CN104766469B - Urban traffic flow tide simulating analysis based on big data analysis - Google Patents
Urban traffic flow tide simulating analysis based on big data analysis Download PDFInfo
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- 238000004458 analytical method Methods 0.000 title claims abstract description 22
- 238000007405 data analysis Methods 0.000 title claims abstract description 18
- 238000013461 design Methods 0.000 claims abstract description 7
- 238000005094 computer simulation Methods 0.000 claims abstract description 5
- 230000007547 defect Effects 0.000 description 4
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- 238000004088 simulation Methods 0.000 description 4
- 238000006467 substitution reaction Methods 0.000 description 4
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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Abstract
The invention discloses it is a kind of based on big data analysis urban traffic flow tide simulating analysis, including, establish Hive sheet formats；Industrial computer is captured and arrived after car data, and the car data of crossing that industrial computer is captured is saved in the first database according to car data initial data tableau format is crossed；The day data of past one that timing preserves to the first database daily is analyzed, and analyze data is saved in into the second database according to data results tableau format, meanwhile, record number of each place as beginning and end；Data are taken out in the data results table preserved from the second database to combine data using the set time as time granularity, the dynamic simulation vehicle start-stop route evolution on GIS according to time shaft；According to the result of step 4 by analyzing generation design sketch or statistical form, so as to draw the conclusion suggestion of urban traffic flow tide.Realize reduction resources costs and ensure the advantages of data are accurate.
Description
Technical field
The present invention relates to intelligent transportation field, in particular it relates to a kind of urban traffic flow tide based on big data analysis
Simulating analysis.
Background technology
At present, with the continuous expansion of China's city size and being continuously increased for the size of population, substantial amounts of residential quarters with
Between the groundwork region of city, between old town and Xincheng District etc., can all occur in morning, evening peak period obvious " tide "
Phenomenon；Morning, a large amount of vehicle crowds are pooled on major trunk roads to enter towards workspace from respective settlement through minor road
Hair；Afternoon, these stream of people's wagon flows return to residence according to former route, have thereby resulted in the unbalanced phenomena of period bidirectional traffics.
This " tide " phenomenon in each city includes multiple start-stop regions, each not phase of stream of people's wagon flow scale in each region
Together, and with urban construction scale and population increase, the start-stop region that " tide " phenomenon is related to also slowly is changing.With
Toward by manual research, mathematical modeling, forecasting traffic flow or traffic simulation software mode to traffic flow " tide " discriminatory analysis, this
A little modes all existing defects from resources costs, time efficiency, data accuracy, especially with the expansion of city size, this
A little defects can also highlight.
It is existing by manual research, mathematical modeling, forecasting traffic flow or traffic simulation software mode to traffic flow " tide "
Discriminatory analysis, these modes all existing defects from resources costs, time efficiency and data accuracy, is advised especially with city
The expansion of mould, these defects can also highlight.It is specific as follows：
1) manual research needs to expend ample resources, and as this investigation work of urban development may need again
Expansion, and the time cycle is longer.
2) mathematical modeling is typically to be drawn a conclusion under relative ideal state, deviation be present for data result authenticity.
3) forecasting traffic flow is generally analyzed using flow collection data, and analysis result is mainly used in traffic
In terms of judgement, such as congestion, slow, unimpeded, but it can not judge for tide initiation region.
4) traffic simulation needs mass data to support, and realizes that " tide " phenomenon emulates by simulation software internal algorithm
And analysis.For this mode firstly the need of mass data, big data needs user's advanced processing, and workload is larger.In simulation software
Algorithms realize that effect and truth can also have deviation.
The content of the invention
It is an object of the present invention in view of the above-mentioned problems, propose a kind of urban traffic flow tide based on big data analysis
Simulating analysis, to realize reduction resources costs and ensure the advantages of data are accurate.
To achieve the above object, the technical solution adopted by the present invention is：
A kind of urban traffic flow tide simulating analysis based on big data analysis, including Step 1: establish Hive tables
Form, Hive are Tool for Data Warehouse, are specially：Established car data raw data table；Establish data results table；
Arrived Step 2: industrial computer is captured after car data, by industrial computer capture to cross car data former according to car data is crossed
Beginning data tableau format is saved in the first database；
Step 3: the day data of past one that timing preserves to the first database daily is analyzed, according to setting time section
Data analysis to crossing car data raw data table, each car start-stop route information in setting time section is recorded, and will analysis
Data are saved in the second database according to data results tableau format, meanwhile, each place is recorded as beginning and end
Number；
Step 4: data are taken out out of the second database preserves data results table is used as time grain using the set time
Degree combines data, and according to time shaft, dynamic simulation vehicle start-stop route evolution, pass course color thickness are anti-on GIS
The quantity by the route vehicle is reflected, each place is reflected by vehicle fleet by shade；
Step 5: according to the result of step 4 by analyzing generation design sketch or statistical form, so as to draw urban traffic flow
The conclusion suggestion of tide.
Preferably, the car data raw data table excessively, including number plate species+brand number, excessively mistake car time, car place
Numbering and picture path.
Preferably, the data results table, including number plate species+brand number, by starting time, by terminal
Time, starting point location number, terminal location number, starting point crosses car picture path and terminal crosses car picture path.
Preferably, the step 4 takes out data with the set time out of the second database preserves data results table
Set time during data are combined as time granularity is set as 10 minutes.
Preferably, the setting time section in the step 3 is urban transportation morning peak period and urban transportation evening peak
Period.
Technical scheme has the advantages that：
Technical scheme, using the existing relevant database of big data technical substitution, realize that data on flows is united
Meter analysis.And bayonet system is combined, new application is put forward to the number-plate number for capturing vehicle, found by analyzing the number-plate number
Traffic flow tide migrates relation, and most this tide relation of migrating is presented on GIS and realizes traffic simulation effect at last.Reach reduction
Resources costs and the guarantee accurate purpose of data.
Below by drawings and examples, technical scheme is described in further detail.
Brief description of the drawings
Fig. 1 is the urban traffic flow tide simulating analysis effect based on big data analysis described in the embodiment of the present invention
Schematic diagram；
Fig. 2 is the urban traffic flow tide simulating analysis statistics based on big data analysis described in the embodiment of the present invention
Vehicle flowrate tendency chart；
Fig. 3 a and Fig. 3 b are the urban traffic flow tide simulation analysis based on big data analysis described in the embodiment of the present invention
The statistical chart of method；
Fig. 4 is based on the urban traffic flow tide simulating analysis that big data is analyzed and inspection described in the embodiment of the present invention
Rope flow chart.
Embodiment
The preferred embodiments of the present invention are illustrated below in conjunction with accompanying drawing, it will be appreciated that described herein preferred real
Apply example to be merely to illustrate and explain the present invention, be not intended to limit the present invention.
A kind of urban traffic flow tide simulating analysis based on big data analysis, including Step 1: establish Hive tables
Form, Hive are Tool for Data Warehouse, are specially：Established car data raw data table；Establish data results table；
Arrived Step 2: industrial computer is captured after car data, by industrial computer capture to cross car data former according to car data is crossed
Beginning data tableau format is saved in the first database；
Step 3: the day data of past one that timing preserves to the first database daily is analyzed, according to setting time section
Data analysis to crossing car data raw data table, each car start-stop route information in setting time section is recorded, and will analysis
Data are saved in the second database according to data results tableau format, meanwhile, each place is recorded as beginning and end
Number；
Step 4: data are taken out out of the second database preserves data results table is used as time grain using the set time
Degree combines data, and according to time shaft, dynamic simulation vehicle start-stop route evolution, pass course color thickness are anti-on GIS
The quantity by the route vehicle is reflected, each place is reflected by vehicle fleet by shade；
Step 5: according to the result of step 4 by analyzing generation design sketch or statistical form, so as to draw urban traffic flow
The conclusion suggestion of tide.
Preferably, car data raw data table, including number plate species+brand number, excessively mistake car time, car location number excessively
With picture path.
Data results table, including number plate species+brand number, by starting time, by terminal time, starting point
Point numbering, terminal location number, starting point cross car picture path and terminal crosses car picture path.
Step 4 takes out data out of the second database preserves data results table and is used as time grain using the set time
Set time during degree combines data is set as 10 minutes.
Setting time section in step 3 is urban transportation morning peak period and urban transportation evening peak period.
Specially：
（1）Establish Hive table structures：
1）Car data raw data table T_PASSEDCAR was established, including：Number plate species+brand number, the car time is spent,
Cross car location number, picture path.The table preserves early, evening peak data on the day of only preservation.Early peak time section is 5:00-9:00,
The evening peak period is 16:00-20:00.Such as：02V8G53（02 represents vehicle below private savings 7, and V8G53 represents local car
）, 20150307101011, ad000001, http://pic.snap.device/20150307/ad000001/02V8G53_
20150307101011.jpg。
2）Data results table T_ANALYSIS_RESULT, field include：Number plate species+brand number, by starting point
Time, car picture path is crossed by terminal time, starting point location number, terminal location number, starting point, terminal crosses car picture road
Footpath.Such as：02V8G53,20150307101011,20150307102011, ad000001, ad000002, http://
pic.snap.device/20150307/ad000001/02V8G53_20150307101011.jpg, http://
pic.snap.device/20150307/ad000002/02V8G53_20150307102011.jpg。
（2）Industrial computer is captured and arrived after car data, is put in storage and preserved according to T_PASSEDCAR format designs.
（3）Timing is analyzed the day data of past one daily, according to early peak time section 5:00-9:00 and the evening peak period
16:00-20:00 pair of T_PASSEDCAR data analysis, record each car start-stop route information in two periods, including start-stop
Picture is captured in time, start-stop place, start-stop.Analyze data is put in storage according to T_ANALYSIS_RESULT format designs and preserved, together
When, record number of each place as beginning and end.
（4）Data are taken out from T_ANALYSIS_RESULT to combine data using 10 minutes as time granularity, according to the time
Axle dynamic simulation vehicle start-stop route evolution on GIS.The number of the route vehicle is passed through in the reflection of pass course color thickness
Amount, each place is reflected by vehicle fleet by shade.
（5）By analyzing generation design sketch, statistical form, conclusion suggestion.As shown in Figure 1, Figure 2, shown in Fig. 3 a and Fig. 3 b.
Suggestion can be drawn the following conclusions according to Fig. 1, Fig. 2, Fig. 3 a and Fig. 3 b：
1st, A → E sections morning peak period vehicle flowrate is larger, it is proposed that sets tide direction traffic single file car in the morning peak period
Road, ensure A → E directions the coast is clear.
2nd, A → F sections morning peak period vehicle flowrate is larger, due to stroke farther out, it is proposed that tide is increased to section bus, and
Public transport priority signal scheme is set, ensures A → F directions the coast is clear.
3rd, B → F, D → E sections are increased month by month by January to historical data analysis in March, vehicle flowrate, it is proposed that relevant department
Prioritization scheme is formulated in anticipation in advance.
As shown in figure 4, after establishing emulation to urban traffic flow tide according to the technical program, can be according to demand to emulation
Database carry out retrieval and inquisition.
The technical program combines existing bayonet system, on the basis of cost is reduced, ensure accuracy, is analyzed using big data
Realize that traffic flow tidal phenomena emulates.Emulated with respect to other traffic flow tides, this method simulation efficiency is higher, and cost is lower, imitates
It is very time-consuming to greatly shorten.
This programme combines generalized information system using the traditional relevant database of big data technical substitution, the policy effect made
More directly perceived, more fitting is actual.Generalized information system is GIS-Geographic Information System.
Finally it should be noted that：The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention,
Although the present invention is described in detail with reference to the foregoing embodiments, for those skilled in the art, it still may be used
To be modified to the technical scheme described in foregoing embodiments, or equivalent substitution is carried out to which part technical characteristic.
Within the spirit and principles of the invention, any modification, equivalent substitution and improvements made etc., it should be included in the present invention's
Within protection domain.
Claims (3)
1. a kind of urban traffic flow tide simulating analysis based on big data analysis, it is characterised in that including including step
First, Hive sheet formats are established, Hive is Tool for Data Warehouse, is specially：Established car data raw data table；Establish data point
Analyse result table；Wherein, car data raw data table was established, including：Number plate species, brand number, spend the car time, cross car place
Coding, picture path；Data results table, field include：Number plate species, brand number, by starting time, by terminal
Time, starting point location number, terminal location number, starting point crosses car picture path, terminal crosses car picture path；
Arrived Step 2: industrial computer is captured after car data, the car data excessively that industrial computer is captured is according to car data original number excessively
The first database is saved according to tableau format；
Step 3: the day data of past one that timing preserves to the first database daily is analyzed, according to setting time section to mistake
The data analysis of car data raw data table, each car start-stop route information in setting time section is recorded, and by analyze data
Second database is saved according to data results tableau format, meanwhile, record time of each place as beginning and end
Number；
Will using the set time as time granularity Step 4: taking out data out of the second database preserves data results table
Data combine, the dynamic simulation vehicle start-stop route evolution on GIS according to time shaft, pass course color thickness reflection warp
The quantity of the route vehicle is crossed, each place is reflected by vehicle fleet by shade；
Step 5: according to the result of step 4 by analyzing generation design sketch or statistical form, so as to draw urban traffic flow tide
Conclusion suggestion.
2. the urban traffic flow tide simulating analysis according to claim 1 based on big data analysis, its feature exist
Data are taken out out of the second database preserves data results table in, the step 4 time granularity is used as using the set time
Set time during data are combined is set as 10 minutes.
3. the urban traffic flow tide simulating analysis based on big data analysis according to any one of claim 1 to 2,
Characterized in that, the setting time section in the step 3 is urban transportation morning peak period and urban transportation evening peak time
Section.
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| CN105427602B (en) * | 2015-12-16 | 2018-04-27 | 浙江宇视科技有限公司 | A kind of vehicle driving theme determines method and device |
| CN105916111A (en) * | 2016-04-15 | 2016-08-31 | 上海河广信息科技有限公司 | Time statistical system and method for route |
| CN109829023A (en) * | 2019-01-18 | 2019-05-31 | 苏州维众数据技术有限公司 | A kind of four-dimensional spacetime GIS-Geographic Information System and its construction method |
| CN111653091B (en) * | 2020-05-13 | 2021-06-18 | 深圳市山行科技有限公司 | Tidal traffic jam identification method based on high-grade data and floating car data |
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