CN105096590B - Traffic information creating method and traffic information generating device - Google Patents
Traffic information creating method and traffic information generating device Download PDFInfo
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Abstract
The invention proposes a kind of traffic information creating methods, comprising: the Floating Car position data from each time point that each vehicle travelled from road surface uploads is received, as floating car data；The same vehicle for capturing and recording by Car license recognition using video monitoring system fits multiple active position information of the vehicle at multiple time points of monitoring, the floating car data as the vehicle in the appearance information of multiple monitoring points；The floating car data of floating car data and each vehicle fitted that each vehicle uploads is fused together, final floating car data is formed；And final floating car data is utilized, generate the traffic information of the traffic condition on each road chain that expression vehicle is travelled.
Description
Technical field
The present invention relates to Real-time Traffic Information process fields, more particularly, to a kind of traffic information creating method and friendship
Logical information generating device, GPS data made of the GPS data of Floating Car upload can be utilized and be fitted as license plate identification data,
The traffic information (such as congestion in road degree) on road is generated in real time.
Background technique
Using floating car technology acquisition Real-time Traffic Information, the method for congestion in road degree is calculated by Chinese city institute
It is widely used.United States Patent (USP) US6546330 (2003), Chinese patent CN200610112606, CN200710087223,
CN200810112607 etc. is proposed oneself Floating Car processing system and method, is all based on the vehicle travelled on road surface
The GPS data that (Floating Car) uploads, these patents are different in implementation detail, but basic principle is similar: being all that acquisition is floating
Then the GPS information of motor-car matches GPS data on the road into electronic map, finally by the vehicle calculated between two o'clock
Average overall travel speed derives the congestion level of road with more vehicle average speeds.Floating car technology commercialization for many years,
In actual application, the precision of floating vehicle system be not still it is very high, main error is to lead to map by GPS accuracy is not high
Caused by mismatch is missed.Mostly using taxi as Floating Car in existing floating vehicle system, the GPS device precision on vehicle is not very
Height, precision is probably at 30~50 meters or so, and the elevation information of vertical direction or no or precision are very poor, in reality
The overlapping road of different height in indistinguishable overpass, viaduct.Due to high building, overpass, complicated grade separation in big city
Bridge etc. blocks GPS signal, also often will appear GPS signal drift when vehicle driving is around these buildings, leads to vehicle
By in system matches to wrong path.For theoretically, the hardware performance of system is improved, improves the precision of GPS device, it can
Partially to overcome these disadvantages.It is done so that will increase the investment and operation cost of system, commercially lack feasibility.
Pair for the precision problem of floating vehicle system, existing one kind solution is the method using data fusion, i.e.,
A variety of collected traffic informations of traffic sensor are merged, and are used and are finally merged obtained result as real-time traffic states
Assessed value, the method as mentioned in Chinese patent application CN201210250735.0 and CN201310008385.1.Such methods
Basic principle be: estimating road traffic state is distinguished to the traffic data that is obtained by different acquisition mode, then further according to
Certain blending algorithm carries out some form of Weighted Fusion to the traffic behavior that different modes obtain.May be summarized to be
The fusion that the output end of all kinds of traffic behavior computing systems carries out result calculates again, and the limitation of this method is different acquisition side
The data type of the acquisition of formula is inconsistent, and the interval of data acquisition is also different, and obtained traffic parameter is different, only in all kinds of friendships
The output end of logical state computation service system merges traffic behavior, and confidence level is not high.Especially when certain two class system
It is relatively difficult to the trade-off of result when output state is opposite, increase the complexity of system, new error may be introduced.
Summary of the invention
Cause floating vehicle system in complex road surfaces such as overpass, viaducts in order to solve aforementioned GPS signal low precision
The problem of low precision, the present invention propose that a kind of fusion floating car data is smart to improve floating vehicle system with vehicle license plate identification data
The method of degree, different from the usual way of such as aforesaid known example CN201210250735.0 and CN201310008385.1, this hair
The bright method is not merged again in result of the output end of sorts of systems to traffic behavior, in the input of system
Input data is merged at end, then fused data are inputted to the floating vehicle system of existing maturation, obtains accurately
Real-time traffic states.
In order to overcome the drawbacks described above of the prior art to propose the present invention.Therefore, an object of the present invention is proposition one
Kind traffic information creating method and traffic information generating device, can be using the GPS data of Floating Car upload and by Car license recognition
GPS data made of data fitting generates the traffic information (such as congestion in road degree) on road in real time.
To achieve the goals above, according to the invention it is proposed that a kind of traffic information creating method, comprising: receive from road
The Floating Car position data at each time point that each vehicle travelled on face uploads, as floating car data；Utilize video monitoring
The same vehicle that system is captured and recorded by Car license recognition fits the vehicle multiple in the appearance information of multiple monitoring points
Multiple active position information at time point of monitoring, the floating car data as the vehicle；The Floating Car number that each vehicle is uploaded
It is fused together according to the floating car data with each vehicle fitted, forms final floating car data；And it utilizes finally
Floating car data generates the traffic information of the traffic condition on each road chain that expression vehicle is travelled.
Preferably, the floating car data of the vehicle fitted includes the information of road chain locating for vehicle, and from each vehicle
The floating car data of biography does not include the information of road chain locating for vehicle.
Preferably, it when generating the traffic information, for the floating car data of the vehicle fitted, is not necessarily to the fitting
Floating car data out is matched on the chain of road, and the floating car data for uploading from each vehicle, then is needed the floating of the upload
In motor-car Data Matching to road chain.
Preferably, the floating car data of floating car data and each vehicle fitted that each vehicle uploads is fused together
The step of include: the time interval that floating car data is uploaded according to vehicle, the floating car data of each vehicle fitted is carried out
Interpolation.
Preferably, the multiple active position information is to be less than each monitoring of predetermined time interval in mutual time interval
Multiple location informations of time point vehicle obtained.
Preferably, the multiple active position information is within predetermined value with the time difference of present system time
Multiple location informations of each time point of monitoring vehicle obtained.
Preferably, the step of generating the traffic information using final floating car data includes: the vehicle for increasing and fitting
Floating car data weight, and reduce the weight of floating car data uploaded from each vehicle, travelled on each road chain to calculate
Vehicle average speed.
In addition, according to the present invention, it is also proposed that a kind of traffic information generating device, comprising: what reception was travelled from road surface
The Floating Car position data at each time point that each vehicle uploads, the unit as floating car data；Utilize video monitoring system
It is captured by Car license recognition and the same vehicle that records is in the appearance information of multiple monitoring points, fit the vehicle in multiple monitoring
Multiple active position information at time point, the unit of the floating car data as the vehicle；And each vehicle is uploaded floating
Motor-car data and the floating car data of each vehicle fitted are fused together, and form the unit of final floating car data；With
And final floating car data is utilized, generate the list of the traffic information of the traffic condition on each road chain that expression vehicle is travelled
Member.
According to the present invention, the traffic information generated based on two kinds of traffic data sources can provide the user with more in complicated highway section
Accurate traffic information.
Detailed description of the invention
Detailed description by reference to following combination attached drawing to used preferred embodiment, above-mentioned mesh of the invention
, advantages and features will become more apparent from, in which:
Fig. 1 is to show the schematic block diagram of processing system according to the present invention.
Fig. 2 is for illustrating to capture by Car license recognition and same vehicle being recorded the case where multiple monitoring points occur
Schematic diagram.
Fig. 3 is to show the schematic block diagram of the system hardware structure of the embodiment of the present invention.
Fig. 4 is the flow chart shown for realizing the processing of multi-source data traffic information.
Fig. 5 is to show an exemplary flow chart of traffic information generating process according to an embodiment of the present invention.
Fig. 6 is the schematic diagram for illustrating scene that vehicle travels near parallel main and side road.
Specific embodiment
The preferred embodiment of the present invention is described below with reference to the accompanying drawings.In the accompanying drawings, identical element will be by identical ginseng
Examine symbol or digital representation.In addition, the specific descriptions to known function and configuration will be omitted in following description of the invention,
To avoid keeping subject of the present invention unclear.
Fig. 1 is to show the schematic block diagram of processing system according to the present invention.As shown in Figure 1, the invention proposes one kind
The method that fusion floating car data and vehicle license plate identify data to improve floating vehicle system precision.It crosses as described above,
Method of the present invention is not merged again in result of the output end of sorts of systems to traffic behavior, in system
Input terminal merges input data, and then fused data are inputted to the floating vehicle system of existing maturation, obtain standard
True real-time traffic states.
It is pointed out here that vehicle license plate identification is typically all basic vehicle video identification technology, current high definition is taken the photograph
Camera is more more and more universal in road monitoring field, and the development trend of these high-definition cameras is also to collect multiple functions in one
Body, wherein Car license recognition function is also becoming one of standard feature for traffic high-definition camera.According to country about " public
Road vehicles intelligent monitoring and recording system general technology " (GA/T497-2009) requirement, the accuracy requirement of Car license recognition is white
It is greater than 90%, and night is greater than 80%.So Vehicle License Plate Recognition System provides a kind of more accurately data source.And due to taking the photograph
The position of camera is relatively fixed and accurate, road locating for the vehicle identified i.e. accurate, and vehicle is not present
The error problem of path adaptation.With popularizing for the high-definition camera with Car license recognition function, video monitoring system can be real
The information that same vehicle occurs in multiple monitoring points is now captured and is recorded by Car license recognition.
As shown in Fig. 2, if the location information of these monitoring cameras (monitoring point) of C2, C3 is fitted to by the C1 in Fig. 2
The location information of vehicle, then multiple location informations can be fitted to same vehicle, even if this vehicle does not upload GPS location
Information can also be considered as a Floating Car to handle.
This precision for fitting the GPS data come is to be determined by the position precision of video camera, and video camera is accurate
Location information often determines that when installing video camera, will not due to road complexity and accuracy decline, encounter overhead, vertical
The complex situations such as bridge, parallel main and side road are handed over also to be able to maintain very high position accuracy, so being calculated with the GPS data of this fitting complicated
The traffic behavior of road is more accurate than the GPS data uploaded with common Floating Car, can solve floating vehicle system in complicated road
The not high problem of road precision.
It is pointed out here that because the Vehicle License Plate Recognition System of floating vehicle system of the present invention, vehicle is all ratio
More mature system can be improved real so method of the present invention has very high commercial viability with relatively low cost
When traffic information precision.
Fig. 3 is the system hardware structure figure of the embodiment of the present invention, is divided into data collection station and centring system.Data acquisition
Terminal is mainly that Floating Car acquisition GPS data uploads to center and monitor camera acquisition vehicle license plate data upload to
System is felt concerned about, because not being emphasis of the invention, data collection station is not elaborated in the present specification.Centring system
It include: communication link 200, the data and issue Real-time Traffic Information outward that acquisition terminal uploads for receiving data；
Storage device 300, for storing GPS data, license plate identification data, floating car data and the traffic information being calculated；
GPS data is fitted device 400, for license plate identification data to be fitted to the GPS data of vehicle location；Data integration device 500,
For the GPS of former Floating Car and the resulting GPS of fitting to be fused to the floating car data formatted；Traffic information calculation device
600, floating car data is handled to obtain Real-time Traffic Information；And traffic information issuing device 700, for being sent out to user
Cloth Real-time Traffic Information.
Centring system is built based on mature floating vehicle system, and the hardware cells such as communication, storage, calculating, publication are all
It is to have mature technology, so all no longer doing excessive introduction for relevant apparatus 200,600,700.It introduces in storage device
How 300 data saved and device 400,500 cooperate.The Floating Car car-mounted device of data collection station obtains
The data such as the real time position in relation to vehicle, for real-time delivery to centring system, this part is also very mature technology, is no longer done excessive
It introduces.Road monitoring camera (such as electronic police) device of data collection station obtains the license board information in relation to vehicle, real
When pass to centring system, this part is also very mature technology, no longer does excessive introduction.This specification is felt concerned about in introducing
System is how to carry out calculation processing after receiving the information from data collection station.
Fig. 4 is the flow chart shown for realizing the processing of multi-source data traffic information.
In general the format of GPS data is as shown in table 1 in Fig. 4.The format of GPS data is not limited to word listed by table 1
Section, but the field in table 1 should be included.
One example of 1 GPS data format and content of table
The format of license plate identification data is as shown in table 2 in Fig. 4.The format of license plate identification data is not limited to listed by table 2
Field, but the field in table 2 should be included.The corresponding relationship that license plate number and vehicle ID is illustrated in table 3, in the meter of system
During calculation, use " license plate number " more convenient using vehicle ID ratio.It will also be mentioned in aftermentioned text, it will using vehicle ID
Help to distinguish the GPS data that Floating Car uploads and the GPS data that vehicle identification data is fitted.
One example of 2 license plate identification data format and content of table
The example of 3 license plate of table number and the corresponding relationship of vehicle ID
| License plate number | Vehicle ID |
| Capital LG8**8 | 2170831 |
| Capital NG8**7 | 3298881 |
| Capital KG1**8 | 3387661 |
The format of camera position data is as shown in table 4 in Fig. 4.The format of camera position data is not limited to 4 institute of table
The field of column, but the field in table 4 should be included." shooting camera ID " in field " video camera ID " and table 2 in table 4 is
It is the number for identifying the road monitoring camera of license plate, the two number corresponds, and can be used for the correlation inquiry of two tables.In table 4
" road chain number " field refer to camera supervised road road chain number.
One example of 4 camera position data format of table and content
For traditional floating vehicle system, the received GPS data from Floating Car is all often that each is floating
The series of data of motor-car is spaced more than ten seconds to tens seconds on the adjacent GPS data time of same vehicle and differs, in table 1
The GPS point interval of vehicle 216038 is about at 30 seconds or so.So license plate identification data must be also fitted to it is similar based on
The continuous GPS data of same vehicle could merge its input terminal with the GPS data of Floating Car in system.This by
GPS data is fitted device 400 and completes, and processing step is as follows:
1) according to table 2 and table 3, the data of same vehicle ID are retrieved and by time-sequencing from database, are obtained
Data set as shown in table 5.
One example of the license plate identification data collection of a certain vehicle of table 5
2) continuity of the data of same vehicle in table 5 further, is analyzed, if concentrated two-by-two in a data
The shooting interval of adjacent license plate identification data is less than certain time-wise separation Td (such as 10 minutes), is considered as this data
The data of concentration are generated from a driving process of the vehicle, the intermediate behavior that traveling is interrupted without parking.So-called middle line-break
The behavior sailed refers to that vehicle stopping, engine misses, user get off and handles other affairs.Because Vehicle License Plate Recognition System is whole day
Work in 24 hours, it has been identified repeatedly it seem likely that there is same vehicle, but the interval of data is all that difference is several every time
The case where hour, then such license plate identification data cannot be used for fitting GPS data, because in these hours, vehicle
Being likely to most times is on parking stall, and data cannot reflect road conditions.The data element number of data set is necessary
Greater than equal 2, otherwise this data set is individual data point, to be ignored in subsequent calculating.
3) if fitting GPS data is calculated for Real-time Traffic Information, that is just also contemplated that the timeliness of data, that is, counts
According to time cannot be too wide in the gap with present system time.Such as certain a string of Time Continuous data of vehicle 2170813 in table 5
The poor Tcd of center time point and present system time is necessarily less than 10 minutes.Parameter Td and Tcd in above-mentioned steps 2 and 3 are
The system parameter that can be set by the user.Its specific value difference has no effect on realization of the invention, belongs to of the invention
Scope.
4) after obtaining the effective vehicle identification data of a data set shown in table 5, according to the position of video camera in table 4
Confidence breath, fits effective vehicle GPS data, as shown in table 6." GPS time " in table 6, " longitude ", " latitude ", " road chain
Number " be all fitted according to the data and vehicle identification data of video camera come, be equivalent to respectively in table 5 " when shooting
Between ", " longitude " of the video camera in table 4, " latitude ", " road chain number ".
One example of the fitting GPS data of the same vehicle of table 6
After device 400 is successfully fitted GPS data, following device 500 will merge the GPS data and vehicle of Floating Car upload
Board identifies the GPS data of data fitting, forms final floating car data as the input of traffic information calculation device 600.
The format of so-called floating car data and the example of data are as shown in table 7.
The format of 7 floating car data of table and the example of data
When merging GPS data in device 500, it should be noted that 3 points:
1) GPS data that is expressed as Floating Car upload of " the road chain number " field value equal to null in table 7, because of Floating Car
The GPS data of upload is not matched on the chain of road also at this time, so " road chain number " is sky.The GPS number of license plate identification data fitting
According to " road chain number " value for sky, value be equal to table 4 in video camera " road chain number ".
2) because Floating Car itself is also possible to be identified by Vehicle License Plate Recognition System, same vehicle may be deposited both
In the original GPS data that Floating Car uploads, there is also the GPS datas of license plate identification data fitting.Because of " the road of two kinds of data
Chain number " field is different, so cannot need at this time to formulate a set of energy by two kinds of data mixings at the same vehicle ID and distinguish
The vehicle ID naming rule of the two.For example, vehicle ID uses 7 for the GPS data of license plate identification data fitting, referred to as intend
Close vehicle ID.And for the GPS data that Floating Car directly uploads, vehicle ID uses 6, referred to as original vehicle ID.In this case,
The license plate number of table 3 and the corresponding relationship of vehicle ID will be newly defined as shown in table 8.When specific implementation, vehicle ID is using more
Few position can be customized by system designer, and design does not affect realization of the invention anyway.
The example of 8 license plate of table number and the corresponding relationship of vehicle ID
| License plate number | It is fitted vehicle ID | Original vehicle ID |
| Capital LG8**8 | 2170831 | 217083 |
| Capital NG8**7 | 3298881 | 329888 |
| Capital KG1**8 | 3387661 | 338766 |
3) time interval of the adjacent data for the GPS data that Floating Car uploads is mostly at tens seconds or so, the GPS number of fitting
According to being obtained with license plate identification data, the time interval of adjacent data is relatively long, may clock in a measure, this is because mesh
The density of the laying of preceding road monitoring camera is not very high.In the case of too big for adjacent fitting GPS data time interval,
Some virtual GPS datas are fitted using the scheme of intermediate interpolated.The scheme of interpolation is mainly based upon between points
Route searching.Such as three fitting GPS datas of the vehicle for being 2170831 of the vehicle ID in table 7, adjacent time inter 3-4
Minute, the method for carry out interpolation to it are as follows:
3-1) using first fitting GPS point as starting point, second fitting GPS point is transit point, and third fitting GPS point is
Terminal carries out Shortest Path Searching, finds out shortest path, calculates average speed v (meter per second).
3-2) using first point as starting point, with average speed v (meter per second) for travel speed, (such as 30 after calculating t seconds
Second) position that reaches of vehicle and affiliated road chain number, in this, as first interpolation point.
It is traveling speed with average speed v (meter per second) 3-3) then with the interpolation point in step 3-2) for new starting point
Degree, the position and affiliated road chain number that (such as 30 seconds) vehicle reaches after calculating t seconds, in this, as second interpolation point.
3-4) repeat step 3-2), 3-3) until new interpolation point and it is next fitting GPS point time interval be less than t seconds
(such as 30 seconds).
3-5) using nearest fitting GPS point as starting point, repeat step 3-2), 3-3), 3-4) to the last one fitting
GPS point completes the calculating of whole interpolation points.
By the above interpolation calculation, floating car data is reformed into as shown in table 9 in table 7:
The format of 9 floating car data of table and the example (containing interpolation) of data
After floating car data as shown in table 9 is stored in storage device 330, traffic information calculation device 600
The calculating of traffic information is carried out according to traditional floating vehicle system calculation, the calculating of this part is because be well known skill
Art is illustrated not as emphasis of the invention, but in order to keep explanation of the invention more complete and understandable, is briefly described
The process flow of traffic information calculation device 600, as shown in Figure 5.It should be pointed out that traffic information shown in fig. 5 calculated
Journey is only an example, and for the present invention and non-limiting.
In traffic information calculation processing process described in Fig. 5, first determine whether floating car data road chain number whether
For empty (Null).If it is sky, this floating car data is the original GPS data uploaded by Floating Car, because of Floating Car
The GPS data of upload is not matched on the chain of road also at this time, so " road chain number " is sky.The GPS number of license plate identification data fitting
According to the value of " road chain number " be not sky, these floating car datas are considered having been matched on the chain of road, road chain number etc.
" the road chain number " of video camera in table 4.Once floating car data is all matched on specific road chain, next just to belonging to
Time difference and the distance interval that point-to-point transmission is calculated with the floating car data of the same vehicle on chain all the way can also calculate same
All the way on chain each car average speed.For a road chain, from the average speed of all vehicles thereon, so that it may calculate
To the average speed of entire road chain.The average speed of each road chain also just constitutes the traffic information of entire road network.
It the characteristics of in view of the fitting GPS data set forth in the present invention based on Car license recognition, can also be to traditional floating
Vehicle system proposes following improve:
If 1) system is further connected with information of vehicles library, the class of corresponding vehicle can be obtained from license plate number
Type, then can reject some special cars such as bus from fitting GPS data, the calculating for improving traffic information is accurate
Degree.Because bus has the bus stop factors such as passenger up and down, driving behavior is different from the driving behavior of common vehicle, Bu Nengyong
In calculating common traffic information, only for calculating the traffic information based on bus trip mode.
2) for the road structure of the complexity such as viaduct, overpass, parallel main and side road, because of the position of road monitoring camera
Confidence breath is more accurate than the GPS information that Floating Car uploads, and does not have GPS drifting problem, so by license plate identification data fitting
GPS data is more accurate than the GPS uploaded by Floating Car.In these special places, the calculating of fitting GPS data can be increased
Weight reduces the calculating weight for the GPS data that Floating Car uploads.In this way, the calculated result of final traffic information will be more quasi-
Really.For example, the scene of parallel main and side road as shown in Figure 6.
From fig. 6 it can be seen that since camera position can be accurately positioned on main road or bypass, so license plate
The GPS data for identifying data fitting, can accurately be matched to main road road chain.The GPS data uploaded for Floating Car, it is contemplated that
Main and side road very close to, and GPS data itself has certain error, so being difficult accurate judgement vehicle is to be located at main road or bypass,
Road chain matching result application condition is big.It in this case, can in order to keep the calculated result of final traffic information more accurate
To increase the calculating weight of fitting GPS data in the calculating process of the road chain average speed in Fig. 6, reduces Floating Car and upload
GPS data calculating weight.
The method described in the present invention critical issue to be solved is how to realize the GPS of license plate identification data and Floating Car
The fusion problem of data.The key for solving this problem is that license plate identification data is fitted to GPS data, extracts Car license recognition number
According to middle implied vehicle position information.License plate identification data is obtained by road monitoring camera, so road monitoring is taken the photograph
The location information of camera may be used for the location information of fitting vehicle.In view of the position of monitor camera is fixed and is compared
It is accurate, so the GPS position information of fitting is also relatively more accurate, what these GPS informations obtained when calculating for traffic information
As a result relatively more accurate.Different from traditional traffic information fusion method, method of the present invention is the input terminal pair in system
Data are merged, so that the data format of two kinds of data sources carries out unification, data processing meter is then carried out in input system
It calculates.By improving the accuracy of input data, in the case where not changing existed system itself, improves system and export traffic information
Accuracy, the improved cost of system can be reduced in this way.At the same time it can also be fitted GPS data by improving in complicated highway section
Weight, it is further to improve the precision of information on complicated highway section, realize that more targeted precision improves.By
The data fusion of data input pin realizes low cost, the system accuracy of high repayment improves.
Several specific embodiments are enumerated above the present invention is elaborated, this few example only illustrate the principle of the present invention and
Its implementation method is used, rather than limitation of the present invention, without departing from the spirit and scope of the present invention, this field
Technical staff can also make various changes and improvements.Therefore, the present invention should not be limited by above-described embodiment, and should be by appended
Appended claims and their equivalents limit.
Claims (7)
1. a kind of traffic information creating method, comprising:
The Floating Car position data from each time point that each vehicle travelled from road surface uploads is received, as floating car data；
The same vehicle for capturing and recording by Car license recognition using video monitoring system is intended in the appearance information of multiple monitoring points
Multiple active position information of the vehicle at multiple time points of monitoring are closed out, as the floating car data of the vehicle, and according to
Vehicle uploads the time interval of floating car data, carries out interpolation to the floating car data of each vehicle fitted；
The floating car data of floating car data and each vehicle after fitting and interpolation that each vehicle uploads is fused together, is formed
Final floating car data；And
Using final floating car data, the traffic information of the traffic condition on each road chain that expression vehicle is travelled is generated.
2. traffic information creating method according to claim 1, which is characterized in that
The floating car data of the vehicle fitted includes the information of road chain locating for vehicle, and the Floating Car number uploaded from each vehicle
According to the information for not including road chain locating for vehicle.
3. traffic information creating method according to claim 1, which is characterized in that
When generating the traffic information, for the floating car data of the vehicle fitted, without the Floating Car for fitting this
In Data Matching to road chain, and the floating car data for being uploaded from each vehicle, then it needs the floating car data of the upload
It is fitted on the chain of road.
4. traffic information creating method according to claim 1, which is characterized in that
The multiple active position information is that each time point of monitoring for being less than predetermined time interval in mutual time interval is obtained
Multiple location informations of the vehicle obtained.
5. traffic information creating method according to claim 1, which is characterized in that
The multiple active position information is in each monitoring period being within predetermined value with the time difference of present system time
Multiple location informations of point vehicle obtained.
6. traffic information creating method according to claim 1, which is characterized in that
Include: using the step of final floating car data generation traffic information
Increase the weight of the floating car data of the vehicle fitted, and reduce the weight of the floating car data uploaded from each vehicle,
To calculate the average speed of the vehicle travelled on each road chain.
7. a kind of traffic information generating device, comprising:
The Floating Car position data from each time point that each vehicle travelled from road surface uploads is received, as floating car data
Receiving unit；
The same vehicle for capturing and recording by Car license recognition using video monitoring system is intended in the appearance information of multiple monitoring points
Multiple active position information of the vehicle at multiple time points of monitoring are closed out, as the floating car data of the vehicle, and according to
Vehicle uploads the time interval of floating car data, and the fitting unit of interpolation is carried out to the floating car data of each vehicle fitted；
And
The floating car data of floating car data and each vehicle after fitting and interpolation that each vehicle uploads is fused together, is formed
The integrated unit of final floating car data；And
Using final floating car data, the life of the traffic information of the traffic condition on each road chain that expression vehicle is travelled is generated
At unit.
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| CN105279960B (en) * | 2015-12-02 | 2018-10-23 | 山东大学 | Device and working method are studied and judged in the different domain traffic vehicle trip in city of compatible Big Dipper GNSS space time informations |
| WO2017117716A1 (en) * | 2016-01-05 | 2017-07-13 | 冯旋宇 | Outdoor positioning management method and system for smart city |
| CN106840181B (en) * | 2016-12-09 | 2022-06-17 | 斑马信息科技有限公司 | System and method for determining vehicle position |
| CN107038762A (en) * | 2017-04-13 | 2017-08-11 | 山东大学 | Method of work and system based on the trip management and control of Big Dipper space-time data |
| CN109426791B (en) * | 2017-09-01 | 2022-09-16 | 深圳市金溢科技股份有限公司 | Multi-site and multi-vehicle matching method, server and system |
| CN107888877B (en) * | 2017-11-13 | 2020-10-09 | 深圳市戴升智能科技有限公司 | Method and system for vehicle tracking and road traffic information acquisition |
| CN108922412A (en) * | 2018-06-27 | 2018-11-30 | 芜湖盘云石磨新能源科技有限公司 | A kind of new energy highway billboard |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6178374B1 (en) * | 1996-10-10 | 2001-01-23 | Mannesmann Ag | Method and device for transmitting data on traffic assessment |
| DE102005053461A1 (en) * | 2005-11-04 | 2007-05-16 | Deutsch Zentr Luft & Raumfahrt | Device for traffic control, has two camera computer systems and traffic simulation is carried out by central traffic simulation computer on basis of data of distributed camera computer systems and by data of XFCD vehicles |
| CN1976296A (en) * | 2006-12-25 | 2007-06-06 | 北京世纪高通科技有限公司 | Method and system for real-time dynamic traffic information collecting, handling, and issuing |
| CN1975800A (en) * | 2006-12-25 | 2007-06-06 | 北京世纪高通科技有限公司 | Traffic information fusion processing method and system |
| CN101571997A (en) * | 2009-05-31 | 2009-11-04 | 上海宝康电子控制工程有限公司 | Method and device for fusion processing of multi-source traffic information |
| CN101739824A (en) * | 2009-11-12 | 2010-06-16 | 上海第二工业大学 | Data fusion technology-based traffic condition estimation method |
| CN102646332A (en) * | 2011-02-21 | 2012-08-22 | 日电（中国）有限公司 | Traffic state estimation device and method based on data fusion |
| CN102930735A (en) * | 2012-10-25 | 2013-02-13 | 安徽科力信息产业有限责任公司 | City real-time traffic and road condition information issuing method based on traffic video |
-
2014
- 2014-04-23 CN CN201410165606.0A patent/CN105096590B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6178374B1 (en) * | 1996-10-10 | 2001-01-23 | Mannesmann Ag | Method and device for transmitting data on traffic assessment |
| DE102005053461A1 (en) * | 2005-11-04 | 2007-05-16 | Deutsch Zentr Luft & Raumfahrt | Device for traffic control, has two camera computer systems and traffic simulation is carried out by central traffic simulation computer on basis of data of distributed camera computer systems and by data of XFCD vehicles |
| CN1976296A (en) * | 2006-12-25 | 2007-06-06 | 北京世纪高通科技有限公司 | Method and system for real-time dynamic traffic information collecting, handling, and issuing |
| CN1975800A (en) * | 2006-12-25 | 2007-06-06 | 北京世纪高通科技有限公司 | Traffic information fusion processing method and system |
| CN100463009C (en) * | 2006-12-25 | 2009-02-18 | 北京世纪高通科技有限公司 | Traffic information fusion processing method and system |
| CN101571997A (en) * | 2009-05-31 | 2009-11-04 | 上海宝康电子控制工程有限公司 | Method and device for fusion processing of multi-source traffic information |
| CN101739824A (en) * | 2009-11-12 | 2010-06-16 | 上海第二工业大学 | Data fusion technology-based traffic condition estimation method |
| CN102646332A (en) * | 2011-02-21 | 2012-08-22 | 日电（中国）有限公司 | Traffic state estimation device and method based on data fusion |
| CN102930735A (en) * | 2012-10-25 | 2013-02-13 | 安徽科力信息产业有限责任公司 | City real-time traffic and road condition information issuing method based on traffic video |
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