CN108389011A - It is a kind of the vehicle that is combined of quadrat method expanded based on big data and tradition possess distribution check modification method - Google Patents
It is a kind of the vehicle that is combined of quadrat method expanded based on big data and tradition possess distribution check modification method Download PDFInfo
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- CN108389011A CN108389011A CN201810428344.0A CN201810428344A CN108389011A CN 108389011 A CN108389011 A CN 108389011A CN 201810428344 A CN201810428344 A CN 201810428344A CN 108389011 A CN108389011 A CN 108389011A
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- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000002715 modification method Methods 0.000 title claims abstract description 13
- 230000011664 signaling Effects 0.000 claims abstract description 14
- 238000012937 correction Methods 0.000 claims abstract description 3
- 238000005070 sampling Methods 0.000 claims description 10
- 238000011835 investigation Methods 0.000 claims description 8
- 238000001514 detection method Methods 0.000 claims description 3
- 239000004744 fabric Substances 0.000 claims description 2
- 230000004807 localization Effects 0.000 claims description 2
- 238000012544 monitoring process Methods 0.000 claims description 2
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- 238000007726 management method Methods 0.000 description 1
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- 230000004048 modification Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
Possess distribution the present invention provides a kind of vehicle being combined based on big data and tradition expansion quadrat method and check modification method, implementation step is as follows：1) family table, people's table and trip table are obtained by resident trip door-to-door survey；2) directly expand sample；3) sample is expanded in combination：Family table is combined to expand sample and possess distribution to vehicle using big data and carries out check amendment；Present invention introduces bayonet data and mobile phone signaling data to carry out data correction, it can more efficiently identify nonlocal vehicle, efficiently solve register vehicle address and the technical problems such as a large amount of nonlocal vehicles can not count in not fully consistent, city, registration authorities' compass of competency limits using address, so that the actual use vehicle total amount in a region is more accurate, so that finally obtained vehicle distribution situation is more accurate.
Description
Technical field
The present invention relates to a kind of vehicles being combined based on big data and tradition expansion quadrat method to possess distribution check amendment side
Method belongs to traffic administration statistical technique field.
Background technology
Resident trip survey is the important measures for solving how to obtain current major urban transport problems basic data.Mainly
Purpose is to provide basic data, work to grasp the trip characteristics of city dweller for the foundation of Urban Traffic Planning model
Achievement directly applies in every real work such as traffic programme, construction, operation, management and decision-making, to be closed for science
The Urban Traffic Planning of reason and policy making, guiding urban transportation benign development provide support.Resident trip survey is most common
Method is door-to-door survey, and working method is that investigator preengages interviewed family in advance, registers one's residence and accesses in the designated time, respondent
It completes to investigate by recalling the register one's residence trip information of the previous day 24 hours of record in detail.Investigation main contents include family's letter
Breath, personal information, personal trip information.Wherein, family information investigation be family's table generally include family number, investigation the date,
Administrative area, street, community, family's coordinate, total population, discontented six years old population, domestic automobile situation etc.；Due to door-to-door survey tissue
Difficulty, sampling rate is generally relatively low, and must carry out tradition to investigation sample data thus expands sample.
Tradition expands quadrat method：1) directly expand sample；2) sample is expanded in combination；3) present situation Model Checking.Expand sample prescription by tradition
Direct expansion sample in method, combination expand sample and the investigation of domestic automobile situation are finally made to form more accurate vehicle and possess distribution.
Traditional combination expands the motor vehicle used in sample and possesses parent data for traffic administration part statistical data, which deposits
In three problems：First, vehicle registration address and use address are not fully consistent, second is that a large amount of other places vehicles are without legally constituted authority in city
Meter, third, being limited according to registration authorities' compass of competency, distributed data granularity is thicker, and most cities are regional-level or entire city
City's only one group of data.
Invention content
Expand the motor vehicle used in quadrat method for existing tradition and possesses defect present in parent statistical data, the present invention
Be designed to provide it is a kind of it is more accurate, the vehicle that quadrat method is combined efficiently expanded based on big data and tradition possess distribution
Check modification method.
Technical scheme is as follows：
It is a kind of the vehicle that is combined of quadrat method expanded based on big data and tradition possess distribution check modification method, the check
The implementation steps of modification method are as follows：
1) family table, people's table and trip table are obtained by resident trip door-to-door survey；The family table includes family's number, investigation day
Phase, street, community, family's coordinate, total population, is discontented with six years old population, domestic automobile situation at administrative area；
2) directly expand sample：The direct expansion sample based on survey sampling rate is carried out to the family table according to the difference of sample and parent；
In door-to-door survey, calculates separately family by family and people and expand spline coefficient and population expansion spline coefficient, wherein spline coefficient=practical amount is expanded at family
÷ sampling samples amounts；Population expands spline coefficient=practical permanent resident population ÷ sampling samples permanent resident populations；
3) sample is expanded in combination：The classification for directly expanding data after sample is modified according to external data source so that the totality after weighting
The overall structure that structure and external data provide is consistent；When sample is expanded in specific combination, expansion sample first is carried out to family table, spline coefficient is expanded at family
It inherits in people's table, expansion sample then is carried out to people's table, population expands spline coefficient followed by holding in trip table, then carried out to trip table
Expand sample；
Wherein, the combination expansion sample of the family table is specially：
A) the direct expansion sample based on family table is as a result, obtain family distribution；
B) it and then to there is vehicle family to carry out expanding sample by Car holding amount obtains vehicle and possesses distribution；
C) distribution is possessed to the vehicle using big data and carries out check amendment, the big data includes mobile phone signaling data and card
Mouth detection data etc.；It is described distribution is possessed to the vehicle using big data to carry out checking modified be as follows：
The first step：The actual use vehicle total amount in a region is obtained using big data；The actual use vehicle in one region is total
Amount is the regular quantity summation for localizing the nonlocal vehicle used and possessing vehicle with local family；The regular localization makes
The quantity of nonlocal vehicle mainly utilizes bayonet data to calculate；Local family possesses the quantity of vehicle from the original system of traffic control department
Count middle acquirement；
Second step：Using the label for whether possessing vehicle in owner information in the mobile phone signaling data, fine granularity layer is obtained
The vehicle of grade possesses distribution to get to area in each subdivision；Then the actual use vehicle total amount in a region is shared each
Area obtains the Vehicle's quantity in area in each subdivision in a subdivision；
Third walks：Possess situation according to vehicle in the family table of resident trip door-to-door survey and carry out expansion sample, calculates area in each subdivision
Expansion spline coefficient, area in the Vehicle's quantity for expanding area in spline coefficient=each subdivision in area/each subdivision in each subdivision
Each vehicle of door-to-door survey possesses quantity.
4th step：It is calculated using the expansion spline coefficient in area in each subdivision and tentatively checks revised vehicle and possess point
Cloth；
D) adjustment ensures that total amount is consistent without vehicle amount amount；It finally obtains the revised vehicle of check and possesses distribution.
Preferably, the region can be the administrative division in a city, county or area.
Preferably, the quantity that the regular nonlocal vehicle for localizing and using is calculated using bayonet data refers to passing through traffic
Administrative department identifies nonlocal vehicle to the data of bayonet monitoring for a long time.
Preferably, the mobile phone signaling data has real-time position information, the institute obtained by the mobile phone signaling data
The vehicle for stating fine granularity level possesses the vehicle distribution for being distributed as actual use address.
Compared with prior art, the present invention advantage is：
1) present invention introduces bayonet data and mobile phone signaling data to carry out data correction, can the significantly more efficient nonlocal vehicle of identification
, efficiently solving vehicle registration address and a large amount of nonlocal vehicles in the not fully consistent, city using address can not count, register
The technical problems such as department's compass of competency limitation so that the actual use vehicle total amount in a region is more accurate, so that most
The vehicle distribution situation obtained eventually is more accurate.
2) present invention obtains fine granularity level using the label for whether possessing vehicle in owner information in mobile phone signaling data
Vehicle possesses distribution, and it is thicker to efficiently solve distributed data granularity in the prior art, and most cities are regional-level or entire
The technical bottleneck of the only one group data in city.
3) present invention utilizes the real-time position information of mobile phone signaling data so that the vehicle distribution situation of acquisition is more smart in real time
Really.
Description of the drawings
Fig. 1 expands the vehicle that quadrat method is combined based on big data and tradition and possesses distribution check modification method
Specific implementation mode
With reference to specific embodiment, invention is further explained, but does not limit the invention to these tools
Body embodiment.One skilled in the art would recognize that present invention encompasses may include in Claims scope
All alternatives, improvement project and equivalent scheme.
It elaborates below in conjunction with the accompanying drawings to embodiments of the present invention.This method is a kind of based on big data and tradition
Expand the vehicle that quadrat method is combined and possess distribution check modification method, the implementation steps of modification method are as follows：
1) family table, people's table and trip table are obtained by resident trip door-to-door survey；The family table includes family's number, investigation day
Phase, street, community, family's coordinate, total population, is discontented with six years old population, domestic automobile situation at administrative area；
2) directly expand sample：The expansion sample that total amount is carried out according to the difference of sample and parent carries out the family table to be based on survey sampling
Rate directly expands sample；In door-to-door survey, calculates separately family by family and people and expand spline coefficient and population expansion spline coefficient, wherein family is expanded
Spline coefficient=practical amount ÷ sampling samples amounts；Population expands spline coefficient=practical permanent resident population ÷ sampling samples permanent resident populations；
3) sample is expanded in combination：The classification for directly expanding data after sample is modified according to external data source so that the totality after weighting
The overall structure that structure and external data provide is consistent；When sample is expanded in specific combination, expansion sample first is carried out to family table, spline coefficient is expanded at family
It inherits in people's table, expansion sample then is carried out to people's table, population expands spline coefficient followed by holding in trip table, then carried out to trip table
Expand sample；
Wherein, family table pack expansion sample is specially：
A) the direct expansion sample based on family table is as a result, obtain family distribution；
B) it and then to there is vehicle family to carry out expanding sample by Car holding amount obtains vehicle and possesses distribution；
C) distribution is possessed to the vehicle using big data and carries out check amendment, the big data includes mobile phone letter and bayonet detection
Data etc.；It is described to check modified be as follows：
The first step：A region, which is obtained, using big data actually uses vehicle total amount；The region can be a city, county or area
Administrative division；Region actual use vehicle total amount is that the regular nonlocal vehicle used that localizes possesses vehicle with local family
Quantity summation；The regular nonlocal vehicle used that localizes mainly passes through long-time testing number using vehicle supervision department
According to nonlocal vehicle is identified, the quantity of the regular nonlocal vehicle for localizing and using such as is calculated using bayonet data；Local family
The quantity for possessing vehicle is obtained from traffic control department raw statistical data.
Second step：Using the label for whether possessing vehicle in owner information in the mobile phone signaling data, fine granularity layer is obtained
The vehicle of grade possesses distribution to get to area in each subdivision；Then a region actual use vehicle total amount is shared each
Area obtains the vehicle in area in each subdivision and possesses total amount in subdivision；The mobile phone signaling data has real-time position information, therefore
It is actually to actually use the vehicle distribution of address that the vehicle that the data obtain, which possesses distribution,.
Third walks：Possess situation according to vehicle in the family table of resident trip door-to-door survey and carry out expansion sample, calculates area in each subdivision
Expanding spline coefficient=vehicle in area possesses total amount in each subdivision/, each vehicle of door-to-door survey in area possesses quantity in respectively segmenting.
4th step：Revised vehicle is calculated using the expansion spline coefficient in area in each subdivision and possesses distribution；
D) no vehicle amount amount is finally adjusted, ensures that total amount is consistent.
As it appears from the above, although the present invention is illustrated with reference to limited embodiment and attached drawing, belonging to the present invention
Have can carrying out various modifications and deform from this record per capita for usual knowledge in field.Other embodiment and power as a result,
Sharp claim belongs to scope of the claims with equivalent.
Claims (4)
1. a kind of vehicle being combined based on big data and tradition expansion quadrat method is possessed distribution and checks modification method, feature exists
In：The implementation steps for checking modification method are as follows：
1) family table, people's table and trip table are obtained by resident trip door-to-door survey；The family table includes family's number, investigation day
Phase, street, community, family's coordinate, total population, is discontented with six years old population, domestic automobile situation at administrative area；
2) directly expand sample：The direct expansion sample based on survey sampling rate is carried out to the family table according to the difference of sample and parent；
In door-to-door survey, calculates separately family by family and people and expand spline coefficient and population expansion spline coefficient, wherein spline coefficient=practical amount is expanded at family
÷ sampling samples amounts；Population expands spline coefficient=practical permanent resident population ÷ sampling samples permanent resident populations；
3) sample is expanded in combination：The classification for directly expanding data after sample is modified according to external data source so that the totality after weighting
The overall structure that structure and external data provide is consistent；When sample is expanded in specific combination, expansion sample first is carried out to family table, spline coefficient is expanded at family
It inherits in people's table, expansion sample then is carried out to people's table, population expands spline coefficient followed by holding in trip table, then carried out to trip table
Expand sample；
Wherein, the combination expansion sample of the family table is specially：
A) the direct expansion sample based on family table is as a result, obtain family distribution；
B) it and then to there is vehicle family to carry out expanding sample by Car holding amount obtains vehicle and possesses distribution；
C) distribution is possessed to the vehicle using big data and carries out check amendment, the big data includes mobile phone signaling data and card
Mouth detection data；It is described distribution is possessed to the vehicle using big data to carry out checking modified be as follows：
The first step：The actual use vehicle total amount in a region is obtained using big data；The actual use vehicle in one region is total
Amount is the regular quantity summation for localizing the nonlocal vehicle used and possessing vehicle with local family；The regular localization makes
The quantity of nonlocal vehicle mainly utilizes bayonet data to calculate；Local family possesses the quantity of vehicle from the original system of traffic control department
Count middle acquirement；
Second step：Using the label for whether possessing vehicle in owner information in the mobile phone signaling data, fine granularity layer is obtained
The vehicle of grade possesses distribution to get to area in each subdivision；Then the actual use vehicle total amount in a region is shared each
Area obtains the Vehicle's quantity in area in each subdivision in a subdivision；
Third walks：Possess situation according to vehicle in the family table of resident trip door-to-door survey and carry out expansion sample, calculates area in each subdivision
Expansion spline coefficient, area in the Vehicle's quantity for expanding area in spline coefficient=each subdivision in area/each subdivision in each subdivision
Each vehicle of door-to-door survey possesses quantity.
4th step：It is calculated using the expansion spline coefficient in area in each subdivision and tentatively checks revised vehicle and possess point
Cloth；
D) adjustment ensures that total amount is consistent without vehicle amount amount；It finally obtains the revised vehicle of check and possesses distribution.
2. a kind of vehicle being combined based on big data and tradition expansion quadrat method is possessed distribution check and repaiied according to claim 1
Correction method, it is characterised in that：The region can be the administrative division in a city, county or area.
3. a kind of vehicle being combined based on big data and tradition expansion quadrat method according to claim 1 or 2 possesses distribution
Check modification method, it is characterised in that：It is described to calculate the regular quantity of nonlocal vehicle used that localizes using bayonet data and be
Refer to and nonlocal vehicle is identified to the data of bayonet monitoring for a long time by vehicle supervision department.
4. a kind of vehicle being combined based on big data and tradition expansion quadrat method according to claim 1 or 2 possesses distribution
Check modification method, it is characterised in that：The mobile phone signaling data has real-time position information, passes through the mobile phone signaling data
The vehicle of the obtained fine granularity level possesses the vehicle distribution for being distributed as actual use address.
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| CN201810428344.0A CN108389011A (en) | 2018-05-07 | 2018-05-07 | It is a kind of the vehicle that is combined of quadrat method expanded based on big data and tradition possess distribution check modification method |
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| CN201810428344.0A CN108389011A (en) | 2018-05-07 | 2018-05-07 | It is a kind of the vehicle that is combined of quadrat method expanded based on big data and tradition possess distribution check modification method |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110363483A (en) * | 2019-07-22 | 2019-10-22 | 西南交通大学 | A kind of expansion sample check method based on shared platform shipping trip data |
| CN111340058A (en) * | 2018-12-19 | 2020-06-26 | 中铁第四勘察设计院集团有限公司 | Multi-source data fusion-based traffic distribution model parameter rapid checking method |
| CN116170761A (en) * | 2023-04-25 | 2023-05-26 | 北京城建交通设计研究院有限公司 | Method and system for comprehensive sample expansion and check of mobile phone signaling data |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006115260A1 (en) * | 2005-04-25 | 2006-11-02 | Intellectual Property Bank Corp. | Device for automatically creating information analysis report, program for automatically creating information analysis report, and method for automatically creating information analysis report |
| EP2770489A1 (en) * | 2011-10-21 | 2014-08-27 | Toyota Jidosha Kabushiki Kaisha | Data recording device for vehicle |
| CN105844031A (en) * | 2016-03-29 | 2016-08-10 | 东南大学 | Mobile phone positioning data based urban traffic corridor identification method |
| CN107704976A (en) * | 2017-11-06 | 2018-02-16 | 东南大学 | Urban family transportation emission forecasting of discharged quantity method based on resident trip survey |
| CN107958031A (en) * | 2017-11-20 | 2018-04-24 | 上海市城市建设设计研究总院（集团）有限公司 | Resident trip OD distribution extracting methods based on fused data |
-
2018
- 2018-05-07 CN CN201810428344.0A patent/CN108389011A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2006115260A1 (en) * | 2005-04-25 | 2006-11-02 | Intellectual Property Bank Corp. | Device for automatically creating information analysis report, program for automatically creating information analysis report, and method for automatically creating information analysis report |
| EP2770489A1 (en) * | 2011-10-21 | 2014-08-27 | Toyota Jidosha Kabushiki Kaisha | Data recording device for vehicle |
| CN105844031A (en) * | 2016-03-29 | 2016-08-10 | 东南大学 | Mobile phone positioning data based urban traffic corridor identification method |
| CN107704976A (en) * | 2017-11-06 | 2018-02-16 | 东南大学 | Urban family transportation emission forecasting of discharged quantity method based on resident trip survey |
| CN107958031A (en) * | 2017-11-20 | 2018-04-24 | 上海市城市建设设计研究总院（集团）有限公司 | Resident trip OD distribution extracting methods based on fused data |
Non-Patent Citations (2)
| Title |
|---|
| 彭泽宇: "居民出行调查数据组合扩样方法及评价研究", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 * |
| 李元: "基于多源大数据的居民出行调查校核体系研究", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111340058A (en) * | 2018-12-19 | 2020-06-26 | 中铁第四勘察设计院集团有限公司 | Multi-source data fusion-based traffic distribution model parameter rapid checking method |
| CN111340058B (en) * | 2018-12-19 | 2022-03-29 | 中铁第四勘察设计院集团有限公司 | Multi-source data fusion-based traffic distribution model parameter rapid checking method |
| CN110363483A (en) * | 2019-07-22 | 2019-10-22 | 西南交通大学 | A kind of expansion sample check method based on shared platform shipping trip data |
| CN110363483B (en) * | 2019-07-22 | 2022-05-03 | 西南交通大学 | Sample expansion and checking method based on shared platform freight trip data |
| CN116170761A (en) * | 2023-04-25 | 2023-05-26 | 北京城建交通设计研究院有限公司 | Method and system for comprehensive sample expansion and check of mobile phone signaling data |
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