Page 10: 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

Through smartphone apps, AI can close road assessment gap

Dodging potholes is a familiar routine for drivers. But, behind every bump and crack in the pavement is a bigger issue: many communities lack the tools and data they need to maintain their roads effectively. Traditional pavement ...

Hi Tech & Innovation

Researcher develops generative learning model to predict falls

In a study published in the journal Information Systems Research, Texas Tech University's Shuo Yu and his collaborators developed a generative machine learning model to detect instability before a fall occurs. The hope is ...

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