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 …

Automated driving is a promising tool for reducing traffic accidents. While some companies
claim that many cutting-edge automated driving functions have been developed, how to …

Scenario-based testing has become a crucial method for certifying the safety of autonomous
vehicles amidst the rapid advancement of autonomous driving technology. The exploration …

The key procedure of haze image synthesis with adversarial training lies in the
disentanglement of the feature involved only in haze synthesis, ie, the style feature, from the …

Achieving excellent generalization on perceiving real traffic scenarios with diversity is the
long-term goal for building robust autonomous driving systems. A recent theoretical study …

Scenario-based testing will help to validate automated driving systems (ADS) and establish
safer road traffic. To date, most data-driven test scenario generation methods rely primarily …

Autonomous driving holds great potential for reducing traffic accidents. Despite many
advancements in autonomous vehicle functions, challenges persist in assessing their safety …

Highly automated vehicles are complex systems, and ensuring their safe operation within
their Operational Design Domain (ODD) presents significant challenges. Diagnosing failure …

The popularization of automated vehicles (AV) necessitates a comprehensive and reliable
safety assessment to validate their driving capabilities. Adaptive scenario testing based on a …

Anomaly detection in surveillance videos is a crucial and challenging task in the intelligent
transportation systems. Previous methods utilize a memory module to store prototypical …