Page 8: 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.

Hi Tech & Innovation

Predictive AI could prevent crowd crush disasters

To prevent crowd crush incidents like the Itaewon tragedy, it's crucial to go beyond simply counting people and to instead have a technology that can detect the real-inflow and movement patterns of crowds. A KAIST research ...

Computer Sciences

Fast traffic algorithm could improve real-time traffic forecasts

Everyone hates traffic. Big cities in particular are plagued by an overabundance of vehicles, turning a simple crosstown jaunt into an odyssey during rush hour. Part of the problem is that traffic is incredibly complex, and ...

Automotive

Research shows vehicle automation can leave drivers at risk

Motorists using automated driving systems overestimate their situation awareness and readiness to respond but are slower to recognize hazards compared with active "hands on" driving, a new study from Macquarie University ...

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