Original scientific paper
https://doi.org/10.7307/ptt.v30i5.2715
Experimental Study for Optimizing Pedestrian Flows at Bottlenecks of Subway Stations
Wei Luo
orcid.org/0000-0001-5953-5382
; Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology
Lishan Sun
; Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology
Liya Yao
; School of Mechanical and Vehicular Engineering, Beijing Institute of Technology
Qingsheng Gong
; Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology
Jian Rong
; Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology
Abstract
In subway stations, bottlenecks are the narrowed areas that reduce pedestrian flows in channels. Because pedestrians at bottlenecks are forced to dense together, bottlenecks decrease flow efficiency and pedestrians’ transfer comfort and may trigger serious crowd disasters such as trampling. This study used pedestrian experiments to investigate the methods of optimizing pedestrian traffic at bottlenecks of subway stations. Three optimization measures were proposed and evaluated by analyzing the characteristics of pedestrian flows, including efficiency, smoothness, and security. In this paper, setting the rear sides of the bottleneck entrance as straight and surface funnel shapes is called straight funnel shape and surface funnel shape, respectively. Setting a column at a bottleneck is called the column obstacle. The results showed that when efficiency or security come first, a column on the left is recommended; when comfort comes first, a concave funnel is recommended; when comprehensiveness is prioritized, a column on the left is recommended. Moreover, the larger the volume, the optimization is more obvious. Although many bottlenecks cannot be prevented when subway stations are constructed, the proposed optimization measures may help ease their adverse effects by improving facility efficiency, smoothness, and security, and by providing recommendations for designing and managing subway stations.
Keywords
Hrčak ID:
207746
URI
Publication date:
31.10.2018.
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