FutureStructure

Solving a Problem with Data: Researchers Build System to Protect Roads in the Spring

Using near-real-time data collection, researchers are demonstrating a way to improve states' ability to protect brittle roads from heavy vehicles at the end of winter.

by / January 29, 2016

Heather Miller and a team of researchers at the University of Massachusetts, Dartmouth, saw a very specific, very technical problem with public roadways, and they turned to technology to solve it.

And that technology just might become much more widely used in the future — branching out to the coldest states in the U.S. and possibly even serving as a data-gathering tool for coastal areas.

The problem at stake was one that presents itself every winter in the remote, snowy parts of states like Maine. As temperatures drop below freezing, the ground freezes. When the air gets warmer, the ground warms from the top down and from the bottom up, leaving a layer of frozen ground in between. Moisture that would otherwise drain downward is trapped near the surface.

When heavy vehicles drive on smaller, less sturdy roads — as might be the case with a truck carrying logs — they put a lot of stress on that mushy ground and can tear up the smaller roads sitting on it. According to Miller, researchers have estimated that a couple of heavy trucks can do the same amount of damage to a road during a spring thaw that they would otherwise do during an entire year.

While that estimate might not always be true depending on the road, it’s a big enough problem that states and counties across the northern part of the country impose “seasonal load restrictions” (SLR). For a certain amount of time each year, transportation regulators prohibit heavy vehicles from driving on the vulnerable roads.

But determining when to impose an SLR has traditionally been a clunky routine. In Maine, the state has sensors underground at various depths to measure temperature. But in order to collect data from the sensors, state workers have traditionally had to drive out to them and plug in a data logger.

“Previously if we were going out manually, you don’t go out there every day. Some of these sites are very remote, and maybe you gather data once a week or once every two weeks," Miller said. "And if you’re trying to use this as a tool to try to support decision-making, you don’t want to have a week or two gap in your data."

So SLRs have been a bit of a balancing act for the state. If regulators impose one too early, they put an undue burden on trucking that industry relies on to get business done and on people who rely on those vehicles to deliver goods.

“If a load restriction is on, [a wood-bearing truck] may carry the same amount of logs [but] have to do two or three runs in a truck rather than one run,” she said. “So from a sustainability viewpoint, if you’re talking about climate change, you’re putting more carbon in the atmosphere because you’re using more than one truck to move the same number of goods, or you’re taking a longer route.”

But wait too long, and the damage those trucks do to the road will mean costly repairs.

So Miller, along with several colleagues at the university, connected the sensors to transmitters that allow them to collect the data via satellite connection. Then they built an online platform where they, along with the state, can monitor twice-daily updates on the thawing situation.

They also fed air temperature data from Weather Underground into the platform.

All that detail has allowed the researchers to build a decision-making tool that can predict when the state will need to impose an SLR as well as when it can lift the restriction.

It essentially means a more reliable, efficient and constituent-friendly way of doing government work, Miller said.

And this is just the pilot study phase. The group continues to work toward expanding the usefulness of the system in a number of ways. The first way is through bringing in Paul Fortier, a professor in the computer engineering department, to help upgrade the sensors’ connectivity system. While satellites allow for easy remote data collection, Miller pointed out that it costs quite a bit to send data into space and then beam it back to the ground. What Fortier is working toward is using radio-frequency identification to allow for the data to be collected by short-range devices instead of a direct plug-in.

Ramprasad Balasubramanian, associate dean of the university’s engineering college and the architect of the project’s decision-making dashboard, said he hopes to see the concepts the team has been working on expand across the country.

“Our goal is to expand it pretty much to all the northern states,” he said. “So we’re trying to work with the Montana [Department of Transportation], Alaska DOT.”

The system could serve as the foundation for other unrelated projects as well, according to Miller. The Internet of Things — the burgeoning network of devices connected to one another — is offering unprecedented levels of data collection. Miller thinks the team’s sensor stations, and future systems set up for the same purpose in other areas, could be used to supplement the insights of weather-based programs.

Specifically she’s looking toward a future of rising sea levels and the possibility of flooding along the coast. The group’s sensors could be used to collect data on water levels, giving public servants a better look at where flooding is happening.

“If we can do that in real time then it could be very useful,” she said.

Ben Miller Staff Writer

Ben Miller is the business beat staff writer for Government Technology. His reporting experience includes breaking news, business, community features and technical subjects. He holds a Bachelor’s degree in journalism from the Reynolds School of Journalism at the University of Nevada, Reno, and lives in Sacramento, Calif.