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

AI system developed to help prevent airport collisions

Near misses like the one at New York's John F. Kennedy International Airport inspired a group from the AirLab in Carnegie Mellon University's Robotics Institute (RI) to create World2Rules, an AI system that learns interpretable ...

Software

Which pothole to fix? AI team helps company develop city system

Artificial intelligence (AI) experts from The University of Texas at Dallas have partnered with a Japanese company through its Irving, Texas-based subsidiary to help local governments prioritize road repairs. The system builds ...

Engineering

Creating the ultimate driver's test for automated vehicles

Automated vehicles have been steadily rolling out in U.S. cities, but scaled deployment still faces a daunting challenge: proving the technology can safely navigate the complexity of real-world driving. Virginia Tech researchers ...

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