Page 2: 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

The promise of self-driving cars hits a traffic snag

As autonomous vehicles (AVs) near widespread use, researchers at The University of Texas at Arlington say the technology could change not just how people travel but how much, reshaping traffic congestion, city planning and ...

Energy & Green Tech

Researchers measure traffic emissions, to the block, in real-time

In a study focused on New York City, MIT researchers have shown that existing sensors and mobile data can be used to generate a near real-time, high-resolution picture of auto emissions, which could be used to develop local ...

Automotive

When self-driving cars become socially intelligent

Driven by AI, the advent of autonomous mobility has accelerated in recent years. It has advantages that go beyond the asphalt. One of the first test drives of an autonomous vehicle in a public area took place on an EPFL campus ...

Automotive

How autonomous vehicles could change morning commutes

Autonomous vehicles (AVs), which already operate on the roads of several major U.S. cities and in countries worldwide, are expected to play a large role in shaping the future of cities. In a new study, researchers have investigated ...

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