CN102208132A - Traffic predicting device, traffic predicting method and program thereof - Google Patents
Traffic predicting device, traffic predicting method and program thereof Download PDFInfo
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Abstract
The invention provides a traffic predicting device which can decrease the computational complexity and track the change trend of every moment. The traffic predicting device (10) comprises an average speed data storing part (12); a change pattern chart storing part (14) for storing a plurality of change pattern charts generated by traffics on predetermined time points and illustrating the traffic changes through a matrix composed of tracked predetermined time points and the traffics at the tracked time points; a change pattern chart updating part (19) for updating the values of the matrix elements corresponding to the obtained average speed change data after reading the change pattern charts from the change pattern chart storing part (14); a predicted traffic calculating part (20) for reading the latest traffic change data from the average speed data storing part (12), calculating the estimation values of the plurality of change pattern charts according to the matrix element values corresponding to the read change data and making the traffic corresponding to the change patter chart with the highest estimation value as the predicted traffic; and a display (16) for outputting the predicted traffic.
Description
Technical field
The present invention relates to the device of prognosis traffic volume.
Background technology
Method of carrying out long-term forecasting and the method for carrying out short-term forecasting are arranged in the method for prognosis traffic volume.Mostly adopt with statistical for long-term forecasting and to obtain per diem or the method for the mean value of the attribute of period etc., and this method is practical.For short-term forecasting, known have use time series data in the past to carry out forecast method or carry out method (patent documentation 1,2) based on the rote learning of pattern.
The prior art document:
Patent documentation 1: TOHKEMY 2001-307278 communique
Patent documentation 2: TOHKEMY 2002-298281 communique
Summary of the invention
The prediction of (for example more than 1 hour) was compared with it between long-term forecasting can be fit to for a long time, and short-term forecasting dynamically is inclined to about institute by every day, therefore is difficult to predict.
Use time series data in the past to carry out the method for forecast method or library, so be not suitable for large scale network is predicted because calculated amount is very big.For example in the nearest neighbor method, pattern increases more that then the comparison calculated amount between pattern is many more.In addition, in above-mentioned prior art, do not consider the variation of dynamic trend (trend),, need carry out the renewal (update) of data continually in order to follow the trail of the trend that at every moment changes.
Therefore, in view of above-mentioned background, the object of the present invention is to provide and a kind ofly can reduce calculated amount, and can follow the trail of the traffic volume forecast device of the trend that at every moment changes.
Traffic volume forecast device of the present invention comprises: the traffic data obtaining section, obtain the data of the volume of traffic of the road of predetermined interval; The traffic data storage part is stored obtained traffic data; Changing pattern figure storage part, store a plurality of changing pattern figure that the volume of traffic on schedule generates, this changing pattern figure represents that by matrix the volume of traffic that reaches above-mentioned each volume of traffic changes, and this matrix is made of the volume of traffic of the time of reviewing from predetermined point of time with the time point of tracing back to; Changing pattern figure renewal portion, when obtaining above-mentioned traffic data, from above-mentioned changing pattern figure storage part, read the changing pattern figure corresponding with obtained traffic data, and from above-mentioned traffic data storage part, read the delta data of the above-mentioned volume of traffic, upgrade the value of the matrix key element of the above-mentioned changing pattern figure corresponding with the delta data of being read; The prognosis traffic volume calculating part, from above-mentioned traffic data storage part, read the delta data of the up-to-date volume of traffic, at a plurality of changing pattern figure, value according to the matrix key element corresponding with the delta data of being read is obtained evaluation of estimate, and obtain with above-mentioned evaluation of estimate for the corresponding volume of traffic of the highest changing pattern figure as prognosis traffic volume; And efferent, export above-mentioned prognosis traffic volume.Above-mentioned traffic data obtaining section can receive the data of the relevant vehicle that sends from probe vehicles, and the data of the average velocity of the vehicle that will obtain according to these data are as above-mentioned traffic data.
Like this, the volume of traffic on schedule generates rectangular a plurality of changing pattern figure of changing pattern that expression reaches the volume of traffic of this volume of traffic in advance, obtain the evaluation of estimate of each changing pattern figure according to the value of the matrix key element corresponding with up-to-date delta data, calculate up-to-date delta data near the computing burden of which changing pattern figure thereby can alleviate, apace prognosis traffic volume.In addition, according to the structure of when obtaining traffic data, upgrading changing pattern figure, can follow the trail of the trend that at every moment changes.
In the traffic volume forecast device of the present invention, above-mentioned changing pattern figure renewal portion can be before the value of the matrix key element of upgrading above-mentioned changing pattern figure, with all matrix key element multiplication by constants E (0＜E＜1) of above-mentioned changing pattern figure.Like this, on duty with constant E by with all matrix key elements of changing pattern figure can reduce the influence of legacy data to changing pattern figure.
In the traffic volume forecast device of the present invention, above-mentioned changing pattern figure renewal portion can upgrade the value of the matrix key element of the above-mentioned changing pattern figure corresponding with above-mentioned delta data, and also upgrades the value of its volume of traffic matrix key element adjacent with the volume of traffic of above-mentioned corresponding matrix key element.Like this, by also upgrading the value of the adjacent matrix key element of the volume of traffic,, therefore can suitably predict owing to adding value in many matrix key elements.Can come updating value with the little ratio of matrix key element that meets than the volume of traffic at the adjacent matrix key element of the volume of traffic.
In the traffic volume forecast device of the present invention, above-mentioned prognosis traffic volume calculating part multiply by by short matrix key element of time of reviewing from predetermined point of time to be compared the big weight coefficient of weight with long matrix key element of the time of reviewing from predetermined point of time and obtains above-mentioned evaluation of estimate.According to this structure,, can carry out more suitable traffic volume forecast by up-to-date traffic data is weighted.
In the traffic volume forecast device of the present invention, above-mentioned changing pattern figure comprises the traffic data of above-mentioned predetermined point of time in other intervals different with above-mentioned predetermined interval as the matrix key element, above-mentioned changing pattern figure renewal portion is when obtaining above-mentioned predetermined interval and above-mentioned other interval traffic datas, from above-mentioned changing pattern figure storage part, read the changing pattern figure corresponding with the traffic data of above-mentioned predetermined interval, and from above-mentioned traffic data storage part, read the delta data of the volume of traffic of above-mentioned predetermined interval, upgrade the value of the matrix key element of the above-mentioned changing pattern figure corresponding with the delta data of being read, and the value of the matrix key element that renewal is corresponding with above-mentioned other interval traffic datas, above-mentioned prognosis traffic volume calculating part is read the delta data of the up-to-date volume of traffic in above-mentioned other intervals from above-mentioned traffic data storage part, a plurality of changing pattern figure at above-mentioned other intervals, value according to the matrix key element corresponding with the delta data of being read is obtained evaluation of estimate, and obtain with above-mentioned evaluation of estimate for the corresponding volume of traffic of the highest changing pattern figure as above-mentioned other interval prognosis traffic volumes, from above-mentioned traffic data storage part, read the delta data of the up-to-date volume of traffic of above-mentioned predetermined interval, a plurality of changing pattern figure at above-mentioned predetermined interval, value according to the matrix key element corresponding with the delta data of being read, obtain evaluation of estimate with the value of the matrix key element corresponding, and obtain with above-mentioned evaluation of estimate and be the prognosis traffic volume of the corresponding volume of traffic of the highest changing pattern figure as above-mentioned predetermined interval with the above-mentioned prognosis traffic volume data of obtaining at above-mentioned other intervals.At this, other intervals both can be the intervals adjacent with above-mentioned predetermined interval, can also be the intervals that has with the similar degree of the changing pattern figure of the above-mentioned predetermined interval changing pattern figure bigger than predetermined threshold.Distance (quadratic sum of difference etc.) between the mutual sequential of changing pattern of the enough average velocity of similar degree energy is obtained.
Because the volume of traffic of road influences each other, thus other interval traffic datas different also used with predetermined interval, thus can improve the precision of prediction of the volume of traffic of predetermined interval.
Traffic volume forecasting method of the present invention is used traffic volume forecast device prognosis traffic volume, and it may further comprise the steps: above-mentioned traffic volume forecast device is obtained the step of traffic data of the road of predetermined interval; Above-mentioned traffic volume forecast device is stored in step in the traffic data storage part with obtained traffic data; Above-mentioned traffic volume forecast device is prepared the step of changing pattern figure storage part, a plurality of changing pattern figure that the volume of traffic that this changing pattern figure storage portion stores is put on schedule generates, this changing pattern figure represents that by matrix the volume of traffic that reaches above-mentioned each volume of traffic changes, and this matrix is made of the volume of traffic of the time of reviewing from predetermined point of time with the time point of tracing back to; Above-mentioned traffic volume forecast device is read the changing pattern figure corresponding with obtained traffic data from above-mentioned changing pattern figure storage part when obtaining above-mentioned traffic data, and from above-mentioned traffic data storage part, read the delta data of the above-mentioned volume of traffic, upgrade the step of value of the matrix key element of the above-mentioned changing pattern figure corresponding with the delta data of being read; Above-mentioned traffic volume forecast device is read the delta data of the up-to-date volume of traffic from above-mentioned traffic data storage part, at a plurality of changing pattern figure, value according to the matrix key element corresponding with the delta data of being read is obtained evaluation of estimate, and obtains with above-mentioned evaluation of estimate and be the step of the corresponding volume of traffic of the highest changing pattern figure as prognosis traffic volume; And above-mentioned traffic volume forecast device is exported the step of above-mentioned prognosis traffic volume.
Program of the present invention is the program of prognosis traffic volume, makes computing machine carry out following steps: the step of traffic data that obtains the road of predetermined interval; Obtained traffic data is stored in step in the traffic data storage part; Guarantee to store the zone of a plurality of changing pattern figure that the volume of traffic on schedule generates and prepare the step of changing pattern figure storage part, this changing pattern figure represents that by matrix the volume of traffic that reaches above-mentioned each volume of traffic changes, and this matrix is made of the volume of traffic of the time of reviewing from predetermined point of time with the time point of tracing back to; When obtaining above-mentioned traffic data, from above-mentioned changing pattern figure storage part, read the changing pattern figure corresponding with obtained traffic data, and from above-mentioned traffic data storage part, read the delta data of the above-mentioned volume of traffic, upgrade the step of value of the matrix key element of the above-mentioned changing pattern figure corresponding with the delta data of being read; From above-mentioned traffic data storage part, read the delta data of the up-to-date volume of traffic, at a plurality of changing pattern figure, value according to the matrix key element corresponding with the delta data of being read is obtained evaluation of estimate, and obtains with above-mentioned evaluation of estimate and be the step of the corresponding volume of traffic of the highest changing pattern figure as prognosis traffic volume; And the step of exporting above-mentioned prognosis traffic volume.
Traffic volume forecasting method of the present invention and program and traffic volume forecast device of the present invention are same, can alleviate the computing burden, apace prognosis traffic volume.In addition, can be with the various structure applications of traffic volume forecast device of the present invention in Traffic volume forecasting method of the present invention and program.
According to the present invention, the volume of traffic by on schedule uses expression to reach rectangular a plurality of changing pattern figure of pattern of delta data of the volume of traffic of this volume of traffic, can alleviate and calculate the computing burden which changing pattern figure up-to-date delta data approaches, and prognosis traffic volume apace.
Description of drawings
Fig. 1 is the figure of structure of the traffic volume forecast device of expression first embodiment.
Fig. 2 is the figure that expression is stored in the example of the data in the changing pattern figure storage part.
Fig. 3 is the figure of the delta data of expression average velocity in the past.
(a) of Fig. 4 is the figure of the example of the changing pattern figure before expression is upgraded.(b) be the figure that is used to illustrate the renewal of changing pattern figure.
Fig. 5 is the figure that is used to illustrate the renewal of changing pattern figure.
Fig. 6 is the figure of example of the up-to-date delta data of expression average velocity.
Fig. 7 is that the figure with the calculated example of the highest changing pattern figure of the consistent degree of delta data is obtained in a plurality of changing pattern figure in expression.
Fig. 8 is the figure of hardware configuration of the traffic volume forecast device of expression first embodiment.
Fig. 9 is the figure of the work of upgrading based on the changing pattern figure of traffic volume forecast device of expression first embodiment.
Figure 10 is the figure based on the work of the traffic volume forecast of traffic volume forecast device of expression first embodiment.
Figure 11 is the figure that is used to illustrate that the changing pattern figure of second embodiment upgrades.
Figure 12 is the figure based on the work of the traffic volume forecast of traffic volume forecast device of expression second embodiment.
Figure 13 is the figure based on the Forecasting Methodology of the volume of traffic of traffic volume forecast device that is used to illustrate the 3rd embodiment.
(a) of Figure 14 is the figure that expression is stored in the example of the changing pattern figure in the changing pattern figure storage part.(b) be the figure of expression road structure.
Figure 15 is the figure that is used to illustrate that the changing pattern figure of the 4th embodiment upgrades.
Figure 16 is the figure based on the work of the traffic volume forecast of traffic volume forecast device of expression the 4th embodiment.
(a) of Figure 17 is the figure that represents with respect between the adjacent region in self interval.(b) be the figure of the example of expression changing pattern figure.
Figure 18 is the figure of structure of the traffic volume forecast device 10a of expression the 6th embodiment.
Figure 19 is the figure of example between the adjacent region of expression the 6th embodiment.
Label declaration:
10 traffic volume forecast devices
11 vehicle data acceptance divisions
12 average velocity data store
13 road-map storage parts
14 changing pattern figure storage parts
15 control parts
16 displays
17 input parts
18 average velocity calculating parts
19 changing pattern figure renewal portions
20 prognosis traffic volume calculating parts
21 display parts
22a, 22e, 23a changing pattern figure
Determination portion between 24 adjacent regions
Embodiment
Below, the traffic volume forecast device of embodiment of the present invention is described with reference to accompanying drawing.
(first embodiment)
Fig. 1 is the figure of structure of the traffic volume forecast device 10 of expression first embodiment.Traffic volume forecast device 10 for example is arranged on traffic information center, receives the various data of vehicle from probe vehicles (Probe Car) P that travels throughout the country.Use the position data and the speed data that receive from probe vehicles P to come prognosis traffic volume in the present embodiment.
The volume of traffic of predetermined interval can be grasped according to the average velocity of the vehicle that travels at this predetermined interval.For example, the average velocity of vehicle is compared with legal limit and is illustrated more that then road is crowded, the volume of traffic is big slowly more.Therefore, in the present embodiment, the data of car speed are handled as the data of the expression volume of traffic.In the present embodiment, be that example describes to come prognosis traffic volume, but also can utilize additive method to obtain the data of the volume of traffic according to the data that obtain from probe vehicles P.For example, also can use the traffic data of collecting by the wagon detector that is arranged on the road.
Traffic volume forecast device 10 comprises: receive from the vehicle data acceptance division 11 of the various data of probe vehicles P transmission; The average velocity data store 12 of the average velocity data of the vehicle in storing predetermined interval; Store the road-map storage part 13 of road-map; Store the changing pattern figure storage part 14 of the changing pattern figure of the variation of representing average velocity data in the past; Generate the control part 15 of changing pattern figure and prediction average velocity data in the future; The display 16 of the prognosis traffic volume that demonstration is obtained by control part 15; And the input part 17 of the various information such as information in the interval of wanting prognosis traffic volume is for example specified in input.
Fig. 2 is the figure that expression is stored in the example of the changing pattern figure in the changing pattern figure storage part 14.Changing pattern figure shown in Figure 2 is the data of changing pattern of the average velocity data of expression predetermined interval.Changing pattern figure storage part 14 stores and the changing pattern figure group as shown in Figure 2 of wanting the interval equal number of prognosis traffic volume.
As shown in Figure 2, changing pattern figure storage part 14 stores a plurality of changing pattern Figure 22 a～22e to each interval.Each changing pattern Figure 22 a～22e is illustrated in the changing pattern that predetermined point of time reaches predetermined average velocity.So-called predetermined point of time is meant the up-to-date time point of obtaining data, is recited as " now " among Fig. 2.For example, changing pattern Figure 22 a is illustrated in the changing pattern of predetermined point of time average velocity for " 40km/h～", and changing pattern Figure 22 e is illustrated in the changing pattern of predetermined point of time average velocity for " 0～10km/h ".Changing pattern figure is by being dividing the matrix that the elements combination stipulated forms with predetermined numerical range and constitute so every 10km/h as the time for per 10 minutes, average velocity.Utilize this changing pattern figure, can cut down the data volume of performance changing pattern significantly.
Changing pattern figure renewal portion 19 is according to the average velocity data that calculated by average velocity calculating part 18 and be stored in data in the average velocity data store 12 and update stored in changing pattern figure in the changing pattern figure storage part 14.At this, use concrete example that the processing of changing pattern figure renewal portion 19 is described.When average velocity calculating part 18 calculated the average velocity data of predetermined interval according to the vehicle data from probe vehicles P, the changing pattern figure corresponding with these average velocity data read in changing pattern figure renewal portion 19.In this embodiment, when the average velocity data are taken as " 40km/h～", read the changing pattern Figure 22 a of the average velocity data of " now " for " 40km/h～".In addition, the average velocity data in the past in this interval are read by changing pattern figure renewal portion 19 from average velocity data store 12.
Fig. 3 is the figure of the delta data of the past average velocity read of expression.(a) of Fig. 4 is the figure of the changing pattern Figure 22 a before expression is upgraded, is the figure that has reprinted changing pattern Figure 22 a shown in Figure 2.(b) of Fig. 4 and Fig. 5 are the figure that is used to illustrate the renewal of changing pattern Figure 22 a.Changing pattern figure renewal portion 19 uses the delta data of being read (with reference to Fig. 3) to upgrade changing pattern figure (Fig. 4 (a)).Changing pattern figure integral body at first be multiply by the constant E (0＜E＜1) less than 1 in changing pattern figure renewal portion 19.(b) expression of Fig. 4 be multiply by 0.9 example with changing pattern figure integral body.Like this, by with the whole multiplication by constants E of changing pattern figure, reduce the influence of legacy data to changing pattern figure.
In example shown in Figure 3, when the process till the average velocity that reaches " 40km/h～" with the same expression of changing pattern figure, before 10 minutes be " 30～40km/h ", before 20 minutes be " 20～30km/h ", be " 20～30km/h " to be " 10～20km/h " before 40 minutes before 30 minutes.The situation that will become the average velocity of " 40km/h～" through such process is added in the matrix key element of correspondence of changing pattern figure.Particularly, as shown in Figure 5, in the changing pattern matrix, append the number of times (1 time) of having reviewed each matrix key element.
Then, prognosis traffic volume calculating part 20 is described.Prognosis traffic volume calculating part 20 is read the delta data of up-to-date average velocity from average velocity data store 12, and the predicted average speed of calculating predetermined interval according to the delta data and the changing pattern figure of the up-to-date average velocity of being read is a prognosis traffic volume.
Fig. 6 is the figure of example of the delta data of the immediate average velocity of expression.When representing delta data shown in Figure 6 with changing pattern figure is same, being now " 20～30km/h ", was " 20～30km/h " before 10 minutes, was " 10～20km/h " before 20 minutes, be " 20～30km/h " to be " 10～20km/h " before 40 minutes before 30 minutes.Prognosis traffic volume calculating part 20 is obtained among a plurality of changing pattern figure the highest changing pattern figure of consistent degree with the delta data in past shown in Figure 6, and obtains the average velocity data corresponding with this changing pattern figure and be used as prognosis traffic volume.
Fig. 7 is that the figure with the calculated example of the highest changing pattern figure of the consistent degree of delta data shown in Figure 6 is obtained among a plurality of changing pattern figure in expression.As shown in Figure 7, the value of the matrix key element that prognosis traffic volume calculating part 20 will be consistent with up-to-date delta data shown in Figure 6 adds up to the evaluation of estimate of obtaining the consistent degree of expression.Prognosis traffic volume calculating part 20 is obtained average velocity in the future, therefore, make the average velocity " 20～30km/h " of " now " of up-to-date delta data corresponding with the matrix key element of " 20～30km/h " of changing pattern figure " before 10 minutes ", make the average velocity " 20～30km/h " of " before 10 minutes " of up-to-date delta data corresponding with the matrix key element of " 20～30km/h " of changing pattern figure " before 20 minutes ", below identical, make it corresponding with the matrix key element that has respectively moved forward.
In example shown in Figure 7, the evaluation of estimate of changing pattern Figure 22 a be " 90 " ... the evaluation of estimate of changing pattern Figure 22 e is " 66 ".In this embodiment, for example when the evaluation of estimate of changing pattern Figure 22 a was maximum, prognosis traffic volume calculating part 20 was obtained the average velocity " 40km/h～" corresponding with changing pattern Figure 22 a as prognosis traffic volume.
Fig. 8 is the figure of hardware configuration of the traffic volume forecast device 10 of expression present embodiment.Traffic volume forecast device 10 comprises CPU30, storer 31, input part 32, hard disk 33, display 34 and communication interface 35, and these inscapes connect by bus 36.Store the functional programs 37 of the traffic volume forecast device 10 of realizing present embodiment in the storer 31.Carry out by CPU30 read routine 37, realize the function of traffic volume forecast device 10, carry out processing as described below.Storage average velocity data, road-map and changing pattern figure in the hard disk 33.That is, hard disk 33 constitutes average velocity data store 12, road-map storage part 13 and changing pattern figure storage part 14.
Fig. 9 is the figure of renewal work of changing pattern figure of the traffic volume forecast device 10 of expression first embodiment.Traffic volume forecast device 10 at first receives vehicle data (S10) from probe vehicles P, calculates and the average velocity (S12) of the vehicle of the predetermined interval of storage road according to the vehicle data that receives.When receiving vehicle data, use a plurality of vehicle datas to calculate average velocity from a plurality of probe vehicles P that travel at predetermined interval.As the computing method of average velocity, length that both can predetermined interval is divided by by the needed time of predetermined interval, the averaging of data of the travel speed that will receive from many probe vehicles P when many probe vehicles P also can be arranged in predetermined interval.
Then, the changing pattern figure (S14) corresponding with the average velocity data that calculate selected and read to traffic volume forecast device 10 from changing pattern figure storage part 14.For example, when the average velocity data that calculate are " 40km/h～", read changing pattern Figure 22 a (with reference to Fig. 2).At this, the changing pattern figure that is read becomes upgating object.All data multiplication by constants E (0＜E＜1) of 10 couples of changing pattern figure that read of traffic volume forecast device (S16).In the present embodiment, use 0.9 as constant E.
Traffic volume forecast device 10 is read the delta data (S18) of average velocity from average velocity data store 12.In the changing pattern figure of upgating object, the matrix key element corresponding with the average velocity data of being read added " 1 ", upgrade changing pattern figure (S20).
Figure 10 is the figure based on the work of the traffic volume forecast of traffic volume forecast device 10 of expression first embodiment.At first, traffic volume forecast device 10 is read the delta data (S30) of the up-to-date average velocity in the interval of wanting prognosis traffic volume from average velocity data store 12.Afterwards, traffic volume forecast device 10 is obtained each and the consistent degree of delta data of a plurality of changing pattern figure in the interval that will predict.Particularly, traffic volume forecast device 10 is read the value of the matrix key element corresponding with up-to-date delta data in each of a plurality of changing pattern figure, the value that reads is added up to the evaluation of estimate (S32) of calculating expression and the consistent degree of up-to-date delta data.Traffic volume forecast device 10 determines that evaluation of estimate is the highest changing pattern figure (S34), obtains the average velocity data corresponding with determined changing pattern figure as prognosis traffic volume (S36).Export the data (S38) of the prognosis traffic volume of obtaining from the display 16 of traffic volume forecast device 10.At this, enumerated from the example of the data of display 16 prediction of output volume of traffic, but also can send the data of the prognosis traffic volume of obtaining as requested, perhaps near this predetermined interval, broadcast.More than, the structure and the work of the traffic volume forecast device 10 of first embodiment have been described.
The traffic volume forecast device 10 of first embodiment average velocity data on schedule generate rectangular a plurality of changing pattern figure of the pattern of the delta data represented to reach the average velocity till this average velocity in advance.Then, the value of the matrix key element by will be corresponding with up-to-date delta data adds up to the evaluation of estimate of obtaining each changing pattern figure, can alleviate and calculate up-to-date delta data and the immediate computing burden of which changing pattern figure, can fast prediction represent the average velocity of the volume of traffic.
(second embodiment)
The traffic volume forecast device 10 of second embodiment of the present invention then, is described.The basic structure of the traffic volume forecast device 10 of second embodiment identical with first embodiment (with reference to Fig. 1), but the difference of the traffic volume forecast device 10 of second embodiment and first embodiment is the update method of changing pattern figure.
Figure 11 is the figure that is used to illustrate that the changing pattern figure of second embodiment upgrades.In second embodiment, except the processing of upgrading the average velocity matrix key element corresponding, also carry out following processing:, also upgrade the adjacent matrix key element of average velocity with respect to the matrix key element corresponding with the delta data in past with delta data in the past.Particularly, traffic volume forecast device 10 adds " 1 " in the matrix key element of correspondence, and adds " 0.5 " in adjacent matrix key element.
Figure 12 is the figure of renewal work of changing pattern figure of the traffic volume forecast device 10 of expression second embodiment.After traffic volume forecast device 10 receives vehicle data from probe vehicles P, in changing pattern figure, to in the matrix key element corresponding, adding " 1 ", the work (S10～S20) identical till the renewal changing pattern figure with first embodiment with the average velocity data in past.In the traffic volume forecast device 10 of second embodiment, also in the average velocity matrix key element adjacent, add " 0.5 " with corresponding matrix key element, upgrade changing pattern figure (S22).More than, the traffic volume forecast device 10 of second embodiment has been described.
The traffic volume forecast device 10 of second embodiment by the value of also upgrading the adjacent matrix key element of average velocity in a plurality of key elements of matrix the introducing value.Therefore, data in the past are few and have under the situation of damaged value or transition value and also can utilize these damaged values of adjacent Data Update or transition value, therefore can suitably average the prediction of speed.
(the 3rd embodiment)
The traffic volume forecast device 10 of the 3rd embodiment then, is described.The basic structure of the traffic volume forecast device 10 of the 3rd embodiment identical with first embodiment (with reference to Fig. 1), the traffic volume forecast device 10 of the 3rd embodiment and the difference of first embodiment have been to use the Forecasting Methodology of the volume of traffic of changing pattern figure.
Figure 13 is the Forecasting Methodology based on the volume of traffic of traffic volume forecast device 10 that is used to illustrate the 3rd embodiment.In the traffic volume forecast device 10 of the 3rd embodiment, when obtaining the evaluation of estimate of expression and the consistent degree of in the past delta data, multiply by the big more weight coefficient of weight with present near more matrix key element.Particularly, on duty with the matrix key element before 10 minutes with weight coefficient " 1.0 ", on duty with the matrix key element before 20 minutes with weight coefficient " 0.9 ", on duty with the matrix key element before 30 minutes with weight coefficient " 0.8 ", on duty with weight coefficient " 0.7 " with the matrix key element before 40 minutes adds up to resulting value and obtains evaluation of estimate.
Usually, the volume of traffic in the future is relevant more nearly with the volume of traffic with the now near more period, therefore, by to be weighted with the value of the big more mode of the weight of present near more matrix key element to the matrix key element, can carry out suitable prediction.
(the 4th embodiment)
The traffic volume forecast device 10 of the 4th embodiment then, is described.The basic structure of the traffic volume forecast device 10 of the 4th embodiment identical with first embodiment (with reference to Fig. 1), the traffic volume forecast device 10 of the 4th embodiment and the difference of first embodiment are, when the average velocity of prediction predetermined interval, also use the average velocity data in the interval adjacent with predetermined interval.For convenience of explanation, predetermined interval that will predicted average speed is called " self interval ".
In addition, in the traffic volume forecast device 10 of above-mentioned the 4th embodiment, be stored among the changing pattern figure of changing pattern figure storage part 14 except the delta data of average velocity, also have the average velocity data between adjacent region with self interval.Average velocity data between adjacent region are also same with the average velocity data in self interval, represent with the numerical range of every 10km/h.In the present embodiment, between adjacent region, only comprise present average velocity data, do not comprise the delta data till the average velocity until now for changing pattern figure.
(a) of Figure 14 is the figure that expression is stored in the example of the changing pattern Figure 23 a in the changing pattern figure storage part 14.In (a) of Figure 14, only show the changing pattern Figure 23 a of average velocity for " 40km/h～" among a plurality of changing pattern figure in self interval.Changing pattern Figure 23 a shown in Figure 14 (a) is the changing pattern figure that is used for the average velocity data that are connected with like that between adjacent region 1,2 road structure forecast self interval shown in Figure 14 (b) at the two ends in self interval respectively.
Shown in Figure 14 (a), among changing pattern Figure 23 a of present embodiment except the changing pattern of the average velocity in identical with above-mentioned embodiment self interval, also have and self interval adjacent two adjacent region between 1,2 average velocity data.These data are data of the average velocity between the average velocity in self interval adjacent region during for " 40km/h～".For example, when self is interval when being " 40km/h～", 1 " 40km/h～" is " 47 " between adjacent region, when self is interval when being " 30～40km/h ", 1 " 30～40km/h " is " 26 " between adjacent region, when self is interval when being " 20～30km/h ", 1 " 20～30km/h " is " 2 " between adjacent region.Hence one can see that, and when the average velocity between adjacent region was " 40km/h～", often the average velocity in self interval also was " 40km/h～".
Figure 15 is the figure of renewal work of changing pattern figure of the traffic volume forecast device 10 of expression the 4th embodiment.Traffic volume forecast device 10 at first receives vehicle data (S40) from probe vehicles P, calculates and store self interval of road and the average velocity (S42) of the vehicle between adjacent region according to the vehicle data that receives.When receiving vehicle data, also can use a plurality of vehicle datas to calculate average velocity from a plurality of probe vehicles P that travel at predetermined interval.
Then, the changing pattern figure (S44) corresponding with the average velocity data that calculate selected and read to traffic volume forecast device 10 from changing pattern figure storage part 14.For example, when the average velocity data that calculate are " 40km/h～", read changing pattern Figure 23 a (with reference to Figure 14).The changing pattern Figure 23 a that is read is a upgating object.All data multiplication by constants E (0＜E＜1) of 10 couples of changing pattern Figure 23 a that read of traffic volume forecast device (S46).In the present embodiment, use 0.9 as constant E.
Traffic volume forecast device 10 is read the delta data (S48) of the average velocity in self interval from average velocity data store 12.In the changing pattern Figure 23 a that is read, in the matrix key element corresponding, add " 1 " with the average velocity data in past, upgrade changing pattern Figure 23 a (S50).In addition, traffic volume forecast device 10 with the adjacent region that calculates between the corresponding matrix key element of average velocity data in add " 1 ", upgrade changing pattern Figure 23 a (S52).
Figure 16 is the figure based on the work of the traffic volume forecast of traffic volume forecast device 10 of expression the 4th embodiment.At first, traffic volume forecast device 10 is read the delta data of up-to-date average velocity in self interval of wanting prognosis traffic volume and the delta data (S60) of the average velocity data between this adjacent region from average velocity data store 12.Afterwards, traffic volume forecast device 10 is obtained each of a plurality of changing pattern figure between adjacent region and the consistent degree of delta data.Particularly, in each of a plurality of changing pattern figure of traffic volume forecast device 10 between adjacent region, read with adjacent region between the value of the corresponding matrix key element of delta data, the value that reads is added up to the evaluation of estimate (S62) of calculating the consistent degree of expression.Traffic volume forecast device 10 determines that evaluation of estimate is the highest changing pattern figure (S64), obtains the average velocity data corresponding with determined changing pattern figure as the predicted average speed data (S66) between adjacent region.
Afterwards, traffic volume forecast device 10 is obtained a plurality of changing pattern figure in self interval and the consistent degree of delta data.Particularly, traffic volume forecast device 10 reads the value of the matrix key element corresponding with the delta data in self interval and the predicted average speed data between adjacent region in each of a plurality of changing pattern figure in self interval, the value that reads is added up to the evaluation of estimate (S68) of calculating the consistent degree of expression.Traffic volume forecast device 10 determines that evaluations of estimate are the highest changing pattern figure (S70), obtains the predicted average speed data (S72) of the average velocity data corresponding with determined changing pattern figure as self interval.The predicted average speed data (S74) that 10 outputs of traffic volume forecast device are obtained.Explanation has herein illustrated the example of the average velocity of predicting self interval.When the average velocity of prediction between above-mentioned adjacent region, will be replaced as self interval between adjacent region, and carry out work same as described above and get final product.More than, the structure and the work of the traffic volume forecast device 10 of the 4th embodiment have been described.
The traffic volume forecast device 10 of the 4th embodiment is except the delta data of the average velocity that uses self interval, also use the average velocity data between interactive adjacent region in road network, thereby can improve the precision of prediction of the volume of traffic in self interval.In addition, in the 4th embodiment, do not use delta data, therefore can suppress calculated load only having used predicted data (the average velocity data of current point in time) between adjacent region.
(the 5th embodiment)
The traffic volume forecast device 10 of fifth embodiment of the invention then, is described.The basic structure of the traffic volume forecast device 10 of the 5th embodiment is identical with the 4th embodiment, but the difference of the traffic volume forecast device 10 of the 5th embodiment is, be not only and self interval direct-connected interval, also use its next interval average velocity data, obtain the average velocity data in the future in self interval.
(a) of Figure 17 is the figure that represents with respect between the adjacent region in self interval, and (b) of Figure 17 is the figure of the example of expression changing pattern figure.Shown in Figure 17 (b), and self interval direct-connected interval be between adjacent region 1～5 and adjacent region between 8, but in the present embodiment, via between adjacent region between 3 adjacent regions that connect 6 with via between adjacent region between 5 adjacent regions that are connected 7 also usefulness act between the adjacent region of the average velocity of predicting self interval, write down these average velocity data.The update method of using this changing pattern figure and changing pattern figure predict that the method for average velocity in self interval is identical with the 4th embodiment.
In the 5th embodiment, be not only and self interval direct-connected interval, also that it is next interval as between adjacent region, also consider the average velocity data that this is interval, thereby can more suitably predict the average velocity data in self interval.In the present embodiment, direct-connected interval and its are next interval as between adjacent region, but may not be till the next one as the scope between adjacent region.For example, both can be following two, also can be more than it.In addition, can also be positioned at and the road interval of self zone distance preset range as between adjacent region.
(the 6th embodiment)
The traffic volume forecast device 10 of sixth embodiment of the invention then, is described.The basic structure of the traffic volume forecast device 10 of the 6th embodiment is identical with the 5th embodiment, but difference is, in the 6th embodiment, have following function: according to the variation of each interval average velocity data tendency, obtain have similar tendency road interval as between adjacent region.The similar interval of delta data may not be adjacent with self interval, but generally speaking, the situation in adjacent interval is more, therefore is called in this manual " between adjacent region ".
Figure 18 is the figure of structure of the traffic volume forecast device 10a of expression the 6th embodiment.The traffic volume forecast device 10a of the 6th embodiment also has determination portion 24 between adjacent region except the structure of the 5th embodiment.Determination portion 24 is carried out cluster with the delta data of average velocity as parameter between adjacent region, will be categorized as same group interval as handling between adjacent region.Cluster can be used known method, for example can use the K-means method.
Figure 19 is the figure of example between the adjacent region of expression the 6th embodiment.In example shown in Figure 19, interval 1, interval 2 and interval 7 is between the adjacent region in self interval.That is, between these adjacent regions 1,2,7 and self interval amount to 4 intervals and be sorted in same group.With respect to interval 1, interval 2, interval 7 and self interval also become between adjacent region.Clustering processing based on determination portion between adjacent region 24 does not need to carry out at every turn, and (for example 1 month) gets final product during being scheduled to.
In the 6th embodiment,, can predict the average velocity data in self interval accurately by delta data and self is interval similarly interval as handling between adjacent region.In the present embodiment, carry out cluster in order to find delta data and self interval similarly interval, but find that similarly interval method is not limited to cluster, also can adopt additive method.
More than, enumerate embodiment and describe traffic volume forecast device of the present invention in detail, but the invention is not restricted to above-mentioned embodiment.
In the above-described embodiment, the matrix example of predicted average speed data usually till being applied to up-to-date delta data before 10 minutes of changing pattern figure has been described, has carried out multistage prediction but also the delta data till the average velocity data that dope further can be applied to changing pattern figure.
Industrial utilizability
The present invention has can alleviate computing burden and can obtain fast the such effect of prognosis traffic volume, such as being useful to traffic congestion center, traffic control system, auto-navigation system, Web Map Services etc.
Claims (10)
1. traffic volume forecast device, it comprises:
The traffic data obtaining section, it obtains the data of the volume of traffic of the road of predetermined interval;
The traffic data storage part, the traffic data that its storage is obtained;
Changing pattern figure storage part, it stores a plurality of changing pattern figure that the volume of traffic on schedule generates, this changing pattern figure represents that by matrix the volume of traffic that reaches above-mentioned each volume of traffic changes, and this matrix is made of the volume of traffic of the time of reviewing from predetermined point of time with the time point of tracing back to;
Changing pattern figure renewal portion, it reads the changing pattern figure corresponding with obtained traffic data from above-mentioned changing pattern figure storage part when obtaining above-mentioned traffic data, and from above-mentioned traffic data storage part, read the delta data of the above-mentioned volume of traffic, and upgrade the value of the matrix key element of the above-mentioned changing pattern figure corresponding with the delta data of being read; And
The prognosis traffic volume calculating part, it reads the delta data of the up-to-date volume of traffic from above-mentioned traffic data storage part, at a plurality of changing pattern figure, value according to the matrix key element corresponding with the delta data of being read is obtained evaluation of estimate, and obtains with above-mentioned evaluation of estimate and be used as prognosis traffic volume for the corresponding volume of traffic of the highest changing pattern figure; And
Efferent, it exports above-mentioned prognosis traffic volume.
2. traffic volume forecast device according to claim 1 is characterized in that,
Above-mentioned traffic data obtaining section receives from the data of the relevant vehicle of probe vehicles transmission, and uses the average velocity data of the vehicle of obtaining according to these data to be used as above-mentioned traffic data.
3. traffic volume forecast device according to claim 1 and 2 is characterized in that,
Above-mentioned changing pattern figure renewal portion carried out the multiplying of multiplication by constants E (0＜E＜1) to the value of all matrix key elements of above-mentioned changing pattern figure before the value of the matrix key element of upgrading above-mentioned changing pattern figure.
4. according to any described traffic volume forecast device in the claim 1～3, it is characterized in that,
Above-mentioned changing pattern figure renewal portion upgrades the value of the matrix key element of the above-mentioned changing pattern figure corresponding with above-mentioned delta data, and upgrades the value of its volume of traffic matrix key element adjacent with the volume of traffic of above-mentioned corresponding matrix key element.
5. according to any described traffic volume forecast device in the claim 1～4, it is characterized in that,
Above-mentioned prognosis traffic volume calculating part multiply by by short matrix key element of time of reviewing from predetermined point of time to be compared the big weight coefficient of weight with long matrix key element of the time of reviewing from predetermined point of time and obtains above-mentioned evaluation of estimate.
6. according to any described traffic volume forecast device in the claim 1～5, it is characterized in that,
The traffic data that above-mentioned changing pattern figure comprises the above-mentioned predetermined point of time in other intervals different with above-mentioned predetermined interval is used as the matrix key element,
Above-mentioned changing pattern figure renewal section is when obtaining above-mentioned predetermined interval and above-mentioned other interval traffic datas; From above-mentioned changing pattern figure storage part, read the changing pattern figure corresponding with the traffic data of above-mentioned predetermined interval; And from above-mentioned traffic data storage part, read the delta data of the volume of traffic of above-mentioned predetermined interval; Upgrade the value of the matrix key element of the above-mentioned changing pattern figure corresponding with the delta data of reading; And the value of the matrix key element that renewal is corresponding with above-mentioned other interval traffic datas
Above-mentioned prognosis traffic volume calculating part is read the delta data of the up-to-date volume of traffic in above-mentioned other intervals from above-mentioned traffic data storage part, a plurality of changing pattern figure at above-mentioned other intervals, value according to the matrix key element corresponding with the delta data of being read is obtained evaluation of estimate, and obtain with above-mentioned evaluation of estimate and be used as above-mentioned other interval prognosis traffic volumes for the corresponding volume of traffic of the highest changing pattern figure, from above-mentioned traffic data storage part, read the delta data of the up-to-date volume of traffic of above-mentioned predetermined interval, a plurality of changing pattern figure at above-mentioned predetermined interval, according to the value of the matrix key element corresponding with the delta data of being read and with obtain evaluation of estimate at the value of the corresponding matrix key element of above-mentioned other interval above-mentioned prognosis traffic volume data of obtaining, and obtain the prognosis traffic volume that is used as above-mentioned predetermined interval with above-mentioned evaluation of estimate for the corresponding volume of traffic of the highest changing pattern figure.
7. traffic volume forecast device according to claim 6 is characterized in that,
Use the interval adjacent to be used as above-mentioned other intervals with above-mentioned predetermined interval.
8. traffic volume forecast device according to claim 6 is characterized in that,
The interval that use has following changing pattern figure is used as above-mentioned other intervals:
With the similar degree of the changing pattern figure of above-mentioned predetermined interval changing pattern figure greater than predetermined threshold.
9. Traffic volume forecasting method, it comes prognosis traffic volume by the traffic volume forecast device, and this method comprises:
Above-mentioned traffic volume forecast device is obtained the step of traffic data of the road of predetermined interval;
Above-mentioned traffic volume forecast device is stored in step in the traffic data storage part with obtained traffic data;
Above-mentioned traffic volume forecast device is prepared the step of changing pattern figure storage part, a plurality of changing pattern figure of generating of the volume of traffic put on schedule of this changing pattern figure storage portion stores wherein, this changing pattern figure represents that by matrix the volume of traffic that reaches above-mentioned each volume of traffic changes, and this matrix is made of the volume of traffic of the time of reviewing from predetermined point of time with the time point of tracing back to;
Above-mentioned traffic volume forecast device is read the changing pattern figure corresponding with obtained traffic data from above-mentioned changing pattern figure storage part when obtaining above-mentioned traffic data, and from above-mentioned traffic data storage part, read the delta data of the above-mentioned volume of traffic, and upgrade the step of value of the matrix key element of the above-mentioned changing pattern figure corresponding with the delta data of being read;
Above-mentioned traffic volume forecast device is read the delta data of the up-to-date volume of traffic from above-mentioned traffic data storage part, at a plurality of changing pattern figure, value according to the matrix key element corresponding with the delta data of being read is obtained evaluation of estimate, and obtains the step that is used as prognosis traffic volume with above-mentioned evaluation of estimate for the corresponding volume of traffic of the highest changing pattern figure; And
Above-mentioned traffic volume forecast device is exported the step of above-mentioned prognosis traffic volume.
10. program that is used for prognosis traffic volume, it makes computing machine carry out following steps:
Obtain the step of traffic data of the road of predetermined interval;
Obtained traffic data is stored in step in the traffic data storage part;
The step of changing pattern figure storage part is prepared in the zone of guaranteeing to store a plurality of changing pattern figure of volume of traffic generation on schedule, this changing pattern figure represents that by matrix the volume of traffic that reaches above-mentioned each volume of traffic changes, and this matrix is made of the volume of traffic of the time of reviewing from predetermined point of time with the time point of tracing back to;
When obtaining above-mentioned traffic data, from above-mentioned changing pattern figure storage part, read the changing pattern figure corresponding with obtained traffic data, and from above-mentioned traffic data storage part, read the delta data of the above-mentioned volume of traffic, and upgrade the step of value of the matrix key element of the above-mentioned changing pattern figure corresponding with the delta data of being read;
From above-mentioned traffic data storage part, read the delta data of the up-to-date volume of traffic, at a plurality of changing pattern figure, value according to the matrix key element corresponding with the delta data of being read is obtained evaluation of estimate, and obtains the step that is used as prognosis traffic volume with above-mentioned evaluation of estimate for the corresponding volume of traffic of the highest changing pattern figure; And
Export the step of above-mentioned prognosis traffic volume.
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| CN104848871A (en) * | 2015-06-09 | 2015-08-19 | 刘光明 | Map having traffic condition change trend, and drive route |
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| JP2011209818A (en) | 2011-10-20 |
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