【摘 要】
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Pedestrian safety issues are a huge challenge for urban rail transit(URT),identifying its risk status is a critical step in URT management.In this paper,a risk index classification method based on nor
【机 构】
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Ningbo University of Technology Ningbo University
论文部分内容阅读
Pedestrian safety issues are a huge challenge for urban rail transit(URT),identifying its risk status is a critical step in URT management.In this paper,a risk index classification method based on normal-cloud theory is developed,which aims at quantitatively classifying the fuzzy and random states of pedestrian crowds in the URT systems.Firstly,the digital features of the normal-cloud are calculated in accordance with the thresholds of different levels of safety.And then,the template clouds at different levels of risk are established by cloud synthesis theory.Secondly,collected data are inputted into a cloud generator to prepare the identifying cloud.Thirdly,the similarity between the identifying cloud and the template clouds are calculated for different facilities(e.g.,channel,stairway,and platform).Last but not the least,data from the Gulou station in Ningbo is collected as method verification.Results show that the proposed normal-cloud model is feasible and effective to classify the risk with experimental survey data,the values of risk index for the channel,stairway and platform are 4.0,8.3 and 2.8,respectively.These results match the real situation in Ningbo rail transit.
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