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A bus route adjustment method based on historical passenger flow

A technology of bus routes and adjustment methods, applied in the field of data analysis, can solve the problem of high time complexity, and achieve the effect of improving bus scheduling and scientific and rational operation

Active Publication Date: 2022-06-07
HUAQIAO UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, affected by the amount of data, the time complexity of traditional clustering methods is often very high, and it needs to be improved according to the characteristics of the data in order to better meet the actual analysis needs

Method used

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  • A bus route adjustment method based on historical passenger flow
  • A bus route adjustment method based on historical passenger flow
  • A bus route adjustment method based on historical passenger flow

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0098] Take out the historical credit card data of Tangbian and Lvcuo stations in Xiamen City. There are more than 300 credit card data for a single line in a single day. For example, there are 17 lines at Tangbian Station. 5248 entries. The credit card data consists of fields: line number, license plate number, transaction date, credit card number, transaction time, transaction amount, train number, station number, and driving direction. The credit card data is shown in Table 1.

[0099] Table 1: Line history card swiping data

[0100] line number number plate transaction date Swipe card number 651 Fujian DZ9525 20181010 11192285 transaction hour number of trips site number driving direction 25800 Fujian DZ5986 23 0

[0101] Take out the card swiping data of the Tangbian and Lucuo stations during the peak period from 7:00 to 9:30, and count the card swiping amount at 10-minute intervals to obtain the passenger flow of the two s...

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Abstract

The invention relates to a bus line adjustment method based on historical passenger flow. By traversing all lengths of passenger flow time subsequences and using correlation coefficients for clustering, the clustering results form two time series sets, namely positive correlation clusters and Negative correlation clusters represent the line sites with the same riding behavior trend and the line sites with the opposite riding behavior trend respectively. By analyzing the clustering results, the macro passenger travel behavior characteristics between lines and between sites can be obtained. The present invention can not only understand passenger's riding demand, but also help to find stations with the same or similar passenger flow changes, provide a basis for laying out bus lines in a city, setting up new lines, adjusting existing lines, and providing decision support for line adjustments. It can also improve bus scheduling and operate more scientifically and rationally. The invention does not depend on a specific scene, is more general, and can be used in public transportation networks of large and medium cities.

Description

technical field [0001] The invention relates to the technical field of data analysis, and more particularly, to a bus route adjustment method based on historical passenger flow. Background technique [0002] The setting and optimization of the bus network is a complex systematic project, which is often affected by many factors, such as the limitation of objective factors such as hardware infrastructure, and the design defects of the bus network itself, such as unreasonable structure, unbalanced development of the network, The line capacity does not match the passenger flow, etc., and the throughput of the passenger flow is far less than expected. This greatly affects the overall efficiency of urban public transport. Therefore, it is of great significance to excavate the change trend of passenger flow between stations and lines and find the differences, which is of great significance to improve the passenger flow throughput of the entire bus network. [0003] For the resear...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/30
CPCG06Q10/047G06Q50/40Y02T10/40
Inventor 李海波翁邵源陈文韵高悦尔
Owner HUAQIAO UNIVERSITY
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