… the state-of-the-art V&V software for autonomous vehicles, particularly addressing the
challenges posed by leveraging artificial intelligence (AI) and machine learning (ML) for safe …

… or safety monitors, creating a major complication for safety … focused on automated driving,
where machine learning is … of a standard vehicle architecture, where a machine learning-…

… The open-world deployment of Machine Learning (ML) algorithms in safety-critical applications
such as autonomous vehicles needs to address a variety of ML vulnerabilities such as …

… presents a safe reinforcement learning system for automated driving that … a safety system
that consists of two safety components: a rule-based and a multimodal learning-based safety …

… YOLOv3 is mostly used as an object detection technique based on deep learning. K-means …
the automated vehicles running on efficient and safe roads are just around the corner. …

… However, ensuring state safety is vital for autonomous vehicles. Therefore, this paper … safety
enhancement method for autonomous driving via direct hierarchical reinforcement learning. …

… designing AI architectures for autonomous driving, such as their safety, training data sources…
of deep learning and AI approaches for autonomous driving and assist with design choices. …

… safety assessments. This paper reviews the state-of-the-art in verification and validation of
safety-critical systems that rely on machine learning… Now, in the advent of autonomous driving, …

… analysis for machine learning algorithms which can be used in smart/autonomous vehicles
to … of unpredictable behaviours of machine learning algorithms and hardware components is …

… it can be solved using reinforcement learning. Failures can also … [17] or represent a
reinforcement learning policy [18]. Simple … discovery [20] and as a reinforcement learning policy …