CN101783069A - Traffic information fusion processing method and system - Google Patents
Traffic information fusion processing method and system Download PDFInfo
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- CN101783069A CN101783069A CN200910244107A CN200910244107A CN101783069A CN 101783069 A CN101783069 A CN 101783069A CN 200910244107 A CN200910244107 A CN 200910244107A CN 200910244107 A CN200910244107 A CN 200910244107A CN 101783069 A CN101783069 A CN 101783069A
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Abstract
The embodiment of the invention provides a traffic information fusion processing method and a system, relating to information fusion technology. The invention can realize the information fusion of various information collection modes with high accuracy and large covering surface. The solution comprises the following steps: circularly reading source data collected by at least one collection mode on at least one road in a period; respectively processing the source data collected by various collection modes to obtain one general specification road situation data record of each piece of source data; and performing fusion processing on all records in the general specification road situation data to obtain the comprehensive road situation information of at least one road in the period. The embodiment of the invention is used for traffic information fusion processing.
Description
Technical field
The present invention relates to information fusion technology, relate in particular to a kind of traffic information fusion processing method and system.
Background technology
Along with going from bad to worse of urban traffic conditions, many countries have carried out research and the construction about intelligent transportation system (ITS).Intelligent transportation system is relaxing road congestion and to reduce traffic hazard, improve the traffic user convenience, comfortable be purpose, utilize the general name of the traffic system of traffic information system, communication network, positioning system and intelligent analysis and route selection.The realization of intelligent transportation comprises collection, analysis and the processing of transport information and announces issue to society.
The traffic information collection mode mainly contains fixed form, move mode and manual entry mode.Wherein, fixed form mainly is to utilize such as collection transport information such as magnetic frequency, ripple frequency, videos, the maturation that possesses skills, is easy to grasp, is not subjected to weather environment to influence, guarantee to provide in 24 hours characteristics such as stablizing valid data; Move mode mainly is to utilize such as floating car data, mobile phone signal collecting etc. to gather transport information, and it is low and efficient is high to have a cost, have real-time, the characteristics that coverage is big; The manual entry mode then be by data typing personnel by modes such as broadcasting, network, scenes, obtain transport information effectively replenishing in real time as traffic information processing system input.
In the prior art, proposed the fusion method in single source at traffic information fusion method, but its application scenarios is at the information fusion of many floating car datas on the road, can't effectively utilize various information acquisition modes, accuracy is relatively poor, and coverage rate is lower.
Summary of the invention
Embodiments of the invention provide a kind of traffic information fusion processing method and system, can realize the information fusion of multiple information acquisition mode, accuracy height, wide coverage.
For achieving the above object, embodiments of the invention adopt following technical scheme:
A kind of traffic information fusion processing method comprises:
The source data that at least a acquisition mode at least one road is gathered in the one-period is read in circulation;
Source data to various acquisition mode collections is handled respectively, obtains a common-use size road condition data record of each source data correspondence;
All records in the described common-use size road condition data are carried out fusion treatment, draw the comprehensive traffic information of described at least one road in the described cycle.
A kind of traffic information fusion processing system comprises:
Reading unit is used to circulate and reads the source data that at least a acquisition mode at least one road is gathered in the one-period;
Processing unit is used for the source data of various acquisition mode collections is handled respectively, obtains a common-use size road condition data record of each source data correspondence;
Integrated unit is used for all records of described common-use size road condition data are carried out fusion treatment, draws the comprehensive traffic information of described at least one road in the described cycle.
Traffic information fusion processing method that the embodiment of the invention provides and system, the source data of the various acquisition mode collections on many roads in the one-period is handled respectively, obtain a common-use size road condition data record of each source data correspondence, then all records in the common-use size road condition data are carried out fusion treatment, draw the comprehensive traffic information of each bar road in this one-period.Can merge the source data that multiple mode gathers such as fixing, move, avoided the poor accuracy that the collection of single source is caused in the prior art, the problem that coverage rate is low merges by multi-source data, can improve accuracy, complementarity, the increase coverage rate of traffic information.
Description of drawings
In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art, to do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art below, apparently, accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.
The FB(flow block) of the traffic information fusion processing method that Fig. 1 provides for the embodiment of the invention;
The probability assignments functional arrangement that Fig. 2 provides for the embodiment of the invention;
The structure block diagram of the traffic information fusion processing system that Fig. 3 provides for the embodiment of the invention;
The structure block diagram two of the traffic information fusion processing system that Fig. 4 provides for the embodiment of the invention;
The structure block diagram three of the traffic information fusion processing system that Fig. 5 provides for the embodiment of the invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment only is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that is obtained under the creative work prerequisite.
The traffic information fusion processing method that the embodiment of the invention provides, as shown in Figure 1, this method step comprises:
The source data that at least a acquisition mode at least one road is gathered in the one-period is read in S101, circulation.
S102, the source data of various acquisition mode collections is handled respectively, obtained a common-use size road condition data record of each source data correspondence.
Concrete, a record in this common-use size road condition data can comprise: acquisition mode classification, the degree of belief to each speed interval, road section length, highway section numbering, highway section grade, highway section number of track-lines etc.
S103, all records in this common-use size road condition data are carried out fusion treatment, draw the comprehensive traffic information of at least one road in this cycle.
Concrete, this fusion treatment can for: according to the degree of belief to each speed interval of at least one record of every road in the common-use size road condition data, the probability assignments function by S type curve obtains the support to this each speed state of road; Then, according to support, obtain the comprehensive traffic information of described road to each speed state of this road.
The traffic information fusion processing method that another embodiment of the present invention provides proposes the multi-source data fusion method based on evidence theory.Mainly describe below from acquisition mode, common-use size road condition data, tripartite this method of facing of multi-source data fusion method.
1, traffic information collection mode
The traffic information collection mode mainly comprises: three kinds of move modes, fixed form, manual entry mode.Wherein:
1. move mode image data source is with collections such as floating car data, mobile phone signalings be applied as the master.Floating car data (Floating Car Data, FCD) vehicle location, direction and the velocity information of vehicle periodic logging in its driving process of equipment GPS, and these information are returned to information center according to certain cycle.It is big that FCD has coverage, cheapness, and Information Monitoring is abundant relatively, round-the-clock advantage, but its bearing accuracy is subjected to the influence of GPS error.
2. fixed form image data source can be divided into three major types, magnetic frequently, as telefault etc.; The ripple frequency is as microwave, ultrasound wave, radar etc.; Video, first-class as video camera.
Wherein, telefault is used widely with its accuracy of detection height, characteristics that cost is low.Telefault is based on the variation that the speciality object causes its inductance value and detects information of vehicles.The a certain section vehicle that it can be used to add up road in the time interval according to determining, calculates required traffic parameter through situation.The parameter that can export is to occupy flow, time average velocity, average vehicle commander and time headway etc.
3. manual entry image data, data typing personnel are by modes such as broadcasting, network, scenes, the real-time transport information of obtaining, as road conditions, incident etc., write down warehouse-in according to predetermined specification, after many people coordinate the arrangement affirmation, as effectively replenishing of traffic information processing system input.
2, common-use size road condition data
Transport information by different modes is gathered after treatment scheme separately, all can generate the common-use size road condition data.These data are based on the road in the electronic chart, and its each bar record all includes acquisition mode classification, the degree of belief to each speed interval, road section length, highway section numbering, highway section grade, highway section number of track-lines.
Details are as follows for related content:
The transport information source category, can for: 00 is FCD, and 01 is the mobile phone signaling, and 10 is coil, and 11 is video, and 20 is manual type etc.
Speed interval, can for: [0,10), [10,20), [20,30), [30,40), [40, ∞), unit is km/h.
Degree of belief a
i, can be [0,1] that this value is relevant with number of objects on the interior road of current period, as vehicle number etc., and satisfy ∑ a
i=1, wherein i is a speed interval quantity.
Road section length can be the length of road shape, the m of unit.
Road number can be the unique identification of road in the electronic chart.
Category of roads, can for: the importance of road is represented, as through street, major trunk roads, subsidiary road etc.
The highway section number of track-lines can be the track quantity that comprises on the road.
For example: record (01,0.67,0.33,0.00,0.00,0.00,200,46616300123,0,3), wherein " 01 " represents that this record derives from the mobile phone signaling; " 0.67 " expression to speed interval [0,10) degree of belief; " 0.33 " expression to speed interval [10,20) degree of belief; " 0.00 " expression to speed interval [20,30) degree of belief; " 0.00 " expression to speed interval [30,40) degree of belief; " 0.00 " expression to speed interval [40, degree of belief ∞); " 200 " expression road section length is 200 meters; " 46616300123 " expression road number is 46616300123; " 0 " expression category of roads is the through street; " 3 " are expressed as the highway section number of track-lines is 3 tracks.
For different source of traffic information, need set up the relational model between raw information and the speed, as the flow-rate pattern of fixed coil etc., can direct estimation highway section travel speed after handle in the mobile data source, manual entry information can be carried out velocity estimation by event type.
This shows that this method can improve the extendability of system greatly,, can carry out data fusion expediently, reduced the coupling of system as long as can convert the source data of gathering to the common-use size road condition data.
3, the fusion method of multi-source data
By the source data that moves, fixes, manual type collects,, generate common-use size road condition data, with of the input of this common-use size road condition data as multi-source data fusion side based on universal architecture through after the corresponding processing procedure.
This fusion method adopts the evidence theory method, can set up incidence matrix between the speed with the data on flows of fixed form and move mode, by critical velocity, determines it to support unimpeded, slow, that block up, thereby and forms and make a strategic decision.The specific implementation method is as follows:
At first determine framework of identification, i.e. speed state set is Ω={ blocking up, slowly, unimpeded }.
According to evidence theory, proposition is the subclass of framework of identification power set, comprises following 8 propositions: 2
Ω=Φ, { blocking up }, { slowly }, { unimpeded }, block up, slowly }, { slowly, unimpeded }, { blocking up, unimpeded }, { blocking up, slowly, unimpeded } }.Wherein, Φ represents empty set; The proposition that comprises an element is as { blocking up }, and { slowly }, { unimpeded } is the primitive proposition; All the other expression states be can not determine, replace with { the unknown } in aftermentioned; Φ is meaningless.
The content of evidence is the intermediate data of this system, the common-use size road condition data that proposed promptly, various different source datas all can generate the common-use size road condition data of unified specification, for a road, may there be the data source of gathering, promptly has many evidences from multiple acquisition mode.
Then, set that each speed state blocks up, the corresponding relation of slow, unimpeded and speed interval, as shown in table 1.
The table 1 road traffic state criteria for classifying (unit: km/h)
Then, determine the probability assignments function, present embodiment goes out by the mode of S curve.As shown in Figure 2, based on speed, wherein unknown portions comprises two kinds of situations, blocks up with slow, slow and unimpeded.
In as 2, transverse axis is a velocity amplitude, and the longitudinal axis is corresponding probability assignments function.If one in the evidence,, need to calculate respectively different interval probability assignments to different speed interval supports.S1, S2, S3 are the state criterion of different brackets road correspondence, promptly less than speed S1 for blocking up, be slowly from S1 to S2, be unimpeded greater than S2.Also as shown in table 1 in this state criteria for classifying of using.
Afterwards, utilize formula
Obtain the support to each speed state of every road, wherein, M
1, M
2... M
nBe n probability assignments function, k is the evidence conflict spectrum, and A is each element except that Φ in the proposition.
At last,, determine { blocking up } of this road, { slowly }, { unimpeded } state according to maximum support to speed state.
The traffic information fusion processing method that the embodiment of the invention provides, with the mobile acquisition mode that combines with stationary phase as transport information, based on Data-Fusion theory, by evidence theory method based on S type curve probability assignments method, realize the multi-source traffic information fusion treatment, improved accuracy, complementarity, the coverage rate of traffic information.And this method also has good extendability and compactedness.
The traffic information fusion processing system that the embodiment of the invention provides as shown in Figure 3, comprising:
Reading unit 301 is used to circulate and reads the source data that at least a acquisition mode at least one road is gathered in the one-period.
The traffic information fusion processing system that the embodiment of the invention provides, the source data of the various acquisition mode collections on many roads in the one-period is handled respectively, obtain a common-use size road condition data record of each source data correspondence, then all records in the common-use size road condition data are carried out fusion treatment, draw the comprehensive traffic information of each bar road in this one-period.Can merge the source data that multiple mode gathers such as fixing, move, avoided the poor accuracy that the collection of single source is caused in the prior art, the problem that coverage rate is low merges by multi-source data, can improve accuracy, complementarity, the increase coverage rate of traffic information.
Further, as shown in Figure 4, reading unit 301 further comprises:
Fixed form data read subelement 3011 is used to read the source data that fixed form is gathered.
Move mode data read subelement 3012 is used to read the source data that move mode is gathered.
Manual entry data read subelement 3013 is used to read the source data that manual entry is gathered.
Fixed form data processing subelement 3021 is used for the source data of fixed form collection is handled, and obtains corresponding common-use size road condition data.
Move mode data processing subelement 3022 is used for the source data of move mode collection is handled, and obtains corresponding common-use size road condition data.
Manual entry data processing subelement 3023 is used for the source data of manual entry collection is handled, and obtains corresponding common-use size road condition data.
The state support obtains subelement 3031, is used for the degree of belief to each speed interval according at least one record of every road of common-use size road condition data, and the probability assignments function by S type curve obtains the support to this each speed state of road.
Traffic information obtains subelement 3032, is used for the support of basis to each speed state of this road, obtains the comprehensive traffic information of this road.
In addition, as shown in Figure 5, above-mentioned traffic information fusion processing system can also comprise:
Collecting unit 304 is used to gather the road condition source data.
The traffic information fusion processing system that the embodiment of the invention provides, the source data of the various acquisition mode collections on many roads in the one-period is handled respectively, obtain a common-use size road condition data record of each source data correspondence, then all records in the common-use size road condition data are carried out fusion treatment, draw the comprehensive traffic information of each bar road in this one-period.Can merge the source data that multiple mode gathers such as fixing, move, avoided the poor accuracy that the collection of single source is caused in the prior art, the problem that coverage rate is low merges by multi-source data, can improve accuracy, complementarity, the increase coverage rate of traffic information.
The above; only be the specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; can expect easily changing or replacing, all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion by described protection domain with claim.
Claims (10)
1. a traffic information fusion processing method is characterized in that, comprising:
The source data that at least a acquisition mode at least one road is gathered in the one-period is read in circulation;
Source data to various acquisition mode collections is handled respectively, obtains a common-use size road condition data record of each source data correspondence;
All records in the described common-use size road condition data are carried out fusion treatment, draw the comprehensive traffic information of described at least one road in the described cycle.
2. traffic information fusion processing method according to claim 1, it is characterized in that a record in the described common-use size road condition data comprises: acquisition mode classification, degree of belief, road section length, highway section numbering, highway section grade, highway section number of track-lines to each speed interval.
3. traffic information fusion processing method according to claim 2 is characterized in that, described fusion treatment comprises:
According at least one degree of belief to each speed interval that writes down of every road in the described common-use size road condition data, the probability assignments function by S type curve obtains the support to this each speed state of road;
According to support, obtain the comprehensive traffic information of described road to each speed state of described road.
4. traffic information fusion processing method according to claim 3, it is characterized in that, described at least one the degree of belief that writes down to each speed interval according to every road in the described common-use size road condition data, probability assignments function by S type curve, obtain support, comprising this each speed state of road:
The setting speed state set is { Φ, { blocking up }, { slowly }, { unimpeded }, { blocking up, slow }, { slowly, unimpeded }, { blocking up, unimpeded }, { blocking up, slowly, unimpeded } } for { blocking up, slowly, unimpeded }, the power set of then described speed state set;
Set the corresponding relation of each speed state and speed interval;
By S type curve setting probability assignments function;
Utilize formula
Obtain the support to each speed state of every road, in the wherein said formula, M
1, M
2... M
nBe n probability assignments function, k is a conflict spectrum, and A is each element except that Φ in the power set of described speed state set.
5. traffic information fusion processing method according to claim 4 is characterized in that, described basis obtains the comprehensive traffic information of described road to the support of each speed state of described road, comprising:
With the speed state of support maximum in each speed state of described road, be defined as the speed state of described road, obtain the comprehensive traffic information of described road.
6. a traffic information fusion processing system is characterized in that, comprising:
Reading unit is used to circulate and reads the source data that at least a acquisition mode at least one road is gathered in the one-period;
Processing unit is used for the source data of various acquisition mode collections is handled respectively, obtains a common-use size road condition data record of each source data correspondence;
Integrated unit is used for all records of described common-use size road condition data are carried out fusion treatment, draws the comprehensive traffic information of described at least one road in the described cycle.
7. traffic information fusion processing according to claim 6 system is characterized in that described reading unit comprises:
Fixed form data read subelement is used to read the source data that fixed form is gathered;
Move mode data read subelement is used to read the source data that move mode is gathered;
Manual entry data read subelement is used to read the source data that manual entry is gathered.
8. traffic information fusion processing according to claim 6 system is characterized in that described processing unit comprises:
Fixed form data processing subelement is used for the source data of fixed form collection is handled, and obtains corresponding common-use size road condition data;
Move mode data processing subelement is used for the source data of move mode collection is handled, and obtains corresponding common-use size road condition data;
Manual entry data processing subelement is used for the source data of manual entry collection is handled, and obtains corresponding common-use size road condition data.
9. traffic information fusion processing according to claim 6 system is characterized in that described integrated unit comprises:
The state support obtains subelement, is used for the degree of belief to each speed interval according at least one record of every road of described common-use size road condition data, and the probability assignments function by S type curve obtains the support to this each speed state of road;
Traffic information obtains subelement, is used for the support of basis to each speed state of described road, obtains the comprehensive traffic information of described road.
10. traffic information fusion processing according to claim 6 system is characterized in that, described traffic information fusion processing system also comprises:
Collecting unit is used to gather the road condition source data;
Release unit is used to issue the road synthetic traffic information.
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| CN200910244107A CN101783069A (en) | 2009-12-29 | 2009-12-29 | Traffic information fusion processing method and system |
| PCT/CN2010/079885 WO2011079726A1 (en) | 2009-12-29 | 2010-12-16 | Traffic information fusion processing method and system |
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| CN108010316A (en) * | 2017-11-15 | 2018-05-08 | 上海电科智能系统股份有限公司 | A kind of road traffic multisource data fusion processing method based on road net model |
| CN113409593A (en) * | 2021-06-25 | 2021-09-17 | 阿波罗智联(北京)科技有限公司 | Traffic signal lamp control signal generation method and device, electronic equipment and medium |
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