Analysis method of congestion degree of rail transit station platform

Abstract

In order to grasp the actual congestion level, travel safety and improve the management level of urban rail transit station, and study the analysis method of platform passenger congestion, this paper uses video technology to obtain the location distribution of passengers at Xi’dan station of Beijing Metro, and studies the distribution process and law of waiting passengers. Firstly, the individual and group behaviors of passengers on the platform are studied, and the actual distribution of passengers in a waiting period is selected to facilitate the division of the platform area; Based on the clustering analysis of density, Density-based clustering analysis (DBSCAN) algorithm can cluster the distribution data of passengers on the platform to realize the density division of the data set, which can effectively solve the clustering problem of the data set with uneven density distribution. Through the visualization of clustering results, it can reflect the aggregation and distribution characteristics of passenger group behavior to a certain extent.