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

New model aims to keep remote robotaxi operators alert and ready

So-called "driverless" cars often have human operators remotely controlling the vehicles to help navigate tricky driving situations and avoid accidents. But this setup poses a number of challenges. How do you ensure the operators ...

Engineering

AI could prevent construction delays before they happen

What if a construction project could rewrite its own schedule the moment a problem appears? A new peer-reviewed study from the University of East London (UEL) suggests that artificial intelligence could make this possible—detecting ...

Engineering

A new way to study how cannabis use impacts safe driving

As marijuana legalization expands across the U.S., it is outpacing research on the impact of cannabis use behind the wheel. Researchers at the Virginia Tech Transportation Institute (VTTI) recently spent two years collecting ...

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