An Analysis of Crowds Flow Characteristics by Using Laser Range Scanners

Recently, according to growth and concentration of population in urban area, congested situations at several railway stations in rush hour become a serious social issue. Therefore, designing the station more comfortably for the passengers has been desired. In other words, in order to mitigate the congested situations, a method measuring crowds flow characteristics should be developed. In this paper, we propose a people tracking method for wide and high density situations by using multiple laser range scanners. Additionally, we try to analyze the crowds flow characteristics such as traffic volume, traffic density, degree of intercrossing, velocity, and directionality. Then, we detect several prominently congested areas. In order to evaluate our proposed system, an experiment at Japan railway station was conducted. The accuracy of people tracking shows over 80% in rush hour. Based on the obtained trajectories, the density and direction distribution of the trajectories are calculated by using Kernel Density Estimation method. Furthermore, based on the variance of moving direction and traffic volume, we define a degree of intercrossing in each flow, and then the prominently congested areas are highlighted. Finally, we conclude our proposed system will be efficient to mitigate a congested situation and improve the usability of the public space such as railway station, exhibition hall, or shopping mall.