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Pittsburgh's AI Traffic Signals Will Make Driving Less Boring

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Traffic congestion costs the U.S. economy 121 billion a year, mostly due to lost productivity, and produces about 25 billion kilograms of carbon dioxide emissions, Carnegie Mellon University professor of robotics Stephen Smith told the audience at a White House Frontiers Conference last week. In urban areas, drivers spend 40 percent of their time idling in traffic, he added. The next step is to have traffic signals talk to cars. Pittsburgh is the test bed for Uber's self-driving cars, and Smith's work on AI-enhanced traffic signals that talk with self-driving cars is paving the way for the ultimately fluid and efficient autonomous intersections.


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Daily Mail

Uber riders in Pittsburgh can get a glimpse of the future by summoning a car capable of handling most of the tasks of driving on its own. Starting Wednesday morning, a fleet of self-driving Ford Fusions will pick up Uber riders who opted to participate in a test program. While the vehicles are loaded with features that allow them to navigate on their own, an Uber engineer will sit in the driver's seat and seize control if things go awry. A group of self driving Uber vehicles position themselves to take journalists on rides during a media preview at Uber's Advanced Technologies Center in Pittsburgh, Monday, Sept. 12, 2016 (AP Photo/Gene J. Puskar) Uber's test program is the latest move in an increasingly heated race between tech companies in Silicon Valley and traditional automakers to perfect fully driverless cars for regular people. Competitors such as Volvo and Google have invested hundreds of millions of dollars and logged millions of miles test driving autonomous vehicles, but Uber is the first company in the U.S. to make self-driving cars available to the general public.


AI Machine Learns to Drive Using Crowdteaching

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These guys have developed a way of creating large annotated databases for exactly these kinds of difficult tasks. By gathering data from a wide range of annotators, Driverseat effectively learns from the crowd. Interestingly, the team's evaluation system found that the algorithm worked less well when the sun was close to the horizon, interfering with vision. For the first time, an AI machine has learned a complex driving skill from the behavior of real people.