Traffic cell division method based on online car-hailing retrieval request data

A technology for requesting data and traffic cells, applied in the field of intelligent transportation, it can solve the problems of strong subjectivity, inability to guarantee the homogeneity of traffic cells, and manual intervention for parameter setting. large amount of effect

Pending Publication Date: 2019-12-06
SOUTHEAST UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing methods for dividing traffic areas mainly include traditional methods based on resident survey data, basic road network structure, administrative divisions, grid geometric patterns, etc. Althou

Method used

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[0037] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings. 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.

[0038] The core idea of ​​the present invention is to use the storability of the online car-hailing retrieval request data, by mining the homogeneity between the drop-off locations requested by the search in the same order, and based on the grid method, the drop-off location and its location Finally, through the improved k-means++ algorithm, the distance between the grids and the homogeneity index are comprehensively considered, and the grids in the area to be divided are clustered to obtain traffic communities with more similar internal properties.

[0039] Such as figure 1 Shown is a schematic flow diagram of the method of the pr

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Abstract

The invention discloses a traffic cell division method based on online car-hailing retrieval request data. The traffic cell division method is based on the theory that each trip has a unique trip purpose, utilizes the storability of online car-hailing retrieval request data, considers the homogeneity between drop-off places requested to be retrieved in the same order, based on rasterization, applies an improved K-means + + algorithm, and divides traffic cells through a large amount of real and objective online car-hailing retrieval request data. According to the traffic cell division method, the traffic cells can be divided more reasonably, so that the difference between the traffic cells is maximum, and high homogeneity is kept in the traffic cells.

Description

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Claims

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Application Information

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Owner SOUTHEAST UNIV
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