Development of an Automated and Integrated Algorithm in Determining Optimum Maintenance and Rehabilitation Strategies Considering Multilane Roadways. Issue 5 (May 2022)

• Record Type: Journal Article
• Authors: Tran, Thai Son; Flores, Julius Marvin; Lee, Hyun Jong; Kim, Kideok; Kim, Hyunwook
• Is Part Of: Transportation research record. Volume 2676:Issue 5(2022)
• Page Start: 806
• Page End: 819
• Publication Date: 2022-05
• Subjects: infrastructure -- infrastructure management and system preservation -- pavement management systems -- decision making: pavement management -- life cycle cost analysis (LCCA) -- network-level data -- pavement management; Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/03611981211072806
• Languages: English
• ISSNs: 0361-1981

Abstract

Pavement management systems include road surveying, data analysis, identification of rehabilitated sections, determination of treatment methods, and budget optimization for maintenance and rehabilitation (M&R). These complex processes challenge many agencies in determining the most appropriate M&R strategies for the current year and choosing rehabilitation alternatives using life cycle cost analysis. In addition, these are time-consuming processes since the analysis and interpretation are done separately. In this study, an automated integrated algorithm is developed to help agencies determine the appropriate rehabilitated homogeneous section and optimize the budget at the network level for single and multilane roads. The algorithm was developed based on the pruned exact linear time and changepoints for a range of penalties methods in determining homogeneous sections from distresses on the surfaces being surveyed on single lanes. An additional algorithm is then proposed to identify homogeneous sections by considering adjacent multilane sections. Finally, the prioritized homogeneous sections for rehabilitation are determined by optimizing the available budget at the network level, considering the distress index and recommended rehabilitation type. During optimization, different budget constraint scenarios were considered to satisfy several requirements from agencies considering a random search approach. The proposed algorithm was applied to real field data where it was found that the recommended M&R strategies for the homogenized sections using the proposed approach are feasible, practical, and reasonable. It is recommended that the performance model used in this study be developed further to improve the proposed integrated algorithm.