Pavement Performance Prediction System is Valuable Tool for TxDOT
Transportation agencies across the US, including the Texas Department of Transportation (TxDOT), have long been moving towards the development of pavement management systems that allow performance monitoring of their roadways. Driven by advanced information technologies such as GIS and sophisticated modeling techniques, such systems would help transportation officials develop more accurate budget and policy planning information to support decision making at technical, administrative, and legislative levels.
Predicting the future performance of a roadway with historical data is critical to the success of strategically preserving our transportation infrastructure. The life-cycle behavior and performance of transportation infrastructure, such as pavements, are affected by a variety of factors, such as material properties, traffic loading, construction quality, and environmental conditions. Past attempts focused on using the available performance data and various modeling techniques to develop such management systems.
Challenges for Texas
However, Texas’ unique characteristics, especially the vast size of the managed pavement network, made some of the decision support models and/or algorithms a challenge to implement. By employing historical data, mechanistic and time-series models, and probabilistic approaches, Dr. Zhanmin Zhang, Associate Professor and Fellow of the Clyde E. Lee Endowed Professorship in Transportation Engineering at the Center for Transportation Research (CTR), developed a web-based system for predicting the future performance of large-scale infrastructure networks such as pavements.
These models, along with other supporting algorithms, have been implemented with a state-of-the-art web-based platform that functions as a sophisticated performance prediction system. This allows the future performance of a large highway network to be analyzed up to 30 years into the future.
Through collaboration with TxDOT districts and the Maintenance Division, the web-based system has been successfully used to support the development and pavement condition prediction of TxDOT’s 4-Year Pavement Management Plans, providing functional capabilities and reliable information that allow TxDOT administrators and engineers to make more informed decisions regarding their budget planning and budget allocation for pavement management, especially under budget constraints.
The Research Saves Texas Big Money
According to Dr. Mike Murphy, a CTR research engineer who has 25 years of experience working at TxDOT on pavement management, collaboratively implementing this system “has yielded an estimated benefit of over $12,000,000 annually to TxDOT”.
Furthermore, considering that this system help produce a statewide plan which manages over $1.5 Billion annually that must be approved by the state Legislature Budget Board (LBB) and Governor’s office on the basis of the pavement condition predicted with this system, the benefits might in fact be even higher.
As result of this collaborative implementation effort, the International Road Federation (IRF) awarded TxDOT the 2011 Global Road Achievement Award in the category of maintenance management.
The significance of this work was also recognized by the American Society of Civil Engineers (ASCE). Dr. Zhanmin Zhang was selected to receive the 2012 ASCE James Laurie Prize, with the award citation:
“For his contribution to the advancement of knowledge and understanding of the management of highway infrastructure systems and in particular his development of a state-of-the-art pavement condition performance prediction process and pavement needs estimates for different pavement condition goals.”