Remaining Service Life Asset Measure, Phase 2

Principal Investigator(s):

Mihai Marasteanu, Professor, Civil, Environmental and Geo-Engineering


  • Gary Davis, Professor, Civil, Environmental and Geo-Engineering
  • Alireza Khani, Associate Professor, Civil, Environmental and Geo-Engineering

Project summary:

MnDOT has used the remaining service life (RSL) measure for pavement condition for more than a decade. RSL is an estimation of the time until the next major rehabilitation of the pavement section. Using pavement deterioration curves, the time when a pavement section reaches a road quality index (RQI) of 2.5 is predicted and the RSL is simply calculated as the difference between the predicted and the present time. However, it is not clear if this metric by itself can show the "true" condition of the system.

At the end of phase one, a work plan was developed for a follow-up phase two. The main objectives of this phase two were to obtain relevant data to calculate the percent remaining service life interval (PRSI) for different categories of pavements, calculate two additional metrics--asset sustainability ratio and deferred preservation liability--and perform analyses to determine how much time and funding is required to bring the system to a stable configuration of even distribution of PRSI, which allows for more consistent planning.

The first step in phase two was to obtain relevant pavement management data from MnDOT and perform preliminary data analyses. Researchers investigated and summarized the prediction models and optimization process currently used by MnDOT. Next, asset sustainability ratio and deferred preservation liability were calculated for MnDOT's network. Then details of the estimation process of state-to-state transition probabilities to be used in the Markov chain model were presented. To allow for site-specific variation, ordinal logistic regression models were incorporated in the Markov chain model. The results were used in a dynamic programming optimization methodology to obtain baseline and optimal policies for different scenarios and a user-friendly Excel spreadsheet tool was developed. Finally, researchers presented a summary of the work performed, followed by conclusions and recommendations.

Project details:

  • Project number: 2020014
  • Start date: 07/2019
  • Project status: Completed
  • Research area: Infrastructure
  • Topics: Data and modeling, Maintenance

Reports or Products: