Modeling effect of information percolation on pedestrian counter flow with a multi-grid model

Abstract

Abstract The transition from free to congested state in counter flow scenario could sometime result in serious crushing disasters. To avoid such disasters, crowd management strategies are usually applied. Thus, it is important to understand nonlinear pedestrian counter flow dynamics considering guiders’ management, especially the information percolation process. In the present paper, the information percolation process is built into a multi-grid model. In the model, those information unknown pedestrians in a channel move towards right where some dangerous situation occurs. The guiders intend to deliver this information to the pedestrians to make them move to the opposite direction, however, the effect is influenced by the interaction between the guiders and the normal pedestrians. Simulation results of the model show that the model can reproduce perfectly stopped phase and the phase transition from congestion to free flow state. The results also indicate that the number of guiders is the most important factor to determine the formation and desperation of perfectly stopped phase. Besides, guider influence radius and crowd density have considerable influence on pedestrian dynamics. If the influence radius is less than a threshold, guiders could not make all pedestrians change their direction. Higher crowd density has a higher probability of forming the perfectly stopped phase. If we add the number of guiders according to the pedestrian number, the phase transition can be avoided. To make pedestrians quickly switch their movement direction to the opposite side of dangerous direction, guiders should adopt a proper strategy. Movement could increase the rate of information percolation, especially in the low density and few guiders scenario. This study may be helpful for the management of pedestrian counter flow in an emergency.