Page 5: 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.

Business

NASA, industry weave data fabric with AI

One of the biggest goals for companies in the field of artificial intelligence is developing "agentic" or autonomous systems. These metaphorical agents can perform tasks without a guiding human hand. This parallels the goals ...

Engineering

New testing scheme could work for chips and clinics

Diagnostic testing is big business. The global market for testing semiconductors for defects is estimated at $39 billion in 2025. For medical lab tests, the market is even bigger: $125 billion.

Software

Q&A: Virtual tire development improved by modeling software

Before a car rolls off the production line, manufacturers run virtual tests on it. Simulating tires is particularly challenging since they are subject to extreme stress when driving over potholes and bumps. This is where ...

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