Research news on AI traffic safety

AI traffic safety concerns the use of artificial intelligence to prevent crashes and reduce injuries in road transport systems. Work in this area spans perception and decision-making for autonomous and cooperative driving, AI-enhanced traffic cameras and inspections, and predictive tools for urban planning and enforcement. Human factors are central, including driver stress and vigilance monitoring, cognitive load and takeover performance in semi-autonomous vehicles, moral decision-making in automated systems, and feedback-based interventions that shape safer driving behavior.

Automotive

AI tech proactively prevents subway door entrapment accidents

A research team led by Professor Jo Woon Chong of the School of Electronic and Electrical Engineering at Sungkyunkwan University (SKKU), in collaboration with researchers from KAIST and Texas Tech University in the United ...

Automotive

AI analysis links pavement conditions to crash risk

A University of Houston professor of civil and environmental engineering is using artificial intelligence to make roads safer by connecting information that is usually analyzed separately. Lu Gao used AI to analyze large-scale ...

page 1 from 16