Urban rail transit road network cooperative current limiting method based on data driving

A technology of urban rail transit and current limiting method, applied in the field of collaborative current limiting based on data-driven urban rail transit road network, can solve problems such as lack of scientificity, and achieve the effect of reducing the number of iterations

Active Publication Date: 2019-09-10
BEIJING JIAOTONG UNIV
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  • Summary
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  • Application Information

AI Technical Summary

Problems solved by technology

Station flow limitation is an effective emergency management measure to relieve passenger flow pressure and hub load. At present, in actual operation management, the determination of flow limitation period, flow limitation station and flow limitation intensity usually depends on the experien

Method used

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Example Embodiment

[0114] The embodiments of the present invention are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals indicate the same or similar elements or elements with the same or similar functions. The following embodiments described with reference to the accompanying drawings are exemplary, and are only used to explain the present invention, and cannot be construed as limiting the present invention.

[0115] Those skilled in the art can understand that, unless specifically stated otherwise, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, Integers, steps, operations, ele

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Abstract

The embodiment of the invention provides a data-driven urban rail transit road network collaborative flow limiting method, which comprises the following steps of S1, grading urban rail transit road networks and station evaluation indexes, and identifying a key flow limiting station set; s2, constructing an urban rail transit road network collaborative flow limiting model according to the key flowlimiting station set; s3, Q-based And solving the rail transit road network collaborative flow limiting model by using a leasing learning algorithm, and outputting the flow limiting intensity corresponding to each key flow limiting station. Effective method support is provided for formulation of a passenger flow limiting scheme of the subway station, and effective theoretical basis is provided for formulation of a passenger flow control strategy.

Description

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Claims

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Application Information

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Owner BEIJING JIAOTONG UNIV
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