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Pedestrians aren't always paying attention. Photo: Ford

Researchers at the University of Michigan are studying human body language to teach self-driving cars to recognize and predict pedestrian movements with greater precision than current technologies.

Why it matters: People don't always pay attention when crossing the street, so AVs need to be on the lookout for distracted pedestrians, not just other cars on the road.

"If a pedestrian is playing with their phone, you know they're distracted. Their pose and where they're looking is telling you a lot about their level of attentiveness. It's also telling you a lot about what they're capable of doing next."
— Ram Vasudevan, assistant professor of mechanical engineering, Michigan

How it works: Using data collected by vehicles through cameras, lidar and GPS, the researchers captured video snippets of humans in motion and then recreated them in 3D computer simulation.

  • This enabled them to create a "biomechanically inspired recurrent neural network" that catalogs human movements.
  • By focusing on humans' gait, body symmetry and foot placement, they can predict what pedestrians might do next and train self-driving cars to recognize behavior.

Background: Until now, most machine learning for AVs has relied on still images.

  • If you show a computer enough photos of a stop sign it will eventually come to recognize stop signs in the real world.

What's next: By using video clips that run for several seconds, Michigan's system can study the first half of the snippet to make its predictions, and then verify the accuracy with the second half.

  • The researchers said they could predict a pedestrian's location within 10 centimeters after one second and less than 80 centimeters after 6 seconds. All other comparison methods were up to 7 meters off.
  • "We're [now] better at figuring out where a person is going to be," says Matthew Johnson-Roberson, associate professor in Michigan's naval architecture and marine engineering department.

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New or expanded climate initiatives are popping up at several universities, a sign of the topic's rising prominence and recognition of the threats and opportunities it creates.

Why it matters: Climate and clean energy initiatives at colleges and universities are nothing new, but it shows expanded an campus focus as the effects of climate change are becoming increasingly apparent, and the world is nowhere near the steep emissions cuts that scientists say are needed to hold future warming in check.

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The pandemic isn't slowing tech

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Thursday's deluge of Big Tech earnings reports showed one thing pretty clearly: COVID-19 may be bad in all sorts of ways, but it's not slowing down the largest tech companies. If anything, it's helping some companies, like Amazon and Apple.

Yes, but: With the pandemic once again worsening in the U.S. and Europe, it's not clear how long the tech industry's winning streak can last.

Texas early voting surpasses 2016's total turnout

Early voting in Austin earlier this month. Photo: Sergio Flores/Getty Images

Texas' early and mail-in voting totals for the 2020 election have surpassed the state's total voter turnout in 2016, with 9,009,850 ballots already cast compared to 8,969,226 in the last presidential cycle.

Why it matters: The state's 38 Electoral College votes are in play — and could deliver a knockout blow for Joe Biden over President Trump — despite the fact that it hasn't backed a Democrat for president since 1976.

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