CN102097006B - Shortest testing mileage acquisition method and device - Google Patents
Shortest testing mileage acquisition method and device Download PDFInfo
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- CN102097006B CN102097006B CN2011100484699A CN201110048469A CN102097006B CN 102097006 B CN102097006 B CN 102097006B CN 2011100484699 A CN2011100484699 A CN 2011100484699A CN 201110048469 A CN201110048469 A CN 201110048469A CN 102097006 B CN102097006 B CN 102097006B
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Abstract
The embodiment of the invention discloses a shortest testing mileage acquisition method and a shortest testing mileage acquisition device, which relate to the field of traffic information processing. Aiming to acquire the shortest testing mileage with relatively higher accuracy, the method provided by the invention is technically characterized by comprising the following steps of: dividing collected road condition data into different types of road condition data according to specified classification conditions; acquiring the road condition data of corresponding types from each type of road condition data until the change rate of a variance of the road condition data of the corresponding types is smaller than a given value; taking the road condition data, acquired when the change rate of the variance of the road condition data of the corresponding types, of the corresponding types as the final sample data of the corresponding types; and acquiring the shortest testing mileage according to the acquired final sample data of each type. The method and the device are applied to the counting and publishing of road traffic information.
Description
Technical field
The present invention relates to the transport information process field, relate in particular to a kind of acquisition methods and device of the shortest test mileage.
Background technology
Floating Car (Float Car Data) technology is one of the advanced technology means of Traffic Information of obtaining that adopted in the international in recent years intelligent transportation system (ITS).Its ultimate principle is: the Floating Car through dense distribution continuous equipment vehicle-bone global positioning system in road network traffic flow is come image data; And according to the data such as vehicle location, direction and velocity information of Floating Car periodic logging in its driving process of gathering; Using relevant computation model and algorithm such as map match, path culculating handles; The position data and the urban road of Floating Car are associated on time and space, finally obtain the traffic congestion information such as driving hourage of Vehicle Speed and the road of road that Floating Car is passed through.
Before adopting relevant computation model and algorithm that the data of gathering are handled, need to confirm supplemental characteristics such as the shortest test mileage.At present, obtain the shortest test stratified random smapling method that mileage adopted, its principle is: overall for one; Its variance be outwardness and can't change, if but total body unit is classified, it is overall promptly to be divided into plurality of sub; Between the unit in each subpopulation is more similar, and the variance of each subpopulation is diminished, and so only needs in subpopulation, to extract the small number of samples unit; Just can represent the characteristic of subpopulation well, thereby improve precision whole overall estimation.Its basic procedure is: according to certain bigger characteristic of observation index influence, the road condition data that the Floating Car of totally collecting is issued is divided into some types; From each type road condition data, randomly draw the road condition data of some; Calculate average, variance, the standard deviation of this road condition data of randomly drawing; When the average of this road condition data of randomly drawing, variance, when standard deviation begins to tend towards stability, obtain the shortest test mileage.
In realizing process of the present invention; The inventor finds to exist at least in the prior art following problem: the initial moment that the average of the road condition data of randomly drawing, variance and standard deviation tend towards stability possibly have nothing in common with each other; The finish time of extracting is not obvious; The different road condition datas that constantly extracted are different, are not sure of the road condition data that extracts constantly according to which this moment and can access the shortest accurately test mileage, reduce the statistical accuracy of the shortest test mileage.
Summary of the invention
Embodiments of the invention provide a kind of acquisition methods and device of the shortest test mileage, can obtain accuracy the shortest higher test mileage.
For achieving the above object, embodiments of the invention adopt following technical scheme:
A kind of acquisition methods of the shortest test mileage comprises:
Class condition is divided into different classes of road condition data with the road condition data of collecting according to the rules;
The road condition data that from the road condition data of each classification, obtains said classification respectively until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting;
The road condition data of the said classification that the rate of change of the variance of the road condition data of said classification is obtained during less than setting is as the final sample data of said classification;
Obtain the shortest test mileage according to the final sample data of obtaining of all categories.
A kind of deriving means of the shortest test mileage comprises:
The data qualification unit, being used for according to the rules, class condition is divided into different classes of road condition data with the road condition data of collecting;
Data capture unit, the road condition data that is used for obtaining said classification respectively from the road condition data of each classification until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting;
Sample is confirmed the unit, and the road condition data of the said classification of being obtained when being used for rate of change with the variance of the road condition data of said classification less than setting is as the final sample data of said classification;
The mileage acquiring unit is used for obtaining the shortest test mileage according to the final sample data of obtaining of all categories.
The acquisition methods and the device of the shortest test mileage that the embodiment of the invention provides; Through class condition according to the rules the road condition data of collecting is divided into different classes of road condition data; The road condition data that from the road condition data of each classification, obtains said classification respectively until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting; And the road condition data of the said classification that the rate of change of the variance of the road condition data of said classification is obtained during less than setting obtains the shortest test mileage as the final sample data of said classification according to the final sample data of obtaining of all categories.Therefore; When the rate of change of the variance of data satisfies rated condition; Just can obtain the shortest test mileage according to the road condition data of current extraction exactly, thereby can carry out the traffic information system assessment more exactly, for the public provides Traffic Information more accurately.
Description of drawings
In order to be illustrated more clearly in the technical scheme of the embodiment of the invention; The accompanying drawing of required use is done an introduction simply in will describing embodiment below; Obviously, the accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills; Under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.
The shortest a kind of schematic flow sheet of testing the acquisition methods of mileage that Fig. 1 provides for the embodiment of the invention;
The shortest a kind of formation synoptic diagram of testing the deriving means of mileage that Fig. 2 provides for the embodiment of the invention.
Embodiment
To combine the accompanying drawing in the embodiment of the invention below, the technical scheme in the embodiment of the invention is carried out clear, intactly description, obviously, described embodiment only is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills are not making the every other embodiment that is obtained under the creative work prerequisite, all belong to the scope of the present invention's protection.
In order to obtain accuracy the shortest higher test mileage, the embodiment of the invention provides a kind of acquisition methods of the shortest test mileage, and is as shown in Figure 1, comprising:
101, class condition is divided into different classes of road condition data with the road condition data of collecting according to the rules;
For example, can from database, obtain the road condition data that Floating Car is collected, according to road chain rank the road condition data that obtains is divided into other road condition data of chain level of not going the same way according to data characteristic.The road condition data that for example, will from database, extract according to road chain rank is divided into road condition datas such as one-level road, secondary road
102, the road condition data that from the road condition data of each classification, obtains said classification respectively until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting;
For example; Such other road condition data of difference random extraction from the road condition data of each classification; The rate of change that satisfies its variance at such other road condition data of current random extraction is during less than the condition of setting, and at this moment, it is stable that the average of road condition data, variance, standard deviation all reach; Be that average, the variance of road condition data, the variation of standard deviation all tend towards stability, stop the calculating and the correlated judgment of the rate of change of extraction, variance such other road condition data.Wherein, this setting can obtain through long-term simulated experiment.
For example; Current from the road condition data of first category the road condition data of random extraction some; Wherein, this some can be to set with reference to obtaining the road condition data amount that the shortest test fare register extracts in the past, with the road condition data of current random extraction as first road condition data.Then, from the road condition data of first category, continue the random extraction road condition data, with the road condition data that continues random extraction and before first road condition data of random extraction as second road condition data.Obtain the isoparametric average of travel speed, running time of first road condition data and second road condition data according to formula
, obtain the variance var (i) of first road condition data and the isoparametric variance var of travel speed, running time (i+1) of second road condition data according to formula
again.Then, obtain the travel speed of second road condition data, the rate of change of the isoparametric variance of running time according to formula
.Whether the rate of change of variance of judging this second road condition data is less than setting.Be not less than setting if judge the rate of change of the variance of this second road condition data; Then continue random extraction road condition data from the road condition data of first category; With the road condition data that continues random extraction and second road condition data as Third Road condition data; Calculate the rate of change of the variance of Third Road condition data according to mode mentioned above, and whether the rate of change of variance of judging these Third Road condition data is less than setting.And the like, during less than setting, stop to extract the road condition data of this first category up to the rate of change of the variance of the road condition data of current all random extraction, finish correlation computations such as variance.
In addition, can set suitable step-length according to the difference of historical data amount, with suitable minimizing computation period.For example, can confirm step-length according to the data volume of the road condition data of Floating Car collection in the database, the data volume that promptly each continuation is extracted from road condition data of all categories.Then, the road condition data that from the road condition data of each classification, obtains said classification respectively at random according to the step-length of confirming until the rate of change of the variance of the road condition data of the said classification of obtaining at random less than setting.For example; Can be behind random extraction first road condition data from the road condition data of first category; Step-length according to setting continues the random extraction road condition data from the road condition data of first category, will continue the random extraction road condition data and first road condition data as second road condition data.
The road condition data of the said classification of 103, the rate of change of the variance of the road condition data of said classification being obtained during less than setting is as the final sample data of said classification;
For example; At the rate of change of the variance of second road condition data less than setting; The rate of change of the variance of promptly obtaining according to said first road condition data and said second road condition data confirms that second road condition data is the final sample data of first category during less than setting.
In addition, in order to guarantee the computational accuracy of variance rate of change, obtain the shortest accurately test mileage; After data extract that can also be in step 102 and correlation computations finish; Continue the random extraction road condition data, and carry out the calculating of the rate of change of variance, if the rate of change of the variance of calculating is still less than setting; Then stop the extraction of road condition data and the correlation computations of variance rate of change, with the road condition data of random extraction in the step 102 as such other final sample data.
For example; At the rate of change of the variance of said second road condition data less than setting; The rate of change of the variance of promptly obtaining according to said first road condition data and said second road condition data is during less than setting; From the road condition data of first category, continue the random extraction road condition data, the road condition data that this continuation is obtained at random and second road condition data calculate the rate of change of the variance of Third Road condition data as Third Road condition data according to method mentioned above; At the rate of change of the variance of Third Road condition data during still less than setting, with the final sample data of second road condition data as first category.If the rate of change of the variance of Third Road condition data is not less than setting, then continue the rate of change of random extraction road condition data, Calculation variance from the road condition data of first category, until the satisfied condition of the rate of change of the variance of calculating less than setting.
104, obtain the shortest test mileage according to the final sample data of obtaining of all categories.
For example; Randomly drawing repeatedly road condition data; When obtaining final sample data of all categories; The data volume summation of final sample data of all categories is the minimum of the road condition data of Floating Car collection and extracts sample size, calculates the shortest test mileage according to the travel speed in the final sample data of obtaining of all categories, running time etc.
Present embodiment carries out process of compilation under the Matlab environment, present embodiment is based on Monte Carlo (Monte Carlo) method to carry out.
The acquisition methods of the shortest test mileage that the embodiment of the invention provides; Through class condition according to the rules the road condition data of collecting is divided into different classes of road condition data; The road condition data that from the road condition data of each classification, obtains said classification respectively until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting; And the road condition data of the said classification that the rate of change of the variance of the road condition data of said classification is obtained during less than setting obtains the shortest test mileage as the final sample data of said classification according to the final sample data of obtaining of all categories.Therefore; When the rate of change of the variance of data satisfies rated condition; Just can obtain the shortest test mileage according to the road condition data of current extraction exactly, thereby can carry out the traffic information system assessment more exactly, for the public provides Traffic Information more accurately.And in the acquisition process of the shortest test mileage, the calculating that independently repeats in a large number respectively increases the simulation number of times simultaneously until thinking that the analog sample data that produced can reflect the characteristic of simulation system under certain precision.And, can reduce manpower and material resources that actual drive test is spent, reduce the time of total system in test process.
With said method accordingly, the embodiment of the invention also provides a kind of deriving means of the shortest test mileage, and is as shown in Figure 2, comprising:
Sample is confirmed unit 203, and the road condition data of the said classification of being obtained when being used for rate of change with the variance of the road condition data of said classification less than setting is as the final sample data of said classification;
Further, said data qualification unit 201 specifically is used for according to road chain rank the road condition data of collecting being divided into other road condition data of chain level of not going the same way.
Further; Said data capture unit 202; Specifically be used for the variance var (i) according to first road condition data, variance var of second road condition data (i+1) and formula
obtain the rate of change of the variance of said second road condition data; The road condition data of said first road condition data for from the road condition data of said classification, obtaining, the road condition data of said second road condition data for from the road condition data of said classification, obtaining, said second road condition data comprises said first road condition data.
Further, said sample confirms that unit 203 specifically comprises:
Rate of change obtains subelement, when being used for rate of change in the variance of said second road condition data less than setting, obtains the rate of change of variance according to the variance of the variance of Third Road condition data and said second road condition data, with the rate of change that obtains as second rate of change; Said Third Road condition data comprise said second road condition data;
Sample is confirmed subelement, is used at said second rate of change during less than setting, with the final sample data of said second road condition data as said classification.
Further, said data capture unit 202 specifically comprises:
Step-length is confirmed subelement, is used for confirming step-length according to the data volume of the road condition data of said collection;
Data are obtained subelement, the road condition data that is used for obtaining said classification respectively from the road condition data of each classification according to said step-length until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting.
The method of work of the deriving means of the shortest test mileage of present embodiment repeats no more at this specifically referring to the described method of Fig. 1.
The deriving means of the shortest test mileage that the embodiment of the invention provides; Through class condition according to the rules the road condition data of collecting is divided into different classes of road condition data; The road condition data that from the road condition data of each classification, obtains said classification respectively until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting; And the road condition data of the said classification that the rate of change of the variance of the road condition data of said classification is obtained during less than setting obtains the shortest test mileage as the final sample data of said classification according to the final sample data of obtaining of all categories.Therefore; When the rate of change of the variance of data satisfies rated condition; Just can obtain the shortest test mileage according to the road condition data of current extraction exactly, thereby can carry out the traffic information system assessment more exactly, for the public provides Traffic Information more accurately.And in the acquisition process of the shortest test mileage, the calculating that independently repeats in a large number respectively increases the simulation number of times simultaneously until thinking that the analog sample data that produced can reflect the characteristic of simulation system under certain precision.And, can reduce manpower and material resources that actual drive test is spent, reduce the time of total system in test process.
One of ordinary skill in the art will appreciate that all or part of flow process that realizes in the foregoing description method; Be to instruct relevant hardware to accomplish through computer program; Described program can be stored in the computer read/write memory medium; This program can comprise the flow process like the embodiment of above-mentioned each side method when carrying out.Wherein, described storage medium can be magnetic disc, CD, read-only storage memory body (Read-Only Memory, ROM) or at random store memory body (Random Access Memory, RAM) etc.
The above; Be merely embodiment of the present invention, but protection scope of the present invention is not limited thereto, any technician who is familiar with the present technique field is in the technical scope that the present invention discloses; Can expect easily changing or replacement, all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion by said protection domain with claim.
Claims (10)
1. the acquisition methods of the shortest test mileage is characterized in that, comprising:
Class condition is divided into different classes of road condition data with the road condition data of collecting according to the rules, and said road condition data is a travel speed;
The road condition data that from the road condition data of each classification, obtains said classification respectively until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting;
The road condition data of the said classification that the rate of change of the variance of the road condition data of said classification is obtained during less than setting is as the final sample data of said classification;
Obtain the shortest test mileage according to the final sample data of obtaining of all categories.
2. method according to claim 1 is characterized in that, said class condition according to the rules is divided into different classes of road condition data with the road condition data of collecting and comprises:
According to road chain rank the road condition data of collecting is divided into other road condition data of chain level of not going the same way.
3. method according to claim 1 is characterized in that, the rate of change of variance that obtains the road condition data of said classification comprises:
According to the variance var (i) of first road condition data, variance var of second road condition data (i+1) and formula
obtain the rate of change of said variance for second road condition data; The road condition data of said first road condition data for from the road condition data of said classification, obtaining, the road condition data of said second road condition data for from the road condition data of said classification, obtaining, said second road condition data comprises said first road condition data.
4. method according to claim 3 is characterized in that, the road condition data of the said classification that the rate of change of the variance of said road condition data with said classification is obtained during less than setting comprises as the final sample data of said classification:
At the rate of change of the variance of said second road condition data during less than setting, obtain the rate of change of variance according to the variance of the variance of Third Road condition data and said second road condition data, with the rate of change that obtains as second rate of change; Said Third Road condition data comprise said second road condition data;
At said second rate of change during less than setting, with the final sample data of said second road condition data as said classification.
5. method according to claim 1 is characterized in that, the said road condition data that from the road condition data of each classification, obtains said classification respectively comprises less than setting until the rate of change of the variance of the road condition data of the said classification of obtaining:
Data volume according to the road condition data of said collection is confirmed step-length;
The road condition data that from the road condition data of each classification, obtains said classification according to said step-length respectively until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting.
6. the deriving means of the shortest test mileage is characterized in that, comprising:
The data qualification unit is used for class condition according to the rules the road condition data of collecting is divided into different classes of road condition data, and said road condition data is a travel speed;
Data capture unit, the road condition data that is used for obtaining said classification respectively from the road condition data of each classification until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting;
Sample is confirmed the unit, and the road condition data of the said classification of being obtained when being used for rate of change with the variance of the road condition data of said classification less than setting is as the final sample data of said classification;
The mileage acquiring unit is used for obtaining the shortest test mileage according to the final sample data of obtaining of all categories.
7. device according to claim 6 is characterized in that, said data qualification unit specifically is used for according to road chain rank the road condition data of collecting being divided into other road condition data of chain level of not going the same way.
8. device according to claim 6; It is characterized in that; Said data capture unit; Specifically be used for the variance var (i) according to first road condition data, variance var of second road condition data (i+1) and formula
obtain the rate of change of the variance of said second road condition data; The road condition data of said first road condition data for from the road condition data of said classification, obtaining, the road condition data of said second road condition data for from the road condition data of said classification, obtaining, said second road condition data comprises said first road condition data.
9. device according to claim 8 is characterized in that, said sample confirms that the unit comprises:
Rate of change obtains subelement, when being used for rate of change in the variance of said second road condition data less than setting, obtains the rate of change of variance according to the variance of the variance of Third Road condition data and said second road condition data, with the rate of change that obtains as second rate of change; Said Third Road condition data comprise said second road condition data;
Sample is confirmed subelement, is used at said second rate of change during less than setting, with the final sample data of said second road condition data as said classification.
10. device according to claim 6 is characterized in that, said data capture unit comprises:
Step-length is confirmed subelement, is used for confirming step-length according to the data volume of the road condition data of said collection;
Data are obtained subelement, the road condition data that is used for obtaining said classification respectively from the road condition data of each classification according to said step-length until the rate of change of the variance of the road condition data of the said classification of obtaining less than setting.
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| CN101286270A (en) * | 2008-05-26 | 2008-10-15 | 北京捷讯畅达科技发展有限公司 | Traffic flow forecasting method combining dynamic real time traffic data |
| CN101673463A (en) * | 2009-09-17 | 2010-03-17 | 北京世纪高通科技有限公司 | Traffic information predicting method based on time series and device thereof |
| CN101950477A (en) * | 2010-08-23 | 2011-01-19 | 北京世纪高通科技有限公司 | Method and device for processing traffic information |
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| CN101286269A (en) * | 2008-05-26 | 2008-10-15 | 北京捷讯畅达科技发展有限公司 | Traffic flow forecasting system combining dynamic real time traffic data |
| CN101286270A (en) * | 2008-05-26 | 2008-10-15 | 北京捷讯畅达科技发展有限公司 | Traffic flow forecasting method combining dynamic real time traffic data |
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