吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (1): 100-107.doi: 10.13229/j.cnki.jdxbgxb201601015

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Identification of pedestrian crowding degree in metro transfer hub based on normal cloud model

ZHOU Ji-biao1, CHEN Hong2, YAN Bin3, ZHANG Wen4, FENG Wei2   

  1. 1.School of Transportation, Ningbo University of Technology, Ningbo 315211, China;
    2.School of Highway, Chang'an University, Xi'an 710064, China;
    3.Department of Driver Training Service, Bengbu Automobile Sergeant's School, Bengbu 233011, China;
    4.Guangzhou Urban Planning & Design Survey Research Institute, Transport Planning & Design Studio, Guangzhou 510060, China
  • Received:2014-09-24 Online:2016-01-30 Published:2016-01-30

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Abstract: In order to solve the problems of fuzziness and randomness in the division of congestion state in metro transfer hub, an identification method of pedestrian crowding degree factor is proposed based on normal cloud model. First, the connotation and the measure standard of the pedestrian crowding degree are analyzed, and according to their boundary value under different service level the digital characteristics of the cloud are calculated. Second, the cloud synthesis theory is applied to establish the template cloud corresponding to different service levels, and the survey data (pedestrian speed, flow etc.) are input into the cloud generator in order to set up the identification cloud model. Third, according the definition of cloud similarity, the similarity between the identified cloud and the template cloud in the infrastructure (e.g. channel, stairs) is calculated. Moreover, the crowding degree is defined independently, which is described in a quantificational level under the state of crowding degree in the metro transfer hub, and the method to identify the pedestrian crowding degree is given. The method is verified by a case study in a metro transfer hub in Xi'an. Results show that the pedestrian crowding degree in the channel 100.095, which is in the crowding state, the pedestrian crowding degree in the stair is 100.273, which is also in the crowded state. This method can not only accurately identify the crowded state quantificationally, but also reflect the change process of pedestrian crowding degree, which has strong practicality.

Key words: engineering of communications and transportation system, crowding degree, cloud model, metro transfer hub, infrastructure

CLC Number: 

  • U491
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