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 …

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 …

In this paper, we reveal that the rarity of safety-critical events in high-dimensional driving
environments is the root cause of the safety challenge for autonomous vehicle development …

In autonomous driving systems, LiDAR and radar play important roles in the perception of
the surrounding environment. LiDAR provides accurate 3D spatial sensing information but …

Safety performance evaluation is critical for developing and deploying connected and
automated vehicles (CAVs). One prevailing way is to design testing scenarios using prior …

Sampling, generation, and evaluation of scenarios are essential steps for intelligent testing
of autonomous vehicles. Since uncertainty in driving behavior always leads to different …

Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of
intelligent modules in the Internet of Vehicles (IoV) by synthesizing augmented datasets …

Testing and evaluating the safety performance of autonomous vehicles (AVs) is essential
before the large-scale deployment. Practically, the acceptable cost of testing specific AV …

An automated driving system (ADS), as the brain of an autonomous vehicle (AV), should be
tested thoroughly ahead of deployment. ADS must satisfy a complex set of rules to ensure …

Sampling critical testing scenarios is an essential step in intelligence testing for Automated
Vehicles (AVs). However, due to the lack of prior knowledge on the distribution of critical …