Using the Liuzhou North Ring Expressway in Guangxi as a case study, researchers developed a multi-level decision-making model comprising the comprehensive objective layer, criterion layer, indicator layer, and scheme layer. By combining road condition assessment with weighted evaluation factors, the optimal maintenance plan was determined. This achievement, published in the journal SC, shows that ultra-thin cover and composite seal coat technologies are highly reasonable in ranking and weight allocation, highly aligned with actual engineering needs, and provide solutions for maintenance decisions by management departments.
As expressway networks across China continue to age and expand, with limited budgets and diverse maintenance options, choosing the most effective preventive maintenance measures for thousands of kilometers of asphalt pavement is no longer just a technical issue; it is a costly and complex management challenge. To address these prominent issues, the research team has developed a multi-level decision-making framework for preventive asphalt pavement maintenance, successfully transforming the complex decision-making process into quantifiable evaluation models. The research results were recently published in the journal SC, providing scientific, transparent, and practical solutions.
Through a practical case study of the Liuzhou North Ring Expressway in Guangxi, the research team proposed a decision framework based on the Analytic Hierarchy Process Method (AHP). This framework addresses how to select maintenance measures. By establishing a four-level evaluation system that includes the objective layer, criterion layer, indicator layer, and scheme layer, it summarizes the core demands of highway maintenance into three dimensions. Researchers consider quality and construction difficulty, and incorporate economic cost, expected pavement service life, and environmental protection into the evaluation system. The system includes three dimensions: technology, economy, and environment, with indicators covering the construction quality, material quality, project cost, service life, traffic disruption, and aesthetic effects.
By analyzing measured data from the Liuzhou North Ring Expressway, the model prioritized five mainstream maintenance technologies. The ultra-thin cover and composite seal coat ranked among the top in comprehensive scores. In the current context of budget constraints and increasing environmental requirements, these two technologies strike the best balance between improving pavement performance, extending service life, and reducing environmental impact. Sensitivity analysis, simulating decision outcomes under different weightings, confirmed the model's robustness. Whether management focuses on technological enhancement or cost control, this framework provides consistent recommendations for decision-making.
By scientifically weighing various indicators, the study draws key conclusions: cost is the core factor, but not the only one. Among the factors influencing decision-making, unit cost remains the most direct influence, while environmental protection indicators and service life should not be overlooked. Using quantitative scoring, the study prioritized various curing techniques. In practice, ultra-thin cover and composite seal coat were rated as the preferred preventive maintenance solutions due to their balance between technical performance and economic benefits.
The biggest highlight of this study is its practicality. It is not just an academic theory, but a practical management tool that helps management departments conduct scientific evaluations and invest in the most cost-effective maintenance technologies. Through timely, scientific preventive interventions, the ageing of roads can be delayed. A clear scoring system is provided, ensuring that every decision in the maintenance project is traceable and reduces subjective arbitrariness in the decision-making process.
The research results show that this decision-making framework can be adjusted according to traffic flow, climate conditions, and management models in different regions, offering strong regional applicability. With the popularization of smart transportation technologies, this system will help China's expressway maintenance and management develop toward more refined and intelligent directions. Currently, the model has completed preliminary validation in real-world engineering settings, demonstrating close alignment with maintenance needs. In the future, the team plans to expand the pilot scope and introduce more intelligent evaluation methods, such as fuzzy mathematics and machine learning, to meet more complex road network maintenance needs. This marks a shift in the operation and maintenance of China's expressways from post-incident firefighting repairs to precise prevention, supporting the development of an efficient, green, and safe expressway network.
This Paper “A multi-criteria decision framework for selecting preventive maintenance measures on asphalt pavement: a case study of the Liuzhou North Ring Expressway” was published in the journal Smart Construction .
Citation: Wu Z, Mohd Hasan MR, Sougui OO, Khan D, Wang H, et al. A multi-criteria decision framework for selecting preventive maintenance measures on asphalt pavement: a case study of the Liuzhou North Ring Expressway. Smart Constr. 2026(2):0011, https://doi.org/10.55092/sc20260011 .
Smart Construction
Experimental study
Not applicable
A multi-criteria decision framework for selecting preventive maintenance measures on asphalt pavement: a case study of the Liuzhou North Ring Expressway
16-Jun-2026