Exploring the behavior of self-organized queuing for pedestrian flow through a non-service bottleneck

Abstract

The self-organized queuing behavior becomes increasingly common at the non-service bottlenecks with no physical constraints, such as an exit of a room, the entrances of an escalator or a narrow passage in subway stations. How the others queue and the level of the social order are vital concerns for crowds to regulate their own behavior. It is necessary to examine the significance of orderly behavior in facilitating the traffic at bottleneck. Unlike the traditional queuing theory methods, an agent-based cellular automata that allows agents to perceive and act from the order of the social environment in real time has been presented. The simulated results show an extremely high-ordered environment is not favorable for the collective egress of human crowds as expected, because the severer unfairness of the entering process and local congestion at the queue end greatly reduce pedestrians’ average speeds during the whole process. A moderate orderly environment can be more beneficial for alleviating the local jams, enhancing the outflow rate at exit, and shortening the egress time. The results of the simulation model are compared with a controlled queuing experiment. The flow–density, flow–velocity relationships as well as the time-varied perception of the group order can be reproduced by simulations.