Simulating pedestrians’ spatio-temporal distribution in underground spaces

Abstract

Many pedestrians gather in underground spaces that connect railway stations. Determining pedestrians’ movements is important for evaluating and improving the actual underground space. Using pedestrian traffic survey data, we propose a model for simulating pedestrians’ spatio-temporal distribution (SD) in an underground space. Through simulation, we obtain pedestrians’ time-specific positions in the network, enabling us to study the interactions between people and the underground space with regard to crowds. We define several crowd condition variables as indicators of the degree of relative congestion in terms of safety, efficiency, and comfort, and we examine some environmental and individual factors’ influence on crowd variations. We then construct a method for assessing the degree of relative congestion in underground spaces with dynamic pedestrian crowds and perform two case studies to examine the effects of proposed flow control plans on actual underground pedestrian systems.