Risk Assessment of Crowd Crushing and Tramping Accidents in Urban Rail Transit Station Based on DEA

2015 ◽  
Vol 730 ◽  
pp. 327-330 ◽  
Author(s):  
Zhi Da Jiao ◽  
Chun Hui Gan

Based on the operation and management of station, the research was mainly about the risk assessment method of the crowd crushing and tramping accidents in urban rail transit stations. The indicator system about the crowd crushing and tramping accidents in urban rail transit station was established. The C2R model of data envelopment analysis (DEA) was used in the risk assessment, and the model was solved with MATLAB programming. The result of the analysis is generally consistent with the actual situation.

2012 ◽  
Vol 253-255 ◽  
pp. 1995-2000
Author(s):  
Qiao Mei Tang ◽  
Li Ping Shen ◽  
Xian Yong Tang

large passenger flow is a common condition of urban transit operation, and the station bears the pressure of large passenger flow directly. This paper analyzes the reason for the appearance of large passenger flow and the characteristics of it, discusses the principles and methods that the station can apply under large passenger flow combined with the passenger’s transport process and the operation process.


2021 ◽  
Author(s):  
Yuzhuang Pian ◽  
Jinshuan Peng ◽  
Lunhui Xu ◽  
Pan Wu ◽  
Jinlong Li

CICTP 2019 ◽  
2019 ◽  
Author(s):  
Hanxuan Dong ◽  
Qiangqiang Li ◽  
Xu Qu ◽  
Jian Zhang ◽  
Hanchu Li ◽  
...  

CICTP 2017 ◽  
2018 ◽  
Author(s):  
Gang Ren ◽  
Jia-Jie Chen ◽  
Hui Xue ◽  
Qiu-Yun Jiang ◽  
Chun-Qiang Yuan

2013 ◽  
Vol 330 ◽  
pp. 569-573
Author(s):  
Chen Chen Zhang ◽  
Xu Zhang ◽  
Yan Hui Wang ◽  
Ling Xi Zhu

There are many ticket gates at the subway station. The managers are quite careful about the load degree of the ticket gates. This paper studies two different methods to calculate the load degree of the ticket gates. One is based on the station ticket gates group as the research object, and the other one is based on the volume of passenger flow passing in and out of the station as the research object. Then we use the data investigated at Chaoyangmen station in Beijing to test and verify both of the methods. At last, we can get the conclusion that we can get the same result by the two methods, but the method of based on the volume of passenger flow passing in and out of the station is more reasonable.


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