Pavement management systems are a form of asset management that provide a framework by which transportation agencies monitor the performance of their pavement networks, set performance targets, and implement strategies to meet those performance targets. CSHub research in this area seeks to improve the methods used to allocate available funding across the needs of the pavement network by developing models to predict the performance of the network and optimize the allocation of funds. This process of performance-based planning enables economically efficient management of pavement networks by optimizing pavement network performance for a given cost.
News
- The Hill: We’re overhauling our cars in the name of energy efficiency — why not our roads? (January 2024)
- The Hill: Before building sustainably, let’s define ‘sustainability’ (June 2021)
- The Hill: America’s Roads Are Crumbling, But We Can Make Them Sustainable (June 2020)
- MIT News: Improving Pavement Networks by Predicting the Future (February 2020)
Topic Summaries
- Network Asset Management (April 2019)
- Improving America’s Road Infrastructure by Embracing Uncertainty (March 2022)
Research Briefs
- Research Brief: Improving America’s Road Infrastructure by Embracing Uncertainty (March 2022)
- Comparison of Feedforward and Recurrent Neural Networks for Predicting Pavement Roughness (January 2021)
- Improving Pavement Network Conditions Through Competition (October 2020)
- The Role of Pavements in Meeting GHG Reduction Targets (August 2019)
- Influence of Treatment Types on Performance-based Planning (August 2019)
- The influence of incorporating uncertainties and treatment path dependence in performance-based planning analyses (November 2018)
- The influence of analysis period on pavement network performance (November 2017)
- Developing a Network-Level Pavement Management Model (November 2015)
Publications
- Batouli, M., Swei, O., Zhu, J., Gregory, J., & Kirchain, R. (2015). “A Simulation Framework for Network Level Cost Analysis in Infrastructure Systems,” in O’Brien W., Ponticelli, S., (Eds.), Computing in Civil Engineering 2015, ASCE.
- F. Guo, O. Swei, J. Gregory, R. Kirchain, “Sensitivity Analysis of Performance Metrics to Different Parameters in Pavement Management Systems”, the Transportation Research Board 97th Annual Meeting Compendium of Papers, Washington, DC, January 7-11, 2018. (PDF)
- Guo, F., Azarijafari, H., Gregory, J., & Kirchain, R. (2021). Environmental and economic evaluations of treatment strategies for pavement network performance-based planning. Transportation Research Part D: Transport and Environment, 99, 103016.
- Guo, F., AzariJafari, H., Gregory, J., Kirchain, R. “Environmental and economic evaluations of treatment strategies for pavement network performance-based planning”, Transportation Research D: Transport and Environment. Volume 99, October 2021, 103016
- Guo, F., Gregory, J., Kirchain, R. “Incorporating cost uncertainty and path dependence into treatment selection for pavement networks,” Transportation Research Part C: Emerging Technologies,
Volume 110, Jan 2020, Pages 40-55, - Guo, Fengdi, et al. “Environmental and economic evaluations of treatment strategies for pavement network performance-based planning.” Transportation Research Part D: Transport and Environment 99 (2021): 103016.
- Guo. F., Xingang, Z., Gregory, J., Kirchain, R. (2021) “A weighted multi-output neural network model for the prediction of rigid pavement deterioration,” International Journal of Pavement Engineering,
- Swei O., Gregory J., Kirchain R., “Does Pavement Degradation Follow a Random Walk with Drift? Evidence from Variance Ratio Tests for Pavement Roughness”, Journal of Infrastructure Systems, Vol. 24, No. 4, 2018.
- Swei O., Gregory J., Kirchain R., “Embedding Flexibility within Pavement Management: Technique to Improve Expected Performance of Roadway Systems”, Journal of Infrastructure Systems, Vol. 25, No. 3, 2019.
- Swei O., Gregory J., Kirchain R., “Pavement Management Systems: Opportunities to Improve the Current Frameworks” Transportation Research Board 95th Annual Meeting, No. 16-2940. 2016.