Simulation analysis of passengers' rescheduling strategies in metro station under COVID-19

ABSTRACT

The spread of COVID-19 has a great impact on public transport which is closely related to social life. As an essential carrier of the cities, metro has become an important object of concern during the epidemic. Due to the high infection risk of COVID-19 in public space, it is necessary to quantitatively evaluate and perform corresponding epidemic control measures on reducing public health risks in metro station. In this paper, three strategies of passenger rescheduling, i.e. controlling the flows of inbound and outbound passengers in the station, setting route guidance in the crucial areas and shortening the interval time of train, are simulated and analyzed based on Anylogic. The performances of different strategies are characterized and evaluated by the important parameters, which include local passengers' density, inbound and outbound time. Finally, the optimization experiments based on an objective function are carried out to obtain the best strategy combination considering passengers' health safety and travel efficiency. The crucial areas with high density are obtained from the simulation results of the initial model. The three independent strategies are helpful in reducing the maximum passengers' density and average travel time. The optimization results of strategy combination and the specific parameters of each strategy are obtained by the final simulation experiment. The research findings are important reference to enhance the present health risk management level and provide specific measures of passenger organization in metro station under COVID-19.