Modelling and assessing long-term urban transportation system resilience based on system dynamics

Abstract

Urban transportation systems (UTSs) face numerous long-term disturbances, such as climate change, technological innovation, and pandemics, highlighting the need for resilient construction and management. However, current research on this area remains insufficient. Consequently, this paper aims to establish a model for evaluating the long-term resilience of UTSs and identify strategic enhancement methods through simulation. Given the intricate interdependencies among diverse components within UTSs, a dynamic system model tailored for the long-term resilience assessment of UTSs is formulated. This model encompasses four dimensions: environment, infrastructure and equipment, economic, and organization. Within each dimension, critical vulnerability factors responsible for potential disruptions are identified, along with the corresponding reinforcing factors designed to mitigate such vulnerabilities. Leveraging the developed model and data from Singapore's UTS, evolutionary analysis, local sensitivity analysis, global sensitivity analysis using the Monte Carlo simulation, and strategy analysis were conducted. Findings reveal the resilience of Singapore's UTS displays an initial ascending trajectory followed by a subsequent decline, primarily attributed to the diminishing environment resilience. Furthermore, increasing passenger safety awareness and reducing emission factors are paramount factors to enhance UTSs’ long-term resilience. A dynamic model for assessing the long-term resilience of UTSs is created and can be generalized to other cities.