Page 9: 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

NASA tests tools to assess drone safety over cities

A future with advanced air mobility aircraft populating the skies will require the U.S. to implement enhanced preflight planning that can mitigate potential risks well before takeoff—and NASA is working to develop the tools ...

Business

How Uber steers its drivers toward better performance

New research shows that the app's ratings and incentive system has made drivers in Chicago as safe and reliable as taxi drivers. The findings suggest regulators may want to consider new quality-control measures.

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