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An App Aims To Help Pedestrians With Disabilities Safely Cross Intersections In East Liberty

Carnegie Library of Pittsburgh
The app will be tested in the vicinity of the Carnegie Library for the Blind and Physically Handicapped in East Liberty

Researchers at Carnegie Mellon University are hoping to help pedestrians with disabilities cross intersections more safely.

Their research project makes up the latest phase in the 5-year-old smart traffic signals initiative centered in East Liberty, where wait times for vehicles have been reduced by 40 percent.

In the first year of the project, researchers will focus on building an app that pedestrians could have on their smart phones.

The app would send personalized data about that individual’s movement patterns to a smart traffic signal at an intersection.

“It could communicate things like how long you need to actually move across,” said CMU robotics professor Stephen Smith. “If you’re in a wheelchair, maybe it takes you longer to get across the street than typically would be allowed for pedestrians.”

If a pedestrian needed more time, the walk sign could be extended. If they started to go outside the crosswalk, the app could alert them to move away from traffic.

In the second year, researchers will experiment with route-sharing, to optimize pedestrian signals and get people to their destinations more efficiently.

Such data sharing has already been shown to move vehicles through intersections more quickly.

Initial testing will be done with the help of 25-30 pedestrians with visual impairments at intersections on Baum Boulevard and Centre Avenue, near the Carnegie Library for the Blind and Physically Handicapped.

The smart traffic signal network was installed in 2012 at nine intersections in East Liberty. In the last five years, the network has been extended to 50 intersections from Wilkinsburg almost to downtown Pittsburgh.

“[Each signal] builds what's called a timing plan, amount of time are going to give green and allocate green to each direction that moves the traffic that it sees through the intersection as quickly as possible,” Smith said.

A $2 million grant from the Federal Highway Administration will help support the research.