Evaluation of construction progress of smart highway: a Bayesian network model

Accurate progress control is essential for intelligent highway construction, where the integration of advanced electromechanical equipment, digital technologies, and complex construction interfaces makes traditional progress evaluation methods insufficient. To address this issue, this study proposes a progress evaluation framework tailored to the characteristics of intelligent highway projects. Based on the analysis of project progress factors and construction management requirements, a multi-dimensional indicator system is established to capture both schedule performance and technology-specific construction characteristics. The proposed framework combines expert judgment and quantitative evaluation to support a more comprehensive assessment of construction progress. Using actual project data from an intelligent highway construction case, the model is applied to evaluate the progress status of different construction stages and identify key factors influencing schedule deviation. The results show that the proposed method can effectively reflect the real progress condition of intelligent highway construction and provide actionable support for project managers in making timely corrective decisions. Compared with conventional progress evaluation approaches, the proposed framework is more suitable for intelligent highway projects because it accounts for their technological complexity and management characteristics. This study offers a practical evaluation tool for progress monitoring and contributes to improving the precision and adaptability of intelligent highway construction management.