Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis
AbstractIn recent years, accidents always happen in confined space such as metro stations because of congestion. Various researchers investigated the patterns of dense crowd behaviors in different scenarios via simulations or experiments and proposed methods for avoiding accidents. In this study, a classic continuum macroscopic model was applied to simulate the crowded pedestrian flow in typical scenarios such as at bottlenecks or with an obstacle. The Lax–Wendroff finite difference scheme and artificial viscosity filtering method were used to discretize the model to identify high-density risk areas. Furthermore, we introduced a contact crowding force test of the interactions among pedestrians at bottlenecks. Results revealed that in the most dangerous area, the individual on the corner position bears the maximum pressure in such scenarios is 90.2 N, and there is an approximate exponential relationship between crowding force and density indicated by our data. The results and findings presented in this paper can facilitate more reasonable and precise simulation models by utilizing crowding force and crowd density and ensure the safety of pedestrians in high-density scenarios. View Full-Text
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Li, X.; Zhou, J.; Chen, F.; Zhang, Z. Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis. Sustainability 2018, 10, 385.
Li X, Zhou J, Chen F, Zhang Z. Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis. Sustainability. 2018; 10(2):385.Chicago/Turabian Style
Li, Xiaohong; Zhou, Jianan; Chen, Feng; Zhang, Zan. 2018. "Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis." Sustainability 10, no. 2: 385.
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