Estimating long-term impacts of tunnel infrastructure development on urban sustainability using granular computing

Abstract

The rapid growth of metro construction causes adverse effects and even threats; thus, the sustainability assessment becomes extremely important but complex. A novel framework integrating System Dynamics (SD) and Granular Computing (GrC) is proposed to estimate the long-term impacts of tunnel infrastructure development on urban sustainability. An integrated system, consisting of social, economic, and environmental sub-systems, is developed to model urban sustainability. A comprehensive method that integrates Analytic Hierarchy Process (AHP) and entropy weighting methods is proposed to provide a more reliable and objective way to sort information and identify the weight of each criterion. The SD model is established to interpret the relationships of the sub-systems and predict future development. The GrC approach is employed to model and reveal the uncertainties in the SD model and improve reliability. A project case is selected to verify the proposed approach. The results show that the economic system (S2) has better performance than the other two systems, namely social (S1) and environmental systems (S3), which indicates the development of metro lines can boost economic growth. The long-term impact of tunnel infrastructure development on urban sustainability fluctuates over time. The developed approach can be used as a decision tool to assess and estimate the long-term impacts of tunnel infrastructure development on urban sustainability with the consideration of uncertainties in factor measurement and provide decision support for enhancing sustainable urban development.