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 …

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 …

Autonomous driving has shown great potential to reform modern transportation. Yet its
reliability and safety have drawn a lot of attention and concerns. Compared with traditional …

Automated Driving Systems (ADS) have made great achievements in recent years thanks to
the efforts from both academia and industry. A typical ADS is composed of multiple modules …

As shown by recent studies, machine intelligence-enabled systems are vulnerable to test
cases resulting from either adversarial manipulation or natural distribution shifts. This has …

Autonomous vehicle (AV) systems must be comprehensively tested and evaluated before
they can be deployed. High-fidelity simulators such as CARLA or LGSVL allow this to be …

Autonomous vehicles must operate safely in their dynamic and continuously-changing
environment. However, the operating environment of an autonomous vehicle is complicated …

Deep Neural Networks (DNNs) have been widely used to perform real-world tasks in cyber-
physical systems such as Autonomous Driving Systems (ADS). Ensuring the correct …

Autonomous driving has become real; semi-autonomous driving vehicles in an affordable
price range are already on the streets, and major automotive vendors are actively …

Autonomous Driving Systems (ADSs) are complex systems that must satisfy multiple
requirements such as safety, compliance to traffic rules, and comfortableness. However …