33 citations · 36 across the 5 of their papers we have counts for
6 papers
Safety Assessment of Vehicle Characteristics Variations in Autonomous Driving Systems
Qi Pan, Tiexin Wang, Paolo Arcaini +2
Autonomous driving systems (ADSs) must be sufficiently tested to ensure their safety. Though various ADS testing methods have shown promising results, they are limited to a fixed s…
Does Road Diversity Really Matter in Testing Automated Driving Systems? -- A Registered Report
Stefan Klikovits, Vincenzo Riccio, Ezequiel Castellano +3
Background/Context. The use of automated driving systems (ADSs) in the real world requires rigorous testing to ensure safety. To increase trust, ADSs should be tested on a large se…
QuSBT: Search-Based Testing of Quantum Programs
Xinyi Wang, Paolo Arcaini, Tao Yue +1
Generating a test suite for a quantum program such that it has the maximum number of failing tests is an optimization problem. For such optimization, search-based testing has shown…
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…