisy Multi-objective Optimisation
Stefan Klikovits, Paolo Arcaini
Multi-objective optimisation is a popular approach for finding solutions to complex problems with large search spaces that reliably yields good optimisation results. However, with…
Architecture-Guided Test Resource Allocation Via Logic
Clovis Eberhart, Akihisa Yamada, Stefan Klikovits +4
We introduce a new logic named Quantitative Confidence Logic (QCL) that quantifies the level of confidence one has in the conclusion of a proof. By translating a fault tree represe…