On the Use of a Pedestrian Simulation Model with Natural Behavior Representation in Metro Stations

Rapid urbanization in many large cities in China makes metro station an integral part of metropolitan people's daily life. High density of crowds in metro stations would cause serious congestion problems and pose threats to pedestrian safety. Because of the heterogeneous and complex properties of pedestrians, traditional approaches face difficulties in predicting future pedestrian flow patterns. The use of agent-based simulation approach makes it possible to naturally reproduce various pedestrian behaviors in different scenarios. This paper presented an agent-based microscopic pedestrian simulation model—CityFlow, which was proved to be flexible in revealing most important pedestrian behaviors in metro stations by several simulation cases. The model applications can provide implications in evaluation of design proposals of metro facilities.