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Title: Modeling and Predicting Smoothness of Asphalt Overlays Using Network and Project Level Data
Accession Number: 01763751
Record Type: Component
Abstract: When asphalt pavement projects are planned, pavement design engineers would like to project what smoothness values of the existing asphalt pavement will be at the time of construction. For example, will future smoothness values trigger rehabilitation and change the original pavement design? Prediction of future smoothness values for these projects can be challenging for pavement engineers and program managers. Although most state agencies have pavement management systems with embedded smoothness prediction models, the network level smoothness models are not accurate enough to meet project designers’ needs. While some project level smoothness models from literature are available, many of the parameters required by these models are not easily obtained or are not suitable for local conditions. This paper provides a new method to predict the smoothness value by utilizing both network and project level data that agencies normally collect. The method contains several key steps including (a) developing and validating network smoothness models using network level data, (b) converting a network model into a project level model using project specific data, and (c) utilizing the project level model to predict asphalt overlay smoothness. The implementation of the proposed method is illustrated in this paper.
Supplemental Notes: This paper was sponsored by TRB committee AKT10 Standing Committee on Pavement Management Systems.
Report/Paper Numbers: TRBAM-21-00933
Language: English
Corporate Authors: Transportation Research BoardAuthors: Cheng, DingXinLane, LerosePyle, TomKing, AllenPagination: 19p
Publication Date: 2021
Conference:
Transportation Research Board 100th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; References; Tables
TRT Terms: Subject Areas: Data and Information Technology; Design; Highways; Pavements
Source Data: Transportation Research Board Annual Meeting 2021 Paper #TRBAM-21-00933
Files: TRIS, TRB, ATRI
Created Date: Dec 23 2020 11:10AM
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