01497805

Component

https://doi.org/10.3141/2366-04

http://scholar.google.com...yadi&publication_year=2013

The Markov decision process is one of the most common probabilistic prediction models used in infrastructure management. When existing data are insufficient, expert knowledge is commonly used to derive a Markovian transition probability matrix. Eventually, every pavement management system will progress to a level at which inspection measurements from the network will be organized into a database to be used for performance prediction. The best way to use this body of data to improve the initially developed transition probability matrix is to combine prior expert knowledge with new observations. This paper proposes a method for periodically updating Markovian transition probabilities as new inspection data become available. Bayesian inference is used to accommodate uncertainty in the expert-derived initial probabilities and measurement errors from inspection of the network. A data set of asphalt concrete pavement observations from the Minnesota Department of Transportation test facility is used to illustrate the proposed method.

01497499

13-0993

English

pp 34-42

2013

Transportation Research Record: Journal of the Transportation Research Board

9780309286855

Print

Figures (5) ; References (31) ; Tables (2)

Asphalt concrete pavements; Bayes' theorem; Markov processes; Pavement management systems; Pavement performance

Highways; Maintenance and Preservation; Pavements; I22: Design of Pavements, Railways and Guideways; I60: Maintenance

TRIS, TRB, ATRI

Feb 5 2013 12:18PM

• Enhancing Network-Level Decision Making Through the Use of a Structural Capacity Index
• Evaluating Pavement Condition of the National Highway System
• Evaluation of the Effectiveness of Mississippi’s Pavement Warranty Program
• Findings from the International Scan on Managing Pavements and Monitoring Performance
• Impact of Error in Pavement Condition Data on the Output of Network-Level Pavement Management Systems
• Improved Method for Evaluating the Pavement Structural Number with Falling Weight Deflectometer Deflections
• Innovative Sprinkle Treatment for Thin Durable Asphalt Overlays
• Integration of Rolling Wheel Deflectometer Deflection Measurements into Pavement Management Systems: Use of Multivariate Statistical Methods and Fuzzy Logic
• Management of Pavement Maintenance, Rehabilitation, and Reconstruction Through Network Partition
• Pavement Condition States Before and After Treatment
• Probabilistic Characterization of Uncertain Inputs in the Life-Cycle Cost Analysis of Pavements
• Project Emission Estimator: Tool for Contractors and Agencies for Assessing Greenhouse Gas Emissions of Highway Construction Projects
• Toward Sustainable Pavement Management: Incorporating Environmental Impacts of Pavement Treatments into a Performance-Based Optimization