Selecting Network-Level Project Sections for Sustainable Pavement Management in Texas

Dae Young Kim, Seokho Chi and Janghwan Kim
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Dae Young Kim: Department of Architectural Engineering, Pusan National University, Busan 46241, Korea
Seokho Chi: Department of Civil and Environmental Engineering/Institute of Engineering Research, Seoul National University, Seoul 08826, Korea
Janghwan Kim: Civil Design Team, Daelim Industrial Corp. Ltd., Seoul 03155, Korea

Sustainability, 2018, vol. 10, issue 3, 1-10

Abstract: In recent years, the increasing gap between available funding and preservation needs has influenced district pavement engineers to select and prioritize projects to effectively use funding. However, currently, projects are often selected after an informal assessment, based on local conditions and local district engineers’ experience, in the absence of a statewide systematic process. The primary objective of this study is to determine network-level project sections for effective sustainable pavement management using logistic regression analysis. A large volume of inventory data, documented using pavement-management information systems (PMIS), was used to develop the logistic regression (LR) model for selecting candidate sections. The LR model was subsequently validated using a single 50/50 split sample method. The findings of this study will assist the Austin, Texas, USA district to select and evaluate candidate projects. Furthermore, the study will eventually contribute to improved efficiency in project selection and prioritization by reducing not only the amount of time necessary to review the district PMIS data to identify project candidates, but also the potential for human error.

Keywords: pavement management; preventive maintenance; logistic regression (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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