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Method for conducting public transportation planning by utilizing mobile communication data mining

A data mining and mobile communication technology, applied in the field of mobile communication, can solve the problems of data information lag, difficult to guarantee accuracy, long investigation cycle, etc.

Inactive Publication Date: 2015-06-24
ZTE CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Long-term OD observation of passenger flow is quite complicated and requires a lot of manpower, material and financial resources, and the accuracy is difficult to guarantee, the survey cycle is also long, and the data information is relatively lagging behind
[0003] At present, the penetration rate of mobile phones has been greatly improved, reaching more than 80 units / 100 people in most provinces and cities. It is estimated that by 2015, the penetration rate of mobile phones in China will reach and exceed 100 units / 100 people. Related methods of public transportation planning based on big data mining technology

Method used

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  • Method for conducting public transportation planning by utilizing mobile communication data mining
  • Method for conducting public transportation planning by utilizing mobile communication data mining
  • Method for conducting public transportation planning by utilizing mobile communication data mining

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0077] Embodiment 1, urban bus route planning.

[0078] According to the user's daily parking point analysis (staying in different location areas for different time periods), describe the user's daily life trajectory (see figure 2 ). Analyze the characteristics (repetition rate, dispersion) of all user life trajectories in the target area (such as cities, districts and counties, etc.), and obtain the densely populated areas and the direction of the flow of people in different time periods. (See image 3 ) Plan the bus routes according to the distribution of the flow of people, and set the bus stops at the points with dense flow of people. The specific implementation steps are as follows:

[0079] 201: Obtain the mobile signaling data of the user terminal within the statistical period in the statistical area from the operator server, and obtain the location update information of the user terminal according to the mobile signaling data of the user terminal;

[0080] The sou...

Embodiment 2

[0105] Embodiment 2, bus route optimization.

[0106] Bus companies should add routes and increase frequency in densely populated areas. The addition of lines allows passengers to take buses bound for different locations at the same station, which not only facilitates passengers, but also brings more tourists to the buses. The specific implementation steps are as follows:

[0107] 301: Obtain mobile signaling data of the user terminal within the statistical period in the statistical area from the operator server, and obtain location update information of the user terminal according to the mobile signaling data of the user terminal;

[0108] The sources of mobile signaling data collected include but are not limited to mobile signaling data, mobile phone GPS positioning information, etc.

[0109] Obtain the mobile signaling update data of the city (statistical area can be set) in the first half of the year (statistical period can be set) from the operator, and obtain user loca...

Embodiment 3

[0132] Embodiment three, bus scheduling optimization.

[0133] Count the time passengers stay at the station, that is, the waiting time. For stations with a large flow of people and a long stay time, it is necessary to increase the bus frequency. Increasing the number of shifts can greatly shorten the waiting time of passengers, which can not only save time for passengers, but also improve the competitiveness of buses. The starting model can also be adjusted according to the characteristics of the user group. The specific implementation steps are as follows:

[0134] 401: Obtain mobile signaling data of the user terminal within the statistical period in the statistical area from the operator server, and obtain location update information of the user terminal according to the mobile signaling data of the user terminal;

[0135] The sources of mobile signaling data collected include but are not limited to mobile signaling data, mobile phone GPS positioning information, etc.

...

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Abstract

Bus planning method using mobile communication data mining, comprising: obtaining mobile signaling data of user terminals in a statistical area and in a statistical time segment from a carrier server, and obtaining location update information of the user terminals based on the mobile signaling data of the user terminals; based on the location update information of the user terminals, obtaining a spatio-temporal data set of a user corresponding to each user terminal respectively; based on the spatio-temporal data set of each user, obtaining a people resident point set and a people travel characteristic; and based on the people resident point set and the people travel characteristic, performing bus planning. Also provided is an apparatus for implementing the method.

Description

technical field [0001] The invention relates to the application of big data mining in the field of mobile communication in the planning of bus routes in smart cities. According to the results of big data analysis, combined with the overall planning scheme of urban public transport and the traffic conditions of existing public transport, suggestions are given for improvement of urban public transport line planning and public transport line scheduling. Background technique [0002] The forecast of passenger flow and passenger flow distribution in public transport planning is the basis of planning schemes, and whether the forecast results are scientific and reasonable will ultimately affect the benefit evaluation of the scheme. Passenger flow OD survey ("O" comes from English ORIGIN, pointing out the starting point of the trip, "D" comes from English DESTINATION, pointing out the destination of the trip.) That is, traffic starting and ending point survey is also called OD traff...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G08G1/00G08G1/01G06F17/30H04W4/02
CPCG06F16/90G08G1/0125G08G1/20G06Q10/047G06Q10/0631G06Q50/30H04W4/023
Inventor 刘淑霞
Owner ZTE CORP
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