Original scientific paper

https://doi.org/10.17559/TV-20221019112637

A New Decision-Making Optimization Approach for Sustainable Expressway Pavement Maintenance

Lin Lin ; School of Traffic and Transportation Engineering, Central South University, No. 22, Shaoshan South Road, Tianxin District, Changsha City, 410000, China
Zijian Wu ; School of Traffic and Transportation Engineering, Central South University, No. 22, Shaoshan South Road, Tianxin District, Changsha City, 410000, China
Hu Yang ; School of Traffic and Transportation Engineering, Central South University, No. 22, Shaoshan South Road, Tianxin District, Changsha City, 410000, China
Bao Guo ; School of Traffic and Transportation Engineering, Central South University, No. 22, Shaoshan South Road, Tianxin District, Changsha City, 410000, China
Minglun Li ; School of Traffic and Transportation Engineering, Central South University, No. 22, Shaoshan South Road, Tianxin District, Changsha City, 410000, China
Jianhe Xiao ; School of Traffic and Transportation Engineering, Central South University, No. 22, Shaoshan South Road, Tianxin District, Changsha City, 410000, China
Shengnan Li ; School of Traffic and Transportation Engineering, Central South University, No. 22, Shaoshan South Road, Tianxin District, Changsha City, 410000, China
Wenyao Peng ; Hunan Pingyi Expressway Construction and Development Co.,Ltd., Yingbin Road, Wushi Neighborhood Committee, Wushi Town, Pingjiang County, Yueyang City, 414100, China
Yi Zhou ; Hunan Pingyi Expressway Construction and Development Co.,Ltd., Yingbin Road, Wushi Neighborhood Committee, Wushi Town, Pingjiang County, Yueyang City, 414100, China
Pu Wang orcid.org/0000-0002-4503-6643 ; School of Traffic and Transportation Engineering, Central South University, No. 22, Shaoshan South Road, Tianxin District, Changsha City, 410000, China *

* Corresponding author.

Abstract

We use actual pavement disease data, pavement performance data and pavement maintenance data to develop a data envelopment analysis (DEA) model to evaluate the effectiveness of repairing each type of pavement disease. Next, an optimization model is proposed to improve the pavement maintenance performance while reducing the pavement maintenance cost. Results indicate that repairing transverse cracking and rutting pavement diseases is more effective in improving the pavement maintenance performance. We also find that the pavement maintenance performance is enhanced prominently if the cost constraint increases from 0.1 to 0.2, while only slight improvements are observed if the maintenance cost keeps increasing. When the cost constraint is set to 0.2, the number of expressway sections with excellent condition increases by 71 and the average pavement condition index (PCI) increases by 0.27, implying that the generated pavement maintenance strategy can achieve a good performance while using much lower maintenance cost.

Keywords

data analysis; decision-making optimization; expressway pavement disease; pavement condition index; pavement maintenance strategy

Hrčak ID:

318464

URI

https://hrcak.srce.hr/318464

Publication date:

27.6.2024.

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