Track network's crowded bottleneck identification method based on percolation theory

Abstract

The invention discloses a track network's crowded bottleneck identification method based on percolation theory. The method comprises the following steps: a) abstracting a track network as a directed topological map; b) selecting the interval full-load rate as the state characteristic index; c) according to the percolation theory, constructing a dynamic network or rather, giving a specific full-load rate value l at each moment wherein if the interval full-load rate is greater than the specific value of l, then deleting the interval; and keeping the interval if otherwise; d) for the same moment, changing the value l with the result of changing the network connection; based on the percolation theory, when the scale of the second largest communication graph SG in the network reaches the maximum, naming the corresponding value l as the threshold value; and e) determining that the interval set deleted at the threshold value extracted at value l as the possible bottleneck set; changing the interval state of the interval set; and if the changed of the interval can improve the network condition, then, determining the interval as the crowded bottleneck. According to the method of the invention, it is possible to perform dynamic identification to a crowded bottleneck so as to facilitate the adjustment of the bus times and intervals to start the buses by the operation and management personnel and to provide high quality service to passengers accordingly.

Description

technical field [0001] The invention relates to the fields of track operation management and big data analysis, in particular to a method for identifying congestion bottlenecks in track networks based on percolation theory, which can be used to support track operation management and improve track traffic 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 the upsurge of subway construction. Especially in big cities like Beijing and Shanghai, the rail transit has been continuously improved and developed. The operating lines have developed from a single line to multiple lines 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. The cross-section passenger ...

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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

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