CN107403551A - A kind of quick identification of access connection traffic flow detection data and data reconstruction method - Google Patents
A kind of quick identification of access connection traffic flow detection data and data reconstruction method Download PDFInfo
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- CN107403551A CN107403551A CN201710661387.9A CN201710661387A CN107403551A CN 107403551 A CN107403551 A CN 107403551A CN 201710661387 A CN201710661387 A CN 201710661387A CN 107403551 A CN107403551 A CN 107403551A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
Abstract
The invention discloses a kind of quick identification of access connection traffic flow detection data and data reconstruction method, comprise the following steps：S1：Obtain the data relationship and framework of traffic signal control system；S2：Identification is stored in the file in traffic signal control system, obtains the data message in each file；S3：The step S2 data messages identified are matched, reconstruct obtains the traffic flow data storehouse based on crossing.Compared with prior art, the present invention turns into the mass data reconstruct of existing traffic signal control system the data that can be used directly, and improves the value of existing equipment, reduces traffic study cost, strong foundation is provided for communications policy.
Description
Technical field
The present invention relates to technical field of intelligent traffic, and the quick knowledge of data is detected more particularly, to a kind of access connection traffic flow
Not and data reconstruction method.
Background technology
Crossing is the node of city road network, assume responsibility for the traffic translation function of different flow directions between road intersection.With friendship
Messenger control system is promoted the use of, and all newly-built vehicle detection system of signal controlled junctions, acquires a large amount of traffic flows
Data are detected, the data resource of preciousness is have accumulated for traffic administration.But access connection traffic flow detection data are all integrated in crossing
In adaptive control system, and the traffic signal control system of the overwhelming majority is open bad, just as a black box, and
The data cell of Traffic flow detecting data disperses to be stored between multiple data files again, it is impossible to directly reads, causes these friendships
Through-flow detection data are difficult to be used by traffic administration person.
At present, although domestic and foreign scholars have done substantial amounts of data processing method research to Traffic flow detecting data, it grinds
The focus and emphasis studied carefully are primarily directed to independent vehicle detection system, such as the China of Application No. 200910217820.5
Patent of invention, its data is easy to identify and handles, and for the Traffic flow detecting data processing in crossing traffic signal control system
Method does not have then substantially so that this partial data is difficult to be utilized, and this partial data is difficult to play value.
The content of the invention
To overcome existing technological deficiency, the invention provides a kind of access connection traffic flow detection data quick identification with
Data reconstruction method so that the Traffic flow detecting data of traffic signal control system become apparent from understanding, and directly apply to friendship
Logical aid decision.
To realize the purpose of the present invention, it is achieved using following technical scheme：
A kind of quick identification of access connection traffic flow detection data and data reconstruction method, comprise the following steps：
S1：Obtain the data relationship and framework of traffic signal control system；
S2：Identification is stored in the file in traffic signal control system, obtains the data message in each file；
S3：The step S2 data messages identified are matched, reconstruct obtains the traffic flow data based on crossing
Storehouse.
The data message includes：Traffic flow detecting data, crossing topological relation and the crossing title at each crossing etc..
The above method is specially：First, the data relationship and framework of the traffic signal control system got, it is determined that handing over
The information such as storage mode, storage location and the data content of each file that are stored in messenger control system；Then,
Chosen according to the data content of file comprising required target data (Traffic flow detecting data, topological relation and the crossing at each crossing
Title) data file, it is different further according to the storage mode (file format) of each file, build different digital independent lists
Member identifies the content of each file, obtains corresponding data table；Finally, the associated data in each tables of data identified is entered
Row matching, reconstruct obtain traffic flow data storehouse.
At present, it is the traffic data at acquisition crossing, uses manual research more, and manual research cost itself is larger, and
In the case of bad weather, the difficulty of manual research is bigger.The present invention passes through the difficulty to being stored in traffic signal control system
After reconstruct is identified with the data directly utilized, obtains that the information used can be directly read, substantially increase existing traffic
The value and utilization rate of whistle control system, substantially reduce traffic study cost (human cost and extra equipment into
Originally), it is the method for a kind of very economical and great practical value.
Further, step S2 is specially：According to the difference of the storage file form of traffic signal control system, structure
Different data-reading units., can also be by read method (the i.e. data reading of every kind of document format data in specific application
Take unit) class is encapsulated as, the class has the digital independent function of different aspects, can realize to different target data
Read identification.
Further, step S3 is specially：The data message that integration step S2 is identified, matching crossing, track, steering
And detection coil, obtain the traffic flow data storehouse based on crossing, the traffic flow data storehouse includes each crossing, each
Track, the Traffic flow detecting data of each steering.
Further, in addition to step S4：Differentiation and repairing to Traffic flow detecting data；Specific method is：To step
The traffic flow data storehouse obtained after S3 reconstruct is differentiated, if during the Traffic flow detecting shortage of data in I tracks, concludes I tracks
Data it is wrong；When judging that data are wrong, then wrong data are repaired, and data carry out data after data modification
Reconstruct obtains new traffic flow data storehouse.
Further, the method repaired to wrong data is specially：Determine I tracks with the presence or absence of adjacent and steering
Identical track；If in the presence of using adjacent and turn to identical track and repaired；If being not present, historical data is utilized
Repaired.
Further, repaired specially using adjacent and steering identical track：Weighed according to track set in advance
The weight traffic flow data wrong to I tracks with adjacent and steering identical track traffic flow data is repaired；The track
Weight determines according to magnitude of traffic flow ratio between the track of historical statistics.Wherein, the specific method of repairing is：By default
Track weight × adjacent turn to the numerical value obtained by identical lane traffic flow data to replace the wrong traffic flows of track I
Data.
Further, carrying out data modification using historical data is specially：Using history is interior for a period of time, same time
The average of the magnitude of traffic flow of point or same period is repaired.
Further, present invention additionally comprises step S5, it is specially：To the further statistical analysis in traffic flow data storehouse,
Obtain different crossings, different statistical intervals, not different periods, same date, the Traffic flow detecting data of different flow directions.Further
Statistical analysis is carried out to traffic flow data storehouse, abundant, strong data foundation is provided for traffic administration decision-making, is favorably improved
The science and reasonability of decision scheme.
Further, suitable for TRANSYT systems, SCATS systems and SCOOT systems.
, can will be existing the invention provides a kind of quick identification of access connection traffic flow detection data and data reconstruction method
The mass data of traffic signal control system, which unlocks, to be come, and the aid decision daily for traffic administration person.With prior art
Compare, the technical program has the advantages of following：
(1) value of existing equipment is improved：The detection device of existing traffic signal control system is only used for signal control
System, utilization rate of equipment and installations is low, value is not high, and the present invention further improves the value of detection device so that the data of equipment
It can be applied by many-side.
(2) traffic study cost is reduced：To obtain the traffic data at crossing, it is often necessary to manual research is carried out to scene,
And manual research cost is larger, the present invention can obtain the traffic flow data at crossing in real time based on whistle control system, be not required to artificial
Investigation, greatly reduce the cost of traffic study.
(3) strong foundation is provided for communications policy：The present invention can provide the multidimensional such as crossing different periods, different steerings
The data of degree, abundant, strong data foundation is provided for traffic administration decision-making, effectively increase the science of decision scheme with
Reasonability.
Brief description of the drawings
Fig. 1 is the flow chart of quick identification and data reconstruction method that access connection traffic flow detects data in embodiment；
Fig. 2 is the data relationship and framework of SCATS whistle control systems；
Fig. 3 is the physical topology relation of intersection；
Fig. 4 is the matching flow of the data such as data on flows and crossing attribute；
Fig. 5 is data modification flow；
Fig. 6 is the multi dimensional analysis of data reconstruction；
Fig. 7 is the case study on implementation crossing overview of the embodiment of the present invention.
Embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with the accompanying drawings to embodiment of the present invention
It is described in more detail.
Embodiment
Quick identification and the data reconstruction method of a kind of access connection traffic flow detection data are present embodiments provided, such as Fig. 1 institutes
Show, by taking SCATS traffic signal control systems as an example, comprise the following steps that：
1. grasp the data relationship and framework of whistle control system
SCATS is a set of complication system for covering traffic signalization, traffic data collection, traffic data storage, is needed
The data that treatment types are various, significance level is different are wanted, this requires SCATS systems to have a set of corresponding data storage
Mode is handled for different pieces of information.As shown in Fig. 2 the data storage of SCATS systems includes three layers of framework：Low layer is
The signal controlling machine at crossing, include the detection coil for being responsible for collection Traffic flow detecting data；Intermediate layer is region server,
The server is responsible for the multiple crossings of control management low layer, and region server stores data (the VS texts of low layer detection coil collection
Part) and the crossing ID of low layer and the file (LX) of crossing title corresponding relation；Upper strata is the server of whole control system,
The server stores a MDB database, and the database contains the basic data at all crossings, there is track, the line at crossing
Circle and steering etc..These data are divided into two kinds of storage modes of database and file according to feature, and file storage can
It is divided into binary file storage and text files memory two ways, it is specific as shown in table 1：
The SCATS basic data storage mode summary sheets of table 1
2. the Traffic flow detecting data of identification signal control system
The magnitude of traffic flow that SCATS systems are detected with all crossing control machines of specific time interval collection, daily with one
Individual binary file storage, and region server backup is uploaded to, file is named with " server name+detection date ", such as
“GZ001_20161026.VS”.Assuming that the specific time interval is 5 minutes, then every 5 minutes servers administration
All crossing traffic flows are all aggregated into a record storage into this document.When every magnitude of traffic flow record can be divided into one
Between section and multiple data on flows sections, time segment length is fixed as 9 bytes：The description of first and second byte does not include two byte
Record length；Third and fourth byte is that crossing ID describes position；5th to the 8th byte describes time, month, day, hour respectively；
7th (Bit, similarly hereinafter) of the 9th byte is the acquisition time flag bit of 15 minutes/5 minutes, is gathered within generally 5 minutes, if
It is set to 1；It is subsequently the data on flows section at each crossing.The data paragraph format at each crossing is as shown in table 2：
The SCATS basic data storage mode summary sheets of table 2
Because Traffic flow detecting data file is binary file, therefore, the coded format structure based on the binary file
Data-reading unit BinDataReader is built, the data-reading unit is to read the core cell of data on flows；Every kind of data
The read method of file format is encapsulated as a class VSDataReader, and such has the digital independent function of different aspects, with reality
The data reconstruction of existing different target.Binary data processing unit class and function performance explanation are as shown in table 3.
The binary data processing unit class of table 3 and function performance explanation
3. by the steering of Traffic flow detecting Data Matching to crossing
Step 2 only identifies the data on flows that each detection coil detects, and the detection is specifically the road represented
Mouth, track and steering are unclear, can not still effectively utilize this partial data, therefore, it is necessary to coil is matched
Each steering at crossing.
In traffic signal control system, each attribute at crossing is stored in the Pcintgrf tables of data of MDB databases
In, the table includes the specific information such as the detection coil numbering of road junction roadway and the steering in track, by reading, identifying
The table can be by the Data Matching of coil to specific track and steering.
The structure of each record of Pcintgrf tables is as shown in table 4, and wherein Type is represented in the record of row record
Hold, general each crossing has 7 records, and every record all records the different information at crossing, included belonging to crossing respectively
Region, coordinate, cantilever (track attribute), signal lamp group, phase, road name, detection coil (coil numbering) etc., such as the institute of table 5
Show.
The structure of Pcintgrf tables in the SCATS systems of table 4
| Field | Width | Remarks |
| Intno | 5 | Number at crossing |
| Type | 1 | The row record type, referring to table 5 |
| Item | 1 | Data first (are used to retrieve) |
| Data | 57 | Data detailed content |
The SCATS crossings attribute data record type of table 5
| Type | Information | Form | Main contents |
| 0 | Region | Text | Crossing region and crossing title |
| 1 | Coordinate | Sixel binary systems | Coordinate (Guangzhou coordinate system) and crossing figure central point information where crossing |
| 2 | Cantilever | Mixing | Cantilever position, track quantity and attribute, graticule information etc. |
| 3 | Signal lamp group | Mixing | Signal lamp group configuration information |
| 4 | Phase | Mixing | The phase that description signal lamp group occurs |
| 5 | Road | Mixing | Road name is described |
| 6 | Detection coil | Sixel binary systems | Detection coil position is described |
The topological relation at crossing is mainly obtained from MDB databases, as shown in figure 3, being closed according to the reality of each entity
System, based on BaseMethod (basic skills class, there is provided general coding/decoding method), establish Intersection, Arm,
Tetra- classes of Lanes, Lane, an Intersection (crossing) contain multiple Arm (cantilever), an Arm include it is left and right,
The Lanes (track group) of three types is canalized, each Lanes contains multiple Lane (track) again, and each Lane is mainly described
Steering and detection coil information.Each data-reading unit class and open function performance explanation are as shown in table 6：
The database data reading unit class of table 6 and function performance explanation
Further, since the above-mentioned magnitude of traffic flow (VS files) and the identification of crossing attribute (MDB databases) both of these documents intersect
Mouth is crossing ID, and the actual name at the crossing is not known, therefore, it is necessary to again from the LX texts of traffic signal control system
The data of correlation are read in part, to realize that the title at crossing is corresponding with crossing ID.By building text data reading unit
TextDataReader is read, and the unit is mainly the numbering that all crossings are read from the configuration file of crossing, therefore only includes one
Individual class SysLxReader, the file for extending entitled " LX " is read using GetAllSiteID functions, obtain all crossing ID row
Table.
After reading data according to three above data-reading unit, we can obtain more data volume, but its data
Source is different, and data acquiring mode and acquisition time are different, it is difficult to accurately obtain all data needed for us.Pass through logic
Algorithms Integration above functional relation associates all Data Integrations, realizes Data Matching function, reduces in data source and repeats
Character data.The matching restructuring procedure of data is specifically as shown in Figure 4：By three tables of data identified above (VS files,
LX files and MDB databases) in crossing ID all Data Integrations are associated, obtain the traffic flow based on crossing
Database.
4. a pair Traffic flow detecting data are differentiated and repaired
The collection of flow relies primarily on buried coil checker in traffic signal control system, and by condition of road surface with
And other factorses influence, coil damage phenomenon happens occasionally.When coil damages, its detection data is completely unavailable, above-mentioned
Step 2 and 3 in, we are only that identification have matched the relation of track, steering and coil, and the availability of data is not entered
Row is studied and judged.Therefore, this step mainly differentiates to detection availability of data, when finding that data are wrong, utilizes adjacent car
The data and historical data in road carry out Efficient software patching.
Wherein, it is using the foundation of adjacent lane data modification：According to the traffic flow ratio between the track of historical statistics
And correlative study data, the traffic flow data of section adjacent lane meets certain proportionate relationship, when the data in a certain track
During consecutive miss, corrected accordingly using the current data of adjacent lane, there is higher precision.
Specific repairing flow is as shown in Figure 5：First, the data after VS file identifications are differentiated, when discovery data are
When " DA " or most of the time on daytime are " 0 ", then conclude that the data are wrong；Then matched according to the steering of step 2 with track
Relation, repaired using the traffic flow data and default track weight of the adjacent lane in the track.The adjacent lane
Must turn to identical with this track, even otherwise adjacent lane, can not be repaired with the track data；When not having
Have adjacent track data be available for reference to repairing when, then utilize historical data carry out data modification.
Wherein, in the present embodiment, weight sets as shown in table 7.
The track weight of table 7 is set
5. pair Traffic flow detecting data carry out multi dimensional analysis
Data after Coil Detector basic data and repairing based on identification, enter line number with the topological relation at crossing
According to reconstruct, while provide the statistical analysis of the various dimensions such as crossing, statistical interval, period, date and flow direction, as shown in fig. 6,
Specifically include：Crossing (single intersection, Multiple Intersections)；Statistical interval (5 minutes, 15 minutes, 30 minutes, 60 minutes)；(some time period
Section, whole day)；Date (odd-numbered day, more days)；Flow direction (unicoil, single current to, single entrance driveway).
Concrete case
Certain known city decussation mouth uses SCATS auto-adaptive controling signal systems, and east, south and north are removed to the right in crossing
Change trains or buses outside without embedded detection coil, there is embedded detection coil in remaining each track, can detect the magnitude of traffic flow in real time, and crossing is opened up
It is as shown in Figure 7 to flutter situation.The Traffic flow detecting data at crossing are stored on region server G003 daily, and are carried out with the date
Name, such as G003_20160720, this document binary coding, can not be identified, it is necessary to by associating SCATS with normal mode
Could normally it be used after the MDB files and LX files of system.
After the method that operation the present embodiment is provided quickly is identified and reconstructed to the traffic flow data at crossing, Ke Yishi
Other Traffic flow detecting data, and the restructuring analysis of various dimensions can be carried out.
Wherein, it is as shown in table 8 by the way that the detection data of each track coil in crossing can be obtained after identifying first.
The hour Vehicle Detection flow of each detection coil in the crossing of table 8
Further, using the topological relation of intersection, detection data can be associated with each steering, such as the institute of table 9
Show, the data behind the direction of association detection data become apparent from understanding, can be directly used for traffic aid decision.
The hour Vehicle Detection flow of each steering in the crossing of table 9
For TRANSYT systems and SCOOT systems, refer to the above method and combine TRANSYT systems and SCOOT systems
The concrete condition of system, the method that rational data identification and data reconstruction are set according to actual conditions.
In general, the present invention can effectively improve the value of existing whistle control system equipment so that equipment
Data can be applied by many-side, while can reduce substantial amounts of traffic study cost, and effectively auxiliary can be provided for communications policy
Support is helped, effectively improves the science and reasonability of traffic administration scheme.
Claims (10)
1. quick identification and the data reconstruction method of a kind of access connection traffic flow detection data, it is characterised in that comprise the following steps：
S1：Obtain the data relationship and framework of traffic signal control system；
S2：Identification is stored in the file in traffic signal control system, obtains the data message in each file；
S3：The step S2 data messages identified are matched, reconstruct obtains traffic flow data storehouse.
2. the quick identification of access connection traffic flow detection data according to claim 1 and data reconstruction method, its feature exist
In step S2 is specially：According to the difference of the storage file form of traffic signal control system, different digital independent lists is built
Member.
3. the quick identification of access connection traffic flow detection data according to claim 1 and data reconstruction method, its feature exist
In step S3 is specially：The data message that integration step S2 is identified, matching crossing, track, steering and detection coil, is obtained
Traffic flow data storehouse based on crossing, the traffic flow data storehouse include each crossing, each track, the friendship of each steering
Through-flow detection data.
4. the quick identification of access connection traffic flow detection data according to claim 1 and data reconstruction method, its feature exist
In, in addition to step S4：Differentiation and repairing to Traffic flow detecting data；Specific method is：Obtained after being reconstructed to step S3
Traffic flow data storehouse is differentiated, if during the Traffic flow detecting shortage of data in I tracks, concluding that the data in I tracks are wrong；When sentencing
Fixed number according to it is wrong when, then wrong data are repaired, and data carry out data reconstruction and obtain new traffic after data modification
Flow database.
5. the quick identification of access connection traffic flow detection data according to claim 4 and data reconstruction method, its feature exist
In the method repaired to wrong data is specially：Determine I tracks with the presence or absence of adjacent and steering identical track；If deposit
Then repaired using adjacent and steering identical track；If being not present, repaired using historical data.
6. the quick identification of access connection traffic flow detection data according to claim 5 and data reconstruction method, its feature exist
In using adjacent and turn to identical track and repaired specially：According to track weight set in advance and adjacent and steering
The Traffic flow detecting data that the Traffic flow detecting data in identical track are wrong to I tracks are repaired.
7. the quick identification of access connection traffic flow detection data according to claim 6 and data reconstruction method, its feature exist
In the track weight determines according to magnitude of traffic flow ratio between the track of historical statistics.
8. the quick identification of access connection traffic flow detection data according to claim 5 and data reconstruction method, its feature exist
In carrying out data modification using historical data is specially：Using history is interior for a period of time, the friendship of same time point or same period
The average of through-current capacity is repaired.
9. quick identification and the data reconstruction method of the access connection traffic flow detection data according to any one of claim 1 ~ 8,
Characterized in that, also including step S5, it is specially：To the further statistical analysis in traffic flow data storehouse, obtain different crossings,
Different statistical intervals, not different periods, same date, the Traffic flow detecting data of different flow directions.
10. quick identification and the data reconstruction method of the access connection traffic flow detection data according to any one of claim 1 ~ 8,
Characterized in that, it is applied to TRANSYT systems, SCATS systems and SCOOT systems.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108205890A (en) * | 2017-12-29 | 2018-06-26 | 迈锐数据（北京）有限公司 | A kind of traffic data processing method and device |
| CN108961747A (en) * | 2018-07-03 | 2018-12-07 | 北京航空航天大学 | A kind of urban road traffic state information extracting method under incomplete bayonet data qualification |
| CN112309136A (en) * | 2019-07-29 | 2021-02-02 | 华为技术有限公司 | Method, device and equipment for determining traffic flow |
| CN116758744A (en) * | 2023-06-21 | 2023-09-15 | 山东宜鑫致远信息科技有限公司 | Smart city operation and maintenance management method, system and storage medium based on artificial intelligence |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101261766A (en) * | 2008-03-12 | 2008-09-10 | 四川通安实业有限公司 | Real time 3-D image monitoring platform for city traffic signals |
| CN101419750A (en) * | 2008-09-28 | 2009-04-29 | 华南理工大学 | Detecting and evaluating system for controlling traffic state at road cross, implementing method and use thereof |
| CN101727746A (en) * | 2009-09-18 | 2010-06-09 | 苏州大学 | Method for dynamically estimating travel time of motor vehicle on urban road under control of signal lamps |
| CN102346968A (en) * | 2011-09-29 | 2012-02-08 | 泉州市视通光电网络有限公司 | Traffic signal control system |
-
2017
- 2017-08-04 CN CN201710661387.9A patent/CN107403551A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101261766A (en) * | 2008-03-12 | 2008-09-10 | 四川通安实业有限公司 | Real time 3-D image monitoring platform for city traffic signals |
| CN101419750A (en) * | 2008-09-28 | 2009-04-29 | 华南理工大学 | Detecting and evaluating system for controlling traffic state at road cross, implementing method and use thereof |
| CN101727746A (en) * | 2009-09-18 | 2010-06-09 | 苏州大学 | Method for dynamically estimating travel time of motor vehicle on urban road under control of signal lamps |
| CN102346968A (en) * | 2011-09-29 | 2012-02-08 | 泉州市视通光电网络有限公司 | Traffic signal control system |
Non-Patent Citations (3)
| Title |
|---|
| 张多: "基于支持向量回归机和多变量相空间重构的短时交通流预测", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
| 王英会: "高速公路交通流异常数据识别及修复方法研究", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
| 顾九春，石建军，于泉: "基于XML的开放式交通控制系统数据共享的结构探讨", 《交通与计算机》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108205890A (en) * | 2017-12-29 | 2018-06-26 | 迈锐数据（北京）有限公司 | A kind of traffic data processing method and device |
| CN108205890B (en) * | 2017-12-29 | 2021-03-09 | 迈锐数据（北京）有限公司 | Traffic data processing method and device |
| CN108961747A (en) * | 2018-07-03 | 2018-12-07 | 北京航空航天大学 | A kind of urban road traffic state information extracting method under incomplete bayonet data qualification |
| CN112309136A (en) * | 2019-07-29 | 2021-02-02 | 华为技术有限公司 | Method, device and equipment for determining traffic flow |
| CN116758744A (en) * | 2023-06-21 | 2023-09-15 | 山东宜鑫致远信息科技有限公司 | Smart city operation and maintenance management method, system and storage medium based on artificial intelligence |
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Application publication date: 20171128 |