Highly Automated Vehicles (HAVs) must undergo strict safety testing before being released
to the public. Mileage-based on-road testing suffers from unaffordable time costs and high …

AI-based systems are software systems with functionalities enabled by at least one AI
component (eg, for image-, speech-recognition, and autonomous driving). AI-based systems …

Automated Driving Systems (ADSs) have seen rapid progress in recent years. To ensure the
safety and reliability of these systems, extensive testings are being conducted before their …

Autonomous driving carries the promise to drastically reduce the number of car accidents;
however, recently reported fatal crashes involving self-driving cars show that such an …

In the near future, systems, that use Artificial Intelligence (AI) methods, such as machine
learning, are required to be certified or audited for fairness if used in ethically sensitive fields …

Autonomous Driving Systems (ADSs) are safety-critical systems, and safety violations of
Autonomous Vehicles (AVs) in real traffic will cause huge losses. Therefore, ADSs must be …

Systematic testing of autonomous vehicles operating in complex real-world scenarios is a
difficult and expensive problem. We present Paracosm, a framework for writing systematic …

Despite recent advances in autonomous driving systems, accidents such as the fatal Uber
crash in 2018 show these systems are still susceptible to edge cases. Such systems must be …

Autonomous Driving Systems (ADSs) are safety-critical, and must be fully tested before
being deployed on real-world roads. To comprehensively evaluate the performance of …

Since safety-critical autonomous vehicles need to interact with an immensely complex and
continuously changing environment, their assurance is a major challenge. While systems …