Google’s Project Green Light, using AI to optimize traffic lights and reduce congestion, is being tested in Seattle and other cities worldwide.
The system, which aims to decrease stop-and-go traffic by up to 30%, has shown promising results.
Experts believe that AI can effectively manage traffic and reduce carbon emissions. (Trending: Fauci’s Ex-Boss Admits The Truth About COVID)
While some express concerns about potential social engineering and micromanagement, the program is seen as a significant step towards integrating AI into U.S. infrastructure.
“AI capabilities can replicate dozens of analysts who normally would perform tasks like this and constantly make adjustments as needed,” Alexander said.
“With all AI, it is crucial that a human being vets the work, and as long as trained experts use AI as a form of augmentation, this is an ideal application for the current state of AI capabilities.”
“We had one case where we moved four seconds from a north-south street to an east-west street for a particular time of day, so then that can help reduce some of that stop-and-go traffic,” Laura Wojcicki, an engineer at Seattle’s Department of Transportation, stated.
“Really, what Google is doing is adding new objectives like idling time and its resultant carbon footprint. Traffic management systems are already quite sophisticated. Perhaps the most important aspect of this one is it’s free,” Phil Siegel said.
“It means a lot for drivers, and it also means a lot for emissions,” Wojcicki added.
“U.S. infrastructure will become integrated with AI, but that doesn’t necessarily mean it will make things easier or better,” Samuel Mangold-Lenett said.
“We all know that people tend to be irrational when behind the wheel; there’s a good chance this is just a quixotic attempt at social engineering and micromanagement.”
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