2 citations · 3 across the 8 of their papers we have counts for
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Real-World Perturbation Testing of Autonomous Driving Systems
Stefano Carlo Lambertenghi, Matthias Weil, Andrea Stocco
Autonomous Driving Systems (ADS) must operate reliably under diverse conditions, yet representative data for rare or adverse scenarios is difficult to obtain. Perturbation-based te…
Cam2Sim: Neural Scenario Reconstruction for Closed-Loop Autonomous Driving Simulation
Davide Jannussi, Stefano Carlo Lambertenghi, Constantin Carste +1
Simulation-based testing enables safe and repeatable evaluation of autonomous driving systems, but its effectiveness is limited by the gap between synthetic simulator outputs and r…
PerturbationDrive: A Framework for Perturbation-Based Testing of ADAS
Hannes Leonhard, Stefano Carlo Lambertenghi, Andrea Stocco
Advanced driver assistance systems (ADAS) often rely on deep neural networks to interpret driving images and support vehicle control. Although reliable under nominal conditions, th…