Abstract: The rapid advancement of autonomous driving platforms (ADPs) demands rigorous safety analysis to ensure reliable vehicle behavior under diverse road and weather conditions, mitigating risks ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Cybersecurity has been reshaped by the rapid rise of advanced artificial intelligence tools, and recent incidents show just how quickly the threat landscape is shifting. Over the past year, we've seen ...

About This Project Phantom Armor Synthetic Log Simulator is an open research effort designed to help the security community evaluate detection and SOC automation systems on realistic, labeled, but ...

Industrial automation is entering a new era with physical AI, where machine learning meets real-world motion control. AI-driven robotics and digital twins are closing the gap between simulation and ...

Getting your Trinity Audio player ready... Big Tech’s self-driving vehicles — a fleet of white Jaguars and powder-blue Zeekrs topped with rotating black cameras and radar — have been rolling around ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

GM will debut the next generation of its Super Cruise hands-free semi-autonomous driving tech, which will allow for eyes-off driving, in the 2028 Cadillac Escalade IQ. The 2028 Escalade IQ will also ...

Trust is a crucial factor that influences human-automation interaction in surface transportation. Previous research indicates that participants tend to display higher levels of subjective trust toward ...

Abstract: Accurately simulating the diverse behaviors of heterogeneous agents in varied scenarios is fundamental to autonomous driving simulation. Our first insight is to leverage state-matching ...