• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.415-420
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• 2020

Crowd flows occur in metropolitan railway transit stations, terminals, multiple buildings, and stadiums and are important in ensuring the safety as well as smooth flow of pedestrians in these facilities. In this study, the author developed a new computational analysis method for crowd flow dynamics and applied it to models of transit connecting paths. Using the analysis method, the potential value of the exit was assigned the smallest value, and the potential value of the surrounding grids gradually increased to form the overall potential map. A pathline map was then constructed by determining the direction vector from the grid with large potential value to the grid and small potential. These pathlines indicate basic routes of passenger flow. In all models of the analysis object, the pedestrians did not move to the first predicted shortest path but instead moved using alternative paths that changed depending on the situation. Even in bottlenecks in which pedestrians in both directions encountered each other, walking became much smoother if the entry time difference was dispersed. The results of the analysis show that a method for reducing congestion could be developed through software analysis such as passenger flow analysis without requiring hardware improvement work at the railway station.