Tyler Fingert

Thursday, June 1, 2017

Valley freeways are getting a better sensor of traffic congestion ahead

PHOENIX – The Arizona Department of Transportation is installing pavement sensors that will allow the transportation agency to more accurately track traffic flow on Valley freeways.

The embedded electronic wires will help ADOT track freeway conditions, estimate travel times and help decide what roads need improvements.

“It helps us keep the traffic moving and then also look ahead, using that data, to make decisions about what are the best candidate locations say for widening or adding extra lanes,” said Doug Nintzel, a spokesman for ADOT.

The technology replaces older, less reliable acoustic devices that are mounted on poles.

Workers install pavement sensors that will allow the transportation agency to more accurately track traffic flow on Valley freeways. (Photo courtesy of Arizona Department of Transportation)

Phoenix resident Luz Perez said knowing how long it will take to drive to a destination eases an often long commute.

“When I have to go to work and be there on time, it helps,” Perez said.

An installation on northbound Interstate 17 in Phoenix is expected to be completed by July 1. By the time the project is finished, ADOT will have embedded traffic-flow sensors in more than 85 places along the Phoenix-area freeway system.

ADOT said they have finished installing the wiring on Interstate 10, US 60, and State Route 51.

The sensors, along with other technology, help ADOT notice trouble spots on the road as quickly as possible.

Workers embed electronic wires along Valley freeways that will better sense traffic flow. The Arizona Department of Transportation uses the sensors to track freeway conditions, estimate travel times and help decide what roads need improvements. (Photo courtesy of Arizona Department of Transportation)

“Because we have the sensors in the pavement, we are able to really judge what is going on there, as far as the conditions,” he said.

That information is passed on to drivers.

“We’re able to utilize the data on traffic flow and the computers translate that into the travel times that you wind up seeing as a driver,” Nintzel said.

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