The virtual-to-real paradigm, ie, training models on virtual data and then applying them to
solve real-world problems, has attracted more and more attention from various domains by …

End-to-End driving is a promising paradigm as it circumvents the drawbacks associated with
modular systems, such as their overwhelming complexity and propensity for error …

In the vehicular mixed reality (MR) Metaverse, the discrepancy between physical and virtual
entities can be overcome by fusing the physical and virtual environments with multi …

This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …

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 …

Automated online recognition of unexpected conditions is an indispensable component of
autonomous vehicles to ensure safety even in unknown and uncertain situations. In this …

Offline model-level testing of autonomous driving software is much cheaper, faster, and
diversified than in-field, online system-level testing. Hence, researchers have compared …

In the rapidly evolving landscape of autonomous driving, the capability to accurately predict
future events and assess their implications is paramount for both safety and efficiency …

Context: Surrogate-assisted search-based testing (SA-SBT) aims to reduce the
computational time for testing compute-intensive systems. Surrogates enhance testing …

With the rapid development of autonomous driving systems (ADSs), testing ADSs under
various environmental conditions has become a key method to ensure the successful …