Autonomous driving systems have witnessed significant development during the past years
thanks to the advance in machine learning-enabled sensing and decision-making …

Simulation is an integral part in the process of developing autonomous vehicles and
advantageous for training, validation, and verification of driving functions. Even though …

We introduce a novel notion of perception contracts to reason about the safety of controllers
that interact with an environment using neural perception. Perception contracts capture …

Autonomous systems emerge from the need to progressively replace human operators by
autonomous agents in a wide variety of application areas. We offer an analysis of the state of …

Ensuring that AI systems reliably and robustly avoid harmful or dangerous behaviours is a
crucial challenge, especially for AI systems with a high degree of autonomy and general …

Abstract We present ChatScene a Large Language Model (LLM)-based agent that
leverages the capabilities of LLMs to generate safety-critical scenarios for autonomous …

Validation and Verification (V&V) of Artificial Intelligence (AI) based cyber physical systems
such as Autonomous Vehicles (AVs) is currently a vexing and unsolved problem. AVs …

We present an exact Bayesian inference method for inferring posterior distributions encoded
by probabilistic programs featuring possibly unbounded loops. Our method is built on a …

This paper summarizes our formal approach to testing autonomous vehicles (AVs) in
simulation for the IEEE AV Test Challenge. We demonstrate a systematic testing framework …

Nowadays, closed-set perception methods for autonomous driving perform well on datasets
containing normal scenes. However, they still struggle to handle anomalies in the real world …