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Bus get-on/off site identification and examination method based on multi-source data mining

A technology of multi-source data and inspection methods, applied in the direction of traffic flow detection, etc., can solve the problems of low accuracy of identification and discrimination, inability to meet engineering application requirements, narrow application range, etc.

Active Publication Date: 2019-06-18
HUAQIAO UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The technical problem to be solved by the present invention is to provide a multi-source data mining bus stop identification and inspection method, which can solve the common bus stop identification and transfer behaviors existing in the prior art The accuracy of recognition and discrimination is low, the scope of application is narrow, and it cannot meet the needs of actual engineering applications

Method used

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  • Bus get-on/off site identification and examination method based on multi-source data mining
  • Bus get-on/off site identification and examination method based on multi-source data mining
  • Bus get-on/off site identification and examination method based on multi-source data mining

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0274] This example uses the IC card swiping data and conventional bus satellite positioning information data in xx city in January 2018 as an example to analyze and identify and inspect the boarding and alighting stations of conventional buses. There are a total of 45,032,397 records of conventional bus swiping card data, and the data files are stored in the dmp format of the Oracle database. , the data file consists of 22 fields (as shown in Table 3); the BRT bus card data is provided by the xx City Transportation Bureau, which is the bus card data of xx city in January 2018, with a total of 13,268,640 records, and the data file adopts the dmp format of the Oracle database Storage, the data file consists of 5 fields (as shown in Table 4); the subway card swiping data is provided by the xx City Transportation Bureau, which is the bus swiping data of xx city in January 2018, with a total of 3,252,269 records, and the data file adopts the dmp format of the Oracle database For s...

Embodiment 2

[0298] This example uses the IC card swiping data and conventional public bus satellite positioning information data in xx city in January 2018 as an example to analyze, and identifies the boarding station (such as figure 2 ). There are a total of 45,032,397 records of conventional bus card swiping data, the data files are stored in dmp format, and the data files are composed of 11 fields (as shown in Table 10); the satellite positioning information data has a total of 311,080,161 records, the data files are stored in dmp format, and the data files are composed of 22 Field composition (see Table 11).

[0299] Table 10 Composition table of bus credit card data

[0300]

[0301]

[0302] Table 11 Data composition table of bus satellite positioning information

[0303]

[0304]

[0305] According to the actual situation of xx city, this example sets N jcz = 1; T qx = 20 (seconds); T ys = 1800 (seconds); T jl = 20 (seconds); T one = 120 (seconds); T two = 300 ...

Embodiment 3

[0311] This example uses the IC card swiping data and conventional public bus satellite positioning information data in January 2018 in xx city as an example to analyze, and performs alighting station matching on the records of known boarding stations of conventional buses (such as image 3 ). There are a total of 45,032,397 records of conventional bus card swiping data, and the data files are stored in the dmp format of the Oracle database. , the data file consists of 22 fields (as shown in Table 15); the BRT bus card data is provided by the xx City Transportation Bureau, which is the bus card data of xx city in January 2018, with a total of 13,268,640 records, and the data file adopts the dmp format of the Oracle database Storage, the data file consists of 5 fields (as shown in Table 16); the subway card swiping data is provided by the xx City Transportation Bureau, which is the bus swiping data of xx city in January 2018, with a total of 3,252,269 records, and the data file...

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Abstract

The invention provides a bus get-on / off site identification and examination method based on multi-source data mining. The method comprises steps that based on IC card swiping and operating vehicle data of conventional buses, IC card swiping passenger get-on site identification based on clustering and correlation analysis is performed; according to the IC card swiping and operating vehicle data ofconventional buses, BRT and subways, IC card swiping passenger travel chain get-off site identification based on the conventional buses, the BRT and the subways are performed; data of unidentified get-off sites is subjected to IC card swiping passenger get-off site identification based on historical ride records; the data of the re-unidentified get-off sites is subjected to IC card swiping passenger get-off site identification based on Bayesian posterior maximum likelihood estimation; the data of the matched get-on site is subjected to IC card swiping passenger get-on site identification basedon the paired sample t test; the data of the matched get-off site is subjected to IC card swiping passenger get-off site identification based on transfer behavior identification. The method has advantages of wide application scope and high site identification accuracy.

Description

technical field [0001] The invention relates to the field of bus information data processing, in particular to a multi-source data mining bus stop identification and inspection method. Background technique [0002] With the upgrading and renewal of public transportation-related technologies and equipment, the popularization of bus card systems, and the increase in the use of IC cards, a large number of passenger IC card swiping data and satellite positioning information data provide feasibility for the analysis of public transportation data. Based on the complete travel data of passengers obtained from multi-source data mining of passenger IC card swiping data, the OD matrix of public transport passengers can be quickly and dynamically obtained, and these OD matrices can be used for bus route adjustment and network optimization, The design of connecting lines, research on transfer policies, and passenger flow characteristics (passenger flow corridors, distribution centers, p...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/01
Inventor 王成崔紫薇陈德蕾
Owner HUAQIAO UNIVERSITY
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