New tools provide a clearer lens for viewing pavement maintenance and preservation

Asphalt pavement patching
Photo: Adobe Stock

Managing the condition of Minnesota’s 14,000 miles of pavement is a complex balancing act. Maintaining existing pavements to prolong their life is often more cost-effective than waiting until they need to be totally replaced. However, knowing exactly when and what activities to perform is a challenge: If rehabilitation is done too soon, part of the pavement life is wasted; if rehabilitation is done too late, the repairs will be more costly.

To help inform these pavement-preservation decisions, the Minnesota Department of Transportation (MnDOT) enlisted U of M researchers to develop new, better tools for determining the ideal maintenance schedule—ultimately allowing the agency’s planners to optimize resources while providing the highest possible ride quality across the pavement network.

For the past decade, MnDOT has used Remaining Service Life (RSL) as a measure for pavement condition to estimate the time until the next major rehabilitation is needed. “RSL is fairly simplistic and was not providing a full understanding of the system’s condition,” says Mihai Marasteanu, a professor with the Department of Civil, Environmental and Geo- Engineering. “We set out to create a better way to assess the condition of the existing pavement network.”

In the first phase, the research team worked with MnDOT to investigate three new parameters that can be used to gain a clearer understanding of the pavement network’s condition. The first measure, Percent Remaining Service Interval, calculates the time remaining until a defined maintenance or construction activity is required. This measure helps provide an “apples-to-apples” comparison between different pavement types.

“This measure is calculated from Remaining Service Life, but it has the advantage of normalizing the differences between pavements with varying design lives and reporting everything using the same units expressed as a percent,” Marasteanu explains.

The second and third measures were adapted from measures successfully used by other state departments of transportation. One is Asset Sustainability Ratio, which measures the sustainability of pavement asset protection investments by comparing replenishment gained from maintenance activities with pavement wear. The second new measure is Deferred Preservation Liability, which estimates the funding required to address the cumulative backlog of deferred pavement maintenance.

“These measures can help MnDOT keep the pavement network in a stable configuration that allows for more consistent planning,” Marasteanu says.

In the second phase of the project, researchers developed a novel mathematical model that predicts the performance and state-to-state deterioration rates—for example, the likelihood a road segment would transition from good to fair condition in a year’s time. The rates are based on factors such as the roadway’s location, repair history, classification, thickness of base, and thickness of surface. The model was integrated into a new tool that will allow pavement managers to prioritize spending in earlier stages of pavement life, reducing greater future rehabilitation or construction costs.

“Our matrix can forecast pavement deterioration based on external factors and present a decision matrix that determines how to optimize the sequence of pavement repairs,” says Jhenyffer Asp, a MnDOT pavement management analyst. “This type of analysis hasn’t been possible in the past and is a big accomplishment of this project.”

According to Glenn Engstrom, director of MnDOT’s Office of Materials and Road Research, this research ties in with the agency’s broader goal of caring for its pavements with strategic preventive maintenance throughout the pavement life cycle and using more advanced processes to address preventive maintenance needs.

“This work will definitely benefit the long-term health of our pavement network—and Minnesota drivers—by helping us make the most efficient and effective investments,” Engstrom says.

Writer: Megan Tsai


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