Rail transit passenger flow distribution predicting model building method and predicting method

A passenger flow distribution and prediction model technology, applied in the field of rail transit, can solve difficult problems such as passenger flow distribution prediction, and achieve the effects of reducing the difficulty of acquisition, enhancing practicability, and enhancing applicability

Active Publication Date: 2013-07-17
BEIJING JIAOTONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Obviously, the above method is difficult to be used for the prediction of passenger flow distribution under the changes of land use type and intensity arou...

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  • Rail transit passenger flow distribution predicting model building method and predicting method
  • Rail transit passenger flow distribution predicting model building method and predicting method
  • Rail transit passenger flow distribution predicting model building method and predicting method

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Embodiment Construction

[0021] refer to Figure 1-2 Examples of the present invention will be described.

[0022] In order to make the above objects, features and advantages more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0023] Such as figure 1 As shown, a method for establishing a rail transit passenger flow distribution prediction model includes the following steps:

[0024] S1. Select the corresponding influencing factors from indicators such as the amount of attraction generated by the orbital station, the category of the station, the topology of the network, and related operating parameters.

[0025] S2. Construct the utility function of the model, the structure of which is shown in the following formula:

[0026] V ij =f(C ij ,D j ,AOD ij ,XZ,GM,k)

[0027] Among them, V ij Select the utility function whose starting point is station i and the end point is station j; C ij is ...

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Abstract

The invention discloses a rail transit passenger flow distribution predicting model building method and a predicting method. The model building method includes the following steps: introducing the discrete variable for describing site property and scale, building a utility function of a passenger flow distribution predicting model by combining rail site generation attraction quantity, a network topological structure and relevant operation parameters, utilizing an individual representing method to convert the site generation attraction quantity belonging to aggregate data into disaggregate data and utilizing the maximum likelihood estimation to demarcate a passenger flow distribution predicting model. A rail transit passenger flow distribution predicting method is further disclosed. The two methods have the advantages of being low in data acquisition difficulty, high in practicability, accurate in prediction and the like.

Description

technical field [0001] The invention relates to the technical field of rail transit, in particular to a rail transit passenger flow distribution prediction model establishment and prediction method. Background technique [0002] In recent years, with the continuous expansion of the rail transit network, the interaction between lines has gradually increased. At the same time, as the new rail transit line is connected to the existing road network and put into use, the network topology and land use around the station will change, and the spatial and temporal distribution of passenger flow will also be re-arranged. The influence of the distribution, as well as providing data support for the urban rail transit operation management department to reasonably plan the train operation plan and formulate the passenger flow induction strategy, the passenger flow distribution prediction under the new line access condition is essential. However, due to the lack of historical passenger fl...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/30
Inventor 姚恩建杨扬王大蕾张永生
Owner BEIJING JIAOTONG UNIV
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