Lighter Traffic Ahead

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Traffic signals controlled by AI are keeping vehicles rolling citywide.

What’s new: Several U.S. cities are testing systems from Israel-based startup NoTraffic that promise to cut both commute times and carbon emissions, according to MotorTrend. The company plans to expand to 41 cities by the end of 2021.

How it works: NoTraffic uses a combination of neural networks and other techniques to optimize intersections and coordinate traffic signals throughout a city. The system is outfitted to integrate with pavement sensors and connected-vehicle protocols.

  • Cameras installed at intersections run models that detect and classify oncoming vehicles, bikes, and pedestrians, and calculate their speed and location.
  • They stream anonymized data to control modules housed in traffic signals, which aggregate the sensor outputs and optimize signal operation. For instance, the system can turn a green light red if there are no cars coming, or change a red light to green as an emergency vehicle approaches.
  • The data is streamed to the cloud for optimization over larger areas and transmitted back to control modules to account for broader traffic patterns. For example, the system can coordinate multiple lights to reroute traffic around a road that has been closed due to an accident.
  • In a two month trial, Redlands, CA, found that installing the systems in 2 percent of intersections spared commuters a total of 900 hours of gridlock, which translated to an extra $331,380 in economic productivity.
  • The Redlands trial also staved off 11 tons of greenhouse gas emissions. The company estimates that installing its technology in every traffic signal in the U.S. would forestall the equivalent of 20 million vehicles’ worth of exhaust annually.

Behind the news: Machine learning is combating congestion outside the U.S. as well.

  • Delhi deployed its own AI-powered traffic signal network at over 7,500 intersections.
  • At least 23 cities in China and Malaysia use Alibaba’s CityBrain to control gridlock.

Why it matters: Worldwide, congestion costs hundreds of billions of dollars in annual productivity, pollutes cities, and burdens the planet with greenhouse gases. AI-driven traffic control doesn’t eliminate those impacts, but it can take the edge off.

We’re thinking: Many traffic lights already are geared to prioritize passage of emergency vehicles, for example by recognizing patterns of flashing lights — but networked sensors stand to improve traffic routing globally.

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