Macroscopic crowd panic quantification model of crowd evacuation based on information entropy

Abstract

To solve the existing problem that panic impact on crowd evacuation is less quantitatively considered at the crowd evacuation model, this contribution proposes a panic quantification model based on Aw-Rascle. This model introduces information entropy in information theory to reflect the degree of confusion in crowds, and maps individual velocity distribution into information entropy graph. The information entropy graph reflects the degree of panic for certain time in the entire evacuation space. To validate the panic propagation model, numerical simulation is conducted based on a case study of the Mecca Hajj stampede in 2015. The simulation results show that when the number of people increases, the degree of crowd panic increases, making the evacuation process more chaotic and the information entropy value increasing.