Page 6: 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

Engineers use artificial intelligence to predict car crashes

If you change the timing of a traffic light from 20 seconds to 30 seconds, a new artificial intelligence tool developed by Johns Hopkins University researchers can predict how many more—or how many fewer—accidents will happen ...

Automotive

Flying taxis are nearly here—what's still grounding them

A new wave of aviation innovation is taking shape above our cities, where short flights in electric air taxis could complement cars and trains as part of everyday transportation. Known as advanced air mobility (AAM), this ...

Robotics

AI trained robots, drones, team up with emergency rescue

In a simulated natural disaster, robotic drones from the University of Maryland's RoboScout Team arrived first, scanning the area for survivors. They beamed patients' locations to robot dogs and medics on the ground to quickly ...

Security

Robotaxis keep riders safe, but what about their data?

A robotaxi pulls up to the curb in Los Angeles. The front seat is empty, no driver in sight. The customer slides into the back seat, and off the ride goes to a destination typed into the app, its cameras and sensors silently ...

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