Study on Critical Density of Percolation in Crowds in Public Areas
| Autor: | Guo Hui, Ying-Hua Song, Wei Lv, Zhi-Wu Lei, Xin-Yao Guo |
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| Rok vydání: | 2020 |
| Předmět: |
050210 logistics & transportation
Computer science business.industry 05 social sciences 01 natural sciences 010305 fluids & plasmas Crowds Artificial Intelligence Data_GENERAL Percolation 0502 economics and business 0103 physical sciences Fluid dynamics Cluster (physics) Computer Vision and Pattern Recognition Statistical physics Artificial intelligence business Software |
| Zdroj: | International Journal of Pattern Recognition and Artificial Intelligence. 34:2059044 |
| ISSN: | 1793-6381 0218-0014 |
| Popis: | The percolation model is an effective tool to solve the problem of fluid flow in the pores; the situation of outsiders crossing the crowd is similar. This paper verifies the obvious percolation phenomenon in the randomly distributed crowd by [Formula: see text] simulation and reveals several characteristics and laws of the crowd percolation phenomena. Studies have shown that sites with different spatial dimensions have different densities of crowd percolation: when the actual density of the crowd is greater than the critical density of the crowd percolation, the outsider is difficult to pass through the crowd; otherwise, the outsider can pass through the crowd easily. Therefore, the critical density of crowd percolation can be one of the indicators of crowd management in public areas, which will provide important guidance for the design of public areas, site selection of public activities and crowd management. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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