CN101763730A - Traffic road condition information filling method and system - Google Patents
Traffic road condition information filling method and system Download PDFInfo
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- CN101763730A CN101763730A CN200910244141A CN200910244141A CN101763730A CN 101763730 A CN101763730 A CN 101763730A CN 200910244141 A CN200910244141 A CN 200910244141A CN 200910244141 A CN200910244141 A CN 200910244141A CN 101763730 A CN101763730 A CN 101763730A
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Abstract
The invention discloses a traffic road condition information filling method and a system, which relate to the field of traffic information treatment and can improve the accuracy of filling road condition information. The traffic road condition information filling method comprises the following steps: completing vacant data in traffic road condition data according to the historical road condition data; carrying out clustering treatment on all the road condition data of a same road in the same time period for obtaining the road condition change trend, and establishing a road traffic road condition trend mode library; matching the road condition trend of the road in the time period containing the time point t with the road condition change trend of the road in the traffic road condition trend mode library, and calculating the driving speed of the road at the time point t for filling the road condition. The method and the system are applied in the treatment of traffic accident information of an intelligent traffic system.
Description
Technical field
The present invention relates to the transport information process field, relate in particular to a kind of traffic road condition information filling method and system.
Background technology
Advanced transportation information service systems (Advanced Traffic Information System, be called for short ATIS) be on perfect information network basis, by be equipped on the road, on the car, on the transfer stop, on the parking lot and the sensor of forecast center and transmission equipment, obtain all kinds of Real-time Traffic Informations and carry out overall treatment, provide comprehensive, accurate, real-time Traffic Information to society in real time.
The traffic trip person can determine line mode and selection schemer according to these information, and the driving driver also can be by locating and navigational system Dynamic Selection travel route automatically.Advanced transportation information service systems not only for the traffic administration personnel provide in time, transport information accurately, makes traffic management control system can effectively adapt to various traffics, for the planning and the transformation of traffic network ability provides decision support; And help road user effectively to avoid traffic congestion, alleviate the anxiety of blocking up, the factor and the effective traffic capacity of raising road network system thereby the minimizing traffic hazard takes place frequently.
The Floating Car technology is to obtain one of advanced technology means of road real-time road in the international in recent years advanced intelligent traffic system, can be real-time obtain the vehicle average velocity on the road segment segment and the hourage of highway section point-to-point transmission.Yet, because the Floating Car limited amount and the irregularities of travelling make that in the same processing cycle a lot of roads are not covered by Floating Car, morning Floating Car more all the more so.Therefore,, when this information of issue, a lot of these information of road vacancy be will have so, information integrity and availability reduced if do not calculate the road traffic jam situation that Floating Car does not cover.Therefore, in a processing cycle, how the congestion in road information of vacancy being filled up is a problem demanding prompt solution during transport information is handled.
Vacancy congestion in road information filling is to utilize road traffic congestion local correlations in time, and the vacancy data are filled up.Prior art provides a kind of traffic road condition information filling method, and the congestion in road information of vacancy is used in the Floating Car congestion in road information history data, and same road filled up at the mean value of at the same time all travel speeds.
The inventor finds that when realizing technical scheme of the present invention there is following problem at least in prior art road conditions information filling method: though the velocity variations trend of every day is roughly similar, evening peak all has certain delay but the road traffic of every day blocks up early, if use historical Mean Method, bigger error will occur, the data of filling up are not accurate enough.
Summary of the invention
Technical matters to be solved by this invention is to provide a kind of traffic road condition information filling method and system, can improve the accuracy of road condition information filling.
For solving the problems of the technologies described above, traffic road condition information filling method of the present invention and system adopt following technical scheme:
A kind of traffic road condition information filling method comprises:
According to historical road condition data, the data of vacancy in the completion traffic road condition data;
According to same road all road condition datas in the identical time period are carried out the road condition change trend that clustering processing draws, set up road traffic road conditions trend library;
The road condition change trend of this road in the road conditions trend of time point t place road in the time period and the road traffic road conditions trend library is complementary, calculates the described road of time point t as the travel speed of filling up road conditions.
Described according to historical road condition data, the data of vacancy comprise in the completion traffic road condition data:
Read trimestral at least historical road condition data;
The road condition data of previous time point that with road condition data is the time point of vacancy is filled up on the time point that this road condition data is a vacancy;
The time period at mark time point place;
Traffic road condition data after the preservation completion.
Described is to comprise before the road condition data of previous time point of the time point of vacancy is filled up on the time point that this road condition data is a vacancy road condition data:
According to road conditions place time point time division section.
Described basis is carried out the road condition change trend that clustering processing draws to same road all road condition datas in the identical time period, sets up road traffic road conditions trend library and comprises:
Read the traffic road condition data after the completion;
To same road, same date not, the traffic road condition data of identical time period carries out clustering processing, obtains the not same date under the same category, the cluster data of identical time period;
Described cluster data is carried out mean value computation;
The result of mean value computation is carried out curve fitting;
According to the curve-fitting results of the classification of the difference under every road different time sections, set up road traffic road conditions trend library.
Described with time point t place road in the time period road conditions trend and road traffic road conditions trend library in the road condition change trend of this road be complementary, calculate the described road of time point t and comprise as the travel speed of filling up road conditions:
Read real-time traffic road condition data;
Read out all road conditions trend polynomial curves of the road of vacancy road conditions on time point t;
By pattern match the vacancy road conditions on the road are inferred.
After the vacancy road conditions on the road being inferred, comprise by pattern match:
Export complete real-time traffic data.
A kind of traffic road condition information filling system comprises:
The historical data pretreatment unit is used for according to historical road condition data, the data of vacancy in the completion traffic road condition data;
Road conditions trend analysis unit is used for setting up road traffic road conditions trend library according to same road all road condition datas in the identical time period are carried out the road condition change trend that clustering processing draws;
Road conditions are filled up processing unit, are used for the road conditions trend of time point t place road in the time period and the road condition change trend of this road of road traffic road conditions trend library are complementary, and calculate the described road of time point t as the travel speed of filling up road conditions.
Described historical data pretreatment unit comprises:
First read module is used to read trimestral at least historical road condition data;
Fill up module, being used for road condition data is the road condition data of previous time point of the time point of the vacancy time point that to fill up this road condition data be vacancy;
Mark module is used for time period at mark time point place;
Preserve module, be used to preserve the traffic road condition data after the completion.
Described road conditions trend analysis unit comprises:
Second read module is used to read the traffic road condition data after the completion;
The clustering processing module is used for same road, same date not, and the traffic road condition data of identical time period carries out clustering processing, obtains the not same date under the same category, the cluster data of identical time period;
The mean value computation module is used for described cluster data is carried out mean value computation;
Curve fitting module is used for the result of mean value computation is carried out curve fitting;
Library is set up module, is used for the curve-fitting results according to the classification of the difference under every road different time sections, sets up road traffic road conditions trend library.
Described road conditions are filled up processing unit and are comprised:
Third reading delivery piece is used to read real-time traffic road condition data;
The 4th read module is used to read out all road conditions trend polynomial curves of the road of vacancy road conditions on time point t;
Infer module, be used for the vacancy road conditions on the road being inferred by pattern match.
Traffic road condition information filling method that the embodiment of the invention provides and system, at first the Floating Car historical data being carried out absence information replenishes, respectively same road all road condition datas in identical certain period are carried out cluster analysis then, the interior friction speed variation tendency of each time period of setting up all roads has constituted road traffic road conditions trend library.The road conditions trend of road is mated in Traffic Information trend in the use road traffic road conditions trend library and the current slot, infer that the travel speed that this road of current time is as filling up road conditions, make the transport information of the vacancy of inferring more accurate, the accuracy that has improved road condition information filling.
Description of drawings
In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art, the accompanying drawing of required use is done to introduce simply in will describing embodiment below, apparently, 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.
Fig. 1 is the process flow diagram of the embodiment of the invention one traffic road condition information filling method;
Fig. 2 is the structural representation of the embodiment of the invention one traffic road condition information filling system;
Fig. 3 is the process flow diagram of the embodiment of the invention two traffic road condition information filling methods;
Fig. 4 is the structural representation of the embodiment of the invention two traffic road condition information filling systems.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that is obtained under the creative work prerequisite.
The embodiment of the invention provides a kind of traffic road condition information filling method and system, can will improve the accuracy of road condition information filling.
Embodiment one
The embodiment of the invention provides a kind of traffic road condition information filling method, and as shown in Figure 1, this method comprises:
Step S101, according to historical road condition data, the data of vacancy in the completion traffic road condition data;
Step S102, basis are carried out the road condition change trend that clustering processing draws to same road all road condition datas in the identical time period, set up road traffic road conditions trend library;
Step S103, the road condition change trend of this road in the road conditions trend of time point t place road in the time period and the road traffic road conditions trend library is complementary, calculates the described road of time point t as the travel speed of filling up road conditions.
The embodiment of the invention also provides a kind of traffic road condition information filling system, and as shown in Figure 2, this system comprises: historical data pretreatment unit 1, road conditions trend analysis unit 2 and road conditions are filled up processing unit 3.
Historical data pretreatment unit 1 is used for according to historical road condition data, the data of vacancy in the completion traffic road condition data.This unit as input, at first carries out completion to the information of vacancy in the historical Floating Car road condition data with the historical traffic information of accumulation, divides the timing statistics section according to road conditions place time point then.
Wherein, the selection of road comprises the main roads in city, for example all roadway element set of Beijing's backbone, as: know spring road, Xueyuan Road etc.; The value of time point comprises the time cycle for boundary from per 5 minutes of 00:00-23:59, as 08:00,08:05,08:10,08:15 etc., has 288 time points in one day.
For the trend over time of Vehicle Speed on better certain bar road of reflection, all time points in one day are divided into 70 time periods, per 8 time points (promptly 40 minutes) are a time period, time point is staggered simultaneously was present in two continuous time periods, for example: time point 0-7 is the time period 0, time point 4-11 is the time period 1, and time point 8-15 is the time period 2 ... time point 280-287 is the time period 70.
Road conditions trend analysis unit 2 is used for setting up road traffic road conditions trend library according to same road all road condition datas in the identical time period are carried out the road condition change trend that clustering processing draws.This unit carries out cluster analysis to road all road condition datas in identical certain period, calculate the road condition change trend on the road in this section period, finally set up Traffic Information trend library according to the friction speed variation tendency in each time period of all roads.
Road conditions are filled up processing unit 3, are used for the road conditions trend of time point t place road in the time period and the road condition change trend of this road of road traffic road conditions trend library are complementary, and calculate the described road of time point t as the travel speed of filling up road conditions.This unit reads real-time floating car traffic information, scanning road vacancy road condition data, the road conditions trend of road is mated in Traffic Information trend in the use Traffic Information trend library and the current slot, infers that the travel speed that this road of current time is as filling up road conditions.
In embodiments of the present invention, at first, historical road condition data to Floating Car carries out replenishing of absence information, respectively same road all road condition datas in identical certain period are carried out cluster analysis then, merge similar traffic information unit, distinguish dissimilar traffic information unit, the velocity variations trend fitting with these road conditions unit processes is a polynomial curve afterwards, and the friction speed variation tendency in each time period of all roads has constituted road traffic road conditions trend library.The road conditions trend of road is mated in road condition change trend in the use road traffic road conditions trend library and the current slot, infers the travel speed that this road of current time as filling up road conditions, and it is more accurate to make this fill up road conditions.
Complementing method adopts the mode of streamline, and the statistical study of all roads is fulfiled ahead of schedule, and filling up then of vacancy road conditions in the real-time road condition information carried out one by one.
Traffic road condition information filling method that the embodiment of the invention provides and system, at first the Floating Car historical data being carried out absence information replenishes, respectively same road all road condition datas in identical certain period are carried out cluster analysis then, the interior friction speed variation tendency of each time period of setting up all roads has constituted road traffic road conditions trend library.The road conditions trend of road is mated in Traffic Information trend in the use road traffic road conditions trend library and the current slot, infer that the travel speed that this road of current time as filling up road conditions, makes the transport information of the vacancy of inferring more accurate.
Embodiment two
On the basis of embodiment one, further, the embodiment of the invention provides a kind of traffic road condition information filling method, and as shown in Figure 3, this method comprises:
S201, read trimestral at least historical road condition data;
The historical data pretreatment module is carried out the calculating of filling up that there are the vacancy road conditions in time point on each road based on the urban history road condition data more than 3 months of accumulation, promptly reads individual month Floating Car urban history road condition data of n (n 〉=3).
Further, divide the timing statistics section according to road conditions place time point.
Wherein, the selection of road comprises the main roads in city, for example all roadway element set of Beijing's backbone, as: know spring road, Xueyuan Road etc.; The value of time point comprises the time cycle for boundary from per 5 minutes of 00:00-23:59, as 08:00,08:05,08:10,08:15 etc., has 288 time points in one day.
For the trend over time of Vehicle Speed on better certain bar road of reflection, all time points in one day are divided into 70 time periods, per 8 time points (promptly 40 minutes) are a time period, time point is staggered simultaneously was present in two continuous time periods, for example: time point 0-7 is the time period 0, time point 4-11 is the time period 1, and time point 8-15 is the time period 2 ... time point 280-287 is the time period 70.
S202, be unit, begin the road condition data of every road is scanned, find that road conditions be the time point of sky from time point 0 with the sky;
S203, with road condition data be vacancy time point the road condition data of previous time point fill up this road condition data on the empty time point;
To road condition data is empty time point t, fill up the road condition data of the previous time point of this time point at this moment between on the point, finish completion successively to road condition data on all time points of whole day.
The time period at S204, mark time point place;
The time period at mark time point place, a general time point can belong to two continuous time periods, according to sequential, a time point can lay respectively at the back segment of a time period and the leading portion of another time period, for example time point 6 (00:30) is positioned at the back segment of time period 0 (00:00 to 00:40), is positioned at the leading portion of time period 1 (00:20 to 00:55) simultaneously.
Traffic road condition data after S205, the preservation completion;
S206, read the traffic road condition data after the completion;
S207, to same road, same date not, the traffic road condition data of identical time period carries out clustering processing, obtains the not same date under the same category, the cluster data of identical time period;
Comprise 8 time points in each time period, and certain bar road was at corresponding velocity amplitude of each time point of certain day, therefore this road all has 8 velocity amplitudes in each time period of this day, regard these 8 velocity amplitudes as length be a vector (array) of 8, so will there be m vector (array) certain bar road each time period under m date.This length is that vector (array) each time point road corresponding travel speed in this time period of 8 just reflects the velocity variations trend of this road in this period.
For an above-mentioned m data, the present invention distinguishes dissimilar vector (array) and merges similar vector (array) by the cluster analysis in the data mining, and resulting result data (or title pattern) just reflects this road all velocity variations trend in this time period.
The present invention adopts the minimax clustering algorithm to carry out cluster analysis, chooses new initial classes center with the maximum Euclidean distance between the velocity variations trend curve in vector set, carries out pattern with minimum cluster principle and sorts out.
S208, described cluster data is carried out mean value computation;
Not same date time period road conditions under the same category are carried out mean value computation.After the cluster to the road speed computation of mean values on the identical time point in the different arrays in every class, a plurality of arrays in final every class are merged into an array, this array has reflected road in the travel speed variation tendency of certain time period, and to speak approvingly of road travel speed variation tendency be a pattern.
S209, the result of mean value computation is carried out curve fitting;
Because include 8 time points in a time period, time range is less, so the velocity variations trend of road can reflect with polynomial curve in a time period scope.The present invention carries out m order polynomial curve fitting to the velocity variations trend that velocity amplitude reacted of a series of continuous time point correspondence that a road comprises according to criterion of least squares, and m+1 parameter of m order polynomial function is as the result of final curves match.Can establish its curvilinear equation is: y=a
mx
m+ a
M-1x
M-1+ ... + a
1X+a
0, a wherein
m∈ R, m＞=0; X ∈ Z, x＞=0; Y＞=0, x represents the time point in a day, the velocity amplitude of y express time point x correspondence.
These curves just provide optional match pattern for the data that finally fill a vacancy, and all roads all optional match patterns in each time period just provide optional all mode for the vacancy data of all road chains.
S210, according to the curve-fitting results of the difference under every road different time sections classification, set up road traffic road conditions trend library.
Preserve the road traffic road conditions trend library of the curve-fitting results of every difference classification under the road different time sections as history.
Road traffic road conditions trend library has been described in the historical road condition data of Floating Car, and all roads in the road network are at the m order polynomial curve of all velocity variations trend of each time period.This library is unit with the road, i.e. library of every road has comprised the polynomial curve of all the reaction road travel speed changing patteries on each time period.
S211, read real-time traffic road condition data;
Read the traffic road condition data of real-time Floating Car.
The road of S212, scanning vacancy road conditions is handled one by one to the road of vacancy road conditions;
S213, read out all road conditions trend polynomial curves of the road of vacancy road conditions on time point t;
S214, the vacancy road conditions on the road are inferred by pattern match;
According to the speed v t-1 of road 4 time point correspondences before the current point in time t in Floating Car real-time road data, vt-2, vt-3, vt-4, the variation tendency of being reacted is mated the curve (assumed curve bar number is the k bar) among the S213.Because the curve in the trend library all is a m order polynomial curve, its curvilinear equation is:
y＝a
mx
m+a
m-1x
m-1+…+a
1x+a
0，
A wherein
m∈ R, m＞=0; X ∈ Z, x＞=0; Y＞=0, x represents the time point in a day, the velocity amplitude of y express time point x correspondence.The curvilinear equation that then can establish wherein is:
y
i＝a
m，ix
i m+a
m-1，ix
i m-1+…+a
1，ix
i+a
0，i，
I=1 wherein, 2 ..., k.Calculate
V wherein
xThe velocity amplitude of time point x correspondence promptly makes in the expression real time data
S215, the complete real-time traffic data of output.
Finish after the filling up of having vacant position road conditions, export the real-time road data of complete road network.
On the basis of embodiment one, the embodiment of the invention also provides a kind of traffic road condition information filling system, and as shown in Figure 4, this system comprises: historical data pretreatment unit 1, road conditions trend analysis unit 2 and road conditions are filled up processing unit 3.
Further, described historical data pretreatment unit 1 comprises: first read module 11, fill up module 12, mark module 13 and preserve module 14.
First read module 11 is used to read trimestral at least historical road condition data; Fill up module 12, being used for road condition data is that the road condition data of previous time point of the time point of vacancy is filled up the time point that this road condition data is a vacancy; Mark module 13 is used for time period at mark time point place; Preserve module 14, be used to preserve the traffic road condition data after the completion.
Further, described road conditions trend analysis unit 2 comprises: second read module 21, clustering processing module 22, mean value computation module 23, curve fitting module 24 and library are set up module 25.
Second read module 21 is used to read the traffic road condition data after the completion; Clustering processing module 22 is used for same road, same date not, and the traffic road condition data of identical time period carries out clustering processing, obtains the not same date under the same category, the cluster data of identical time period; Mean value computation module 23 is used for described cluster data is carried out mean value computation; Curve fitting module 24 is used for the result of mean value computation is carried out curve fitting; Library is set up module 25, is used for the curve-fitting results according to the classification of the difference under every road different time sections, sets up road traffic road conditions trend library.
Further, described road conditions are filled up processing unit 3 and are comprised: third reading delivery piece 31, the 4th read module 32 and infer module 33.
Third reading delivery piece 31 is used to read real-time traffic road condition data; The 4th read module 32 is used to read out all road conditions trend polynomial curves of the road of vacancy road conditions on the T time point; Infer module 33, be used for the vacancy road conditions on the road being inferred by pattern match.
Traffic road condition information filling method that the embodiment of the invention provides and system, at first the Floating Car historical data being carried out absence information replenishes, respectively same road all road condition datas in identical certain period are carried out cluster analysis then, merge similar traffic information unit, distinguish dissimilar traffic information unit, velocity variations trend fitting with these road conditions unit processes is a polynomial curve afterwards, and the friction speed variation tendency in each time period of all roads has constituted road traffic road conditions trend library.The road conditions trend of road is mated in Traffic Information trend in the use road traffic road conditions trend library and the current slot, infers that the travel speed that this road of current time is as filling up road conditions.The embodiment of the invention with all the velocity variations trend in certain period of road in the Floating Car historical data all as optional pattern, because the velocity variations in certain period is done as a wholely to treat, this just overcomes the defective of the historical Mean Method of knowing clearly, fill a vacancy during transport information actual, more accurate by the transport information of mating optional pattern, making the vacancy of inferring.
Those of ordinary skills can recognize, the unit and the algorithm steps of each example of describing in conjunction with embodiment disclosed herein, can realize with electronic hardware, computer software or the combination of the two, for the interchangeability of hardware and software clearly is described, the composition and the step of each example described prevailingly according to function in the above description.These functions still are that software mode is carried out with hardware actually, depend on the application-specific and the design constraint of technical scheme.The professional and technical personnel can use distinct methods to realize described function to each specific should being used for, but this realization should not thought and exceeds scope of the present invention.
The method of describing in conjunction with embodiment disclosed herein or the step of algorithm can use the software module of hardware, processor execution, and perhaps the combination of the two is implemented.Software module can place the storage medium of any other form known in random access memory (RAM), internal memory, ROM (read-only memory) (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or the technical field.
The above; only be the specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; can expect easily changing or replacing, all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion by described protection domain with claim.
Claims (10)
1. a traffic road condition information filling method is characterized in that, comprising:
According to historical road condition data, the data of vacancy in the completion traffic road condition data;
According to same road all road condition datas in the identical time period are carried out the road condition change trend that clustering processing draws, set up road traffic road conditions trend library;
The road condition change trend of this road in the road conditions trend of time point t place road in the time period and the road traffic road conditions trend library is complementary, calculates the described road of time point t as the travel speed of filling up road conditions.
2. method according to claim 1 is characterized in that, described according to historical road condition data, the data of vacancy comprise in the completion traffic road condition data:
Read trimestral at least historical road condition data;
The road condition data of previous time point that with road condition data is the time point of vacancy is filled up on the time point that this road condition data is a vacancy;
The time period at mark time point place;
Traffic road condition data after the preservation completion.
3. method according to claim 2 is characterized in that, described is to comprise before the road condition data of previous time point of the time point of vacancy is filled up on the time point that this road condition data is a vacancy road condition data:
According to road conditions place time point time division section.
4. method according to claim 3 is characterized in that, described basis is carried out the road condition change trend that clustering processing draws to same road all road condition datas in the identical time period, sets up road traffic road conditions trend library and comprises:
Read the traffic road condition data after the completion;
To same road, same date not, the traffic road condition data of identical time period carries out clustering processing, obtains the not same date under the same category, the cluster data of identical time period;
Described cluster data is carried out mean value computation;
The result of mean value computation is carried out curve fitting;
According to the curve-fitting results of the classification of the difference under every road different time sections, set up road traffic road conditions trend library.
5. method according to claim 4, it is characterized in that, described with time point t place road in the time period road conditions trend and road traffic road conditions trend library in the road condition change trend of this road be complementary, calculate the described road of time point t and comprise as the travel speed of filling up road conditions:
Read real-time traffic road condition data;
Read out all road conditions trend polynomial curves of the road of vacancy road conditions on time point t;
By pattern match the vacancy road conditions on the road are inferred.
6. method according to claim 5 is characterized in that, comprises after by pattern match the vacancy road conditions on the road being inferred:
Export complete real-time traffic data.
7. a traffic road condition information filling system is characterized in that, comprising:
The historical data pretreatment unit is used for according to historical road condition data, the data of vacancy in the completion traffic road condition data;
Road conditions trend analysis unit is used for setting up road traffic road conditions trend library according to same road all road condition datas in the identical time period are carried out the road condition change trend that clustering processing draws;
Road conditions are filled up processing unit, are used for the road conditions trend of time point t place road in the time period and the road condition change trend of this road of road traffic road conditions trend library are complementary, and calculate the described road of time point t as the travel speed of filling up road conditions.
8. system according to claim 7 is characterized in that, described historical data pretreatment unit comprises:
First read module is used to read trimestral at least historical road condition data;
Fill up module, being used for road condition data is the road condition data of previous time point of the time point of the vacancy time point that to fill up this road condition data be vacancy;
Mark module is used for time period at mark time point place;
Preserve module, be used to preserve the traffic road condition data after the completion.
9. system according to claim 6 is characterized in that, described road conditions trend analysis unit comprises:
Second read module is used to read the traffic road condition data after the completion;
The clustering processing module is used for same road, same date not, and the traffic road condition data of identical time period carries out clustering processing, obtains the not same date under the same category, the cluster data of identical time period;
The mean value computation module is used for described cluster data is carried out mean value computation;
Curve fitting module is used for the result of mean value computation is carried out curve fitting;
Library is set up module, is used for the curve-fitting results according to the classification of the difference under every road different time sections, sets up road traffic road conditions trend library.
10. system according to claim 6 is characterized in that, described road conditions are filled up processing unit and comprised:
Third reading delivery piece is used to read real-time traffic road condition data;
The 4th read module is used to read out all road conditions trend polynomial curves of the road of vacancy road conditions on time point t;
Infer module, be used for the vacancy road conditions on the road being inferred by pattern match.
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|---|---|---|---|
| CN200910244141A CN101763730B (en) | 2009-12-30 | 2009-12-30 | Traffic road condition information filling method and system |
| PCT/CN2010/079732 WO2011079707A1 (en) | 2009-12-30 | 2010-12-13 | Traffic road condition information filling method and system |
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|---|---|---|---|
| CN200910244141A CN101763730B (en) | 2009-12-30 | 2009-12-30 | Traffic road condition information filling method and system |
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| CN101763730A true CN101763730A (en) | 2010-06-30 |
| CN101763730B CN101763730B (en) | 2012-09-26 |
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| WO (1) | WO2011079707A1 (en) |
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- 2009-12-30 CN CN200910244141A patent/CN101763730B/en active Active
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| CN107680377A (en) * | 2017-11-06 | 2018-02-09 | 浙江工商大学 | Traffic flow data based on trend fitting intersects complementing method |
| CN107680377B (en) * | 2017-11-06 | 2019-09-27 | 浙江工商大学 | Traffic flow data based on trend fitting intersects complementing method |
| CN110657798A (en) * | 2019-09-11 | 2020-01-07 | 广州海洋地质调查局 | Terrestrial magnetism daily variable data filling method and processing terminal |
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| Publication number | Publication date |
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| WO2011079707A1 (en) | 2011-07-07 |
| CN101763730B (en) | 2012-09-26 |
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