Toward energy-efficient urban rail transit with capacity constraints under a public health emergency

Urban rail transit (URT) plays a pivotal role in mitigating urban congestion and emissions, positioning it as a sustainable transportation alternative. Nevertheless, URT’s function in transporting substantial numbers of passengers within confined public spaces renders it vulnerable to the proliferation of infectious diseases during public health crises. This study proposes a decision support model that integrates operational control strategies pertaining to passenger flow and train capacity utilization, with an emphasis on energy efficiency within URT networks during such crises. The model anticipates a URT system where passengers adhere to prescribed routes, adhering to enhanced path flow regulations. Simultaneously, train capacity utilization is intentionally limited to support social distancing measures. The model’s efficacy was assessed using data from the COVID-19 outbreak in Xi’an, China, at the end of 2021. Findings indicate that focused management of passenger flows and specific risk areas is superior in promoting energy efficiency and enhancing passenger convenience, compared to broader management approaches.