New analysis from Carnegie Mellon College might assist autonomous autos navigate crowded streets – CBS Pittsburgh

By: KDKA-TV News Staff

PITTSBURGH (KDKA) – Most motorists know that driving on a street with cars parked on either side and coming down a one-way street in this situation is frustrating.

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It becomes an even greater challenge when there is no human driver behind the wheel.

However, new research from Carnegie Mellon University’s Argo AI Center for Autonomous Vehicle Research is working to solve this challenge.

“It’s the unwritten rules of the road that we pretty much have to deal with here,” says Christoph Killing, former visiting scientist at the Robotics Institute at the CMU School of Computer Science. “It’s a difficult piece. You have to learn to deal with this scenario without knowing whether the other vehicle is stopping or driving. “

Killing started with researcher John Dolan as well as Ph.D. Student Adam Villaflor to work on this subject.

At the International Conference on Robotics and Automation, the team presented its research paper “Learning To Robustly Negotiate Bi-Directional Lane Usage in High-Conflict Driving Scenarios”.

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“I’ve always found this to be an interesting and sometimes difficult aspect of driving in Pittsburgh,” said Dolan.

The team developed a method that would model different levels of driver cooperation, including the likelihood of one driver stopping to let the other pass, and an algorithm that could help autonomous vehicles safely navigate a situation on a crowded road .

So far it has only been used in the simulation and not on a real vehicle in the real world.

They say their results are promising.

“Extensive testing brings the final percentage of touch cases to light,” said Dolan. “We keep finding these corner cases and always finding ways to deal with them.”

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You can read the team’s full study and more about their work at this link.

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