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Detection method of urban rail transit passenger congestion based on convolutional neural network

A technology of urban rail transit and convolutional neural network, applied in the direction of neural learning method, biological neural network model, neural architecture, etc., can solve the problems of low accuracy and low efficiency, achieve high accuracy, reduce the amount of calculation, and feature The effect of extracting effect compared to

Active Publication Date: 2021-04-02
JIANGSU AEROSPACE DAWEI TECH CO LTD
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  • Application Information

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Problems solved by technology

[0006] Aiming at the current technical problems, the present invention provides a method for detecting passenger congestion in urban rail transit
This method overcomes the shortcomings of low efficiency and low accuracy in the existing technology, and then realizes accurate estimation of passenger congestion in urban rail transit

Method used

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  • Detection method of urban rail transit passenger congestion based on convolutional neural network
  • Detection method of urban rail transit passenger congestion based on convolutional neural network
  • Detection method of urban rail transit passenger congestion based on convolutional neural network

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0042] figure 1 The present invention provides a convolutional neural network-based method for detecting passenger congestion in urban rail transit.

[0043] Such as figure 1 As shown, the present invention provides a kind of urban rail transit passenger congestion degree detection method based on convolutional neural network, and described method comprises:

[0044] Step S1: Divide the entire running time of urban rail transit into N running time periods, and perform M times of sampling for each time period to obtain the total sampled monitoring image X IN , compared with collecting a single image or multiple frames of images, the detection accuracy of the subsequent congestion degree is improved.

[0045] According to the running time of urban rail transit, divide N running time periods, including at least four time periods of morning, noo...

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Abstract

The invention discloses a method for detecting passenger congestion in urban rail transit based on a convolutional neural network. The method includes dividing the entire running time of urban rail transit into N running time segments, and performing M times of sampling for each time segment , to obtain the total sampled monitoring image X IN ; Use the first feature extraction module and the second feature extraction module to monitor the image X IN Carry out feature extraction to obtain the corresponding feature vectors in the running time of urban rail transit, which is used to indicate the passenger congestion degree of urban rail transit; set the passenger congestion degree detection module, input the output of the second feature extraction module to the passenger congestion degree detection module, estimate Passenger congestion degree; define a loss function, take into account the gap between two adjacent congestion degree levels, optimize the gap between the output congestion level and the actual congestion level, and improve the detection accuracy.

Description

technical field [0001] The invention relates to a method for detecting the degree of passenger congestion, in particular to a method for detecting the degree of passenger congestion in urban rail transit based on a convolutional neural network. Background technique [0002] With the improvement of living standards, urban rail transit has become the main means of travel for urban residents. Since urban rail transit is usually located in a closed underground or elevated track, the area of ​​the station hall is relatively limited. When the peak passenger flow arrives, the influx of a large number of passengers will easily cause congestion in the station hall and channel blockage, which will easily cause large-scale group safety accidents, resulting in bad social influence. Therefore, a convenient and efficient method is needed to obtain the passenger flow distribution in real time, monitor the passenger flow status of the station, provide strong technical support for passenger...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/53G06V10/40G06N3/045G06F18/22
Inventor 钱智荣潘蔚李家洪王佳毅
Owner JIANGSU AEROSPACE DAWEI TECH CO LTD
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