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A bottleneck identification method for track network congestion based on percolation theory

A technology of seepage theory and network congestion, applied in data processing applications, instruments, calculations, etc., can solve problems such as few bottleneck identification, lack of dynamic bottleneck analysis, etc., to achieve the effect of improving operational efficiency

Inactive Publication Date: 2020-06-02
BEIHANG UNIV
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Problems solved by technology

[0006] Most of the existing research on track bottleneck identification focuses on the analysis and identification of station static bottleneck characteristics, lacks the analysis of dynamic bottlenecks caused by changes in passenger flow, and rarely involves bottleneck identification at the network level

Method used

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  • A bottleneck identification method for track network congestion based on percolation theory
  • A bottleneck identification method for track network congestion based on percolation theory
  • A bottleneck identification method for track network congestion based on percolation theory

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Embodiment Construction

[0023] The present invention will be further elucidated below in conjunction with the accompanying drawings and examples. The present invention provides a kind of track network congestion bottleneck identification method based on seepage theory, and described method step is as follows:

[0024] 1. Abstract the track network into a directed topological graph:

[0025] The P-space method in the complex network model construction method is used to construct the track network model, that is, track stations are regarded as nodes, and if two stations have direct lines, then they have edges. The track network used in this example is the Beijing track network, and its topology is as follows figure 1 shown.

[0026] 2. Select the full load rate of the section as the characterization index of the section state of the track network:

[0027] The calculation method of section full load rate is:

[0028]

[0029] In the formula, l ij Indicates the full load rate of section ij, m in...

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Abstract

The invention discloses a method for identifying rail network congestion bottlenecks based on seepage theory. The method includes the steps: a. Abstract the track network into a directed topology graph; b. Select the interval full load rate as the state representation index; c. Construct a dynamic network based on the percolation theory, that is, a specific full load rate is given at each moment value l, if the interval full load rate is greater than a specific value l, the interval will be deleted; otherwise, it will be retained; d. For the same moment, changing the l value will change the network connectivity; according to the percolation theory, when the second largest connected graph SG in the network The corresponding l value when the scale reaches the maximum is the critical threshold; e. When l takes the critical threshold, the set of intervals removed is the set of possible bottlenecks; change the interval status in this set, if the change of the interval can improve the network condition, then Identified as a congestion bottleneck. The invention can dynamically identify congestion bottlenecks and help operation managers timely adjust departure shifts, intervals, etc., thereby providing efficient and high-quality services to passengers.

Description

technical field [0001] The present invention relates to the fields of rail operation management and big data analysis, in particular to a method for identifying congestion bottlenecks in rail networks based on seepage theory, which can be used to support rail operation management and improve rail transit service levels. Background technique [0002] As an effective way to alleviate urban traffic congestion, rail transit has developed rapidly in recent years. At present, cities in my country's inland are ushering in an upsurge of subway construction. Especially in big cities like Beijing and Shanghai, the rail transit has been continuously improved and developed. The operating line has developed from a single line to a multi-line and gradually entered the network stage, and the level of urban rail transit has been greatly improved. But at the same time, it also attracts a huge passenger flow, especially in the morning and evening peak hours, when the cross-section passenger ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q50/30
CPCG06Q10/063G06Q50/40
Inventor 鲁光泉熊莹王云鹏鹿应荣马晓磊陈鹏丁川
Owner BEIHANG UNIV
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