Abstract Context: A Machine Learning based System (MLS) is a software system including
one or more components that learn how to perform a task from a given data set. The …

Scenario-based approaches have been receiving a huge amount of attention in research
and engineering of automated driving systems. Due to the complexity and uncertainty of the …

The autonomous driving community has witnessed a rapid growth in approaches that
embrace an end-to-end algorithm framework, utilizing raw sensor input to generate vehicle …

Testing autonomous driving algorithms on real autonomous vehicles is extremely costly and
many researchers and developers in the field cannot afford a real car and the corresponding …

This paper proposes AV-FUZZER, a testing framework, to find the safety violations of an
autonomous vehicle (AV) in the presence of an evolving traffic environment. We perturb the …

We present VerifAI, a software toolkit for the formal design and analysis of systems that
include artificial intelligence (AI) and machine learning (ML) components. VerifAI particularly …

Toward verified artificial intelligence Page 1 46 COMMUNICATIONS OF THE ACM | JULY
2022 | VOL. 65 | NO. 7 contributed articles ILL US TRA TION B Y PETER CRO W THER A …

Diverse and realistic traffic scenarios are crucial for evaluating the AI safety of autonomous
driving systems in simulation. This work introduces a data-driven method called TrafficGen …

We present a new approach to automated scenario-based testing of the safety of
autonomous vehicles, especially those using advanced artificial intelligence-based …

Large-scale driving datasets such as Waymo Open Dataset and nuScenes substantially
accelerate autonomous driving research, especially for perception tasks such as 3D …