01476607

Component

https://doi.org/10.3141/2366-13

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

The quality of pavement condition data is important not only in assessing the current condition of the network but also in predicting its future condition and planning future maintenance and rehabilitation (M&R) activities. This paper provides a quantitative assessment of the impact of error magnitude and type (systematic and random) in pavement condition data on the accuracy of pavement management system (PMS) outputs (i.e., forecasted needed budget and M&R activities in a multiyear planning period). The process developed to simulate the propagation of pavement condition errors to PMS output consisted of five components: condition data generation, error perturbation, condition prediction, M&R prioritization, and output generation. This process was applied to the 2011 pavement condition data set of the Bryan District of the Texas Department of Transportation. In 2011, the roadway network of the Bryan District consisted of approximately 3,200 roadbed centerline miles. The study results show that both systematic and random errors can highly distort some PMS output parameters, even in error ranges that may be considered acceptable in practice. These effects tend to persist throughout the planning period. The findings of this study can help highway agencies optimize processes for collecting pavement condition data by focusing on error levels and types that cause the greatest impact on PMS output.

01497499

13-4466

English

pp 110–119

2013

Transportation Research Record: Journal of the Transportation Research Board

9780309286855

Print

Figures (9) ; References (31)

Case studies; Condition surveys; Data quality; Errors; Metrics (Quantitative assessment); Pavement management systems; Pavement performance; Pavements

Bryan (Texas)

Highways; Maintenance and Preservation; Pavements; I60: Maintenance

PRP, TRIS, TRB, ATRI

Feb 5 2013 12:52PM

• Bayesian Approach to Updating Markov-Based Models for Predicting Pavement Performance
• 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
• 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