CN110427360A - Processing method, processing unit, processing system and the computer program product of track data - Google Patents
Processing method, processing unit, processing system and the computer program product of track data Download PDFInfo
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- CN110427360A CN110427360A CN201910575595.6A CN201910575595A CN110427360A CN 110427360 A CN110427360 A CN 110427360A CN 201910575595 A CN201910575595 A CN 201910575595A CN 110427360 A CN110427360 A CN 110427360A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/245—Query processing
- G06F16/2455—Query execution
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention discloses a kind of processing methods of track data, comprising: carries out multilevel splitting to road network according to road mileage and divides to obtain multiple grids, and is encoded according to code length corresponding with the region area of grid to each grid；Track data to be processed is obtained, each anchor point for being included by track data encodes；The ownership grid and adjacent mesh and all candidate road sections for therefrom extracting each anchor point of each anchor point are determined, to constitute the respective candidate road section set of each anchor point；The matching degree for calculating each candidate road section in each anchor point and respective candidate road section set, according to the determining section to match with each anchor point of matching degree；And each anchor point is subjected to position with the section to match and is associated with to correct the anchor point of positional misalignment in the track data, the processing of the track data is completed, to solve the problems, such as that the accuracy of track data existing in the prior art is low and track data lacks.
Description
Technical field
The present invention relates to data processing fields, and fill in particular it relates to a kind of processing method of track data, processing
It sets, processing system and computer program product.
Background technique
With can positioning intelligent equipment universal and wireless communication technique development, large-scale location data adopted
Collect and persistence saves, forms the track data of magnanimity.Be richly stored with knowledge in these data, it can reflect people's
Movement law, and traffic condition can be embodied.User trajectory not only includes the trip information of user, and the also trip comprising user is practised
Used, experience of life etc..
In the ideal case, the precision of GPS positioning data is 5 meters -10 meters.However, due to various external interferences, it is actual
Positioning accuracy will be lower than ideal value.The factor for influencing GPS location precision specifically includes that location hardware and environmental factor.Environment because
Element includes: that satellite-signal blocks, signal refraction, atmosphere or ionospheric interference.Tall and big building dense or weather condition not
In the case where good, because GPS signal passes through multiple refraction or reflection, signal errors caused, location data is caused to be drifted about.
GPS positioning data wander will lead to many problems.For example, positioning coordinate (longitude and latitude) is frequent when GPS terminal is static
Changing, and is changing under specific circumstances bigger.Sometimes, it or even can also show that GPS terminal has speed or mileage statistics
Deviation is larger.Such case further include: the vehicle with GPS terminal is parked in specific position one day of unit, and GPS positioning data
But show that it has travelled more than ten kilometers or even kilometer up to a hundred.The case where signal blocks, is: when vehicle by tunnel or enters ground library
When can because search can not be positioned less than satellite.
In conclusion existing in the prior art, data deviation acquired in positioning system is larger and positioning system can not obtain
Access according to when, there is the problem of accuracy is low and track data missing of track data.The data as acquired in positioning system
Accuracy directly affect result accuracy when being analyzed based on data, therefore track data is handled to promote number
According to accuracy be in the prior art required for solution.
Summary of the invention
In order to solve the problems in the prior art, the present invention provides the processing method, processing unit, place of a kind of track data
Reason system and computer program product, solve track data existing in the prior art accuracy is low and track data missing
Problem.
According on one side, the present invention provides a kind of processing method of track data characterized by comprising
It carries out multilevel splitting to road network according to road mileage to divide to obtain multiple grids, and according to the area surface with grid
The corresponding code length of product encodes each grid；
Track data to be processed is obtained, each anchor point for being included by the track data encodes；
The prefix matching that each anchor point and each grid are encoded, with the home network of each anchor point of determination
Lattice and adjacent mesh；
All candidate road sections in the ownership grid and adjacent mesh of each anchor point are extracted, it is each to constitute each anchor point
From candidate road section set；
The matching degree for calculating each candidate road section in each anchor point and respective candidate road section set, according to matching degree
The determining section to match with each anchor point；And
Each anchor point is carried out position with the section to match to be associated with to correct positional misalignment in the track data
Anchor point completes the processing of the track data.
It is described to include: to road network progress multilevel splitting division according to road mileage
The grid dividing that current level is carried out to road network, counts the quantity of road-net node in the grid of each current level；
If the quantity of the road-net node in the grid of arbitrary current level is more than specified amount threshold, to described
The grid of the current level of meaning carries out next stage grid dividing, up to the number of road-net node in the other grid of arbitrary afterbody
Until amount is no more than specified amount threshold, so that the multilevel splitting for completing the road network divides.
Basis code length corresponding with the region area of grid encodes each grid, comprising:
Pre-establish the corresponding relationship of geographic area area and code length；
Calculate the geographic area area of each grid；
The code length of each grid is obtained according to the corresponding relationship；
It is encoded using coordinate of the code length to the center of each grid.
Wherein the geographic area area of the grid of current level is greater than the geographic area area of the other grid of next stage.
It further include by each net before being encoded using coordinate of the code length to the center of each grid
The two-dimentional longitude and latitude of the coordinate of center of a lattice position are converted into character string respectively, and wherein character string is longer, then string table
The range shown is more accurate.
The each anchor point for being included by the track data encodes, comprising:
Determine the position coordinates for each anchor point that the track data is included, and to the position coordinates of each anchor point
Longitude and the character string that is constituted of latitude encoded.
The ownership grid for extracting each anchor point and all candidate road sections in adjacent mesh include:
Determine each anchor point ownership grid and adjacent mesh included in all road circuit nodes, be based on each road
Node determines all candidate road sections associated with road circuit node.
The matching degree for calculating each candidate road section in each anchor point and respective candidate road section set, according to
Determine that the section to match with each anchor point includes: with degree
Each anchor point in multiple anchor points is successively chosen as current anchor point:
The matching degree of each candidate road section distance in current anchor point and candidate road section set is calculated, is obtained in matching degree
The maximum value of probability value is P1, P1={ p11, p12..., p1m, wherein m is candidate road section quantity；
The registration for calculating path and each candidate road section that historical trajectory data is included obtains general in registration
The maximum value of rate value is P2, P2={ p21, p22..., p2m}；
The matching degree of operating range is calculated, the maximum value for obtaining probability value in matching degree is P3, P3={ p31,
p32..., p3m}；
Three probability values of current anchor point are subjected to COMPREHENSIVE CALCULATING, obtain of current anchor point and each candidate road section
With degree P, P=P1P2P3={p11p21p31, p12p22p32..., p1mp2mp3m, the maximum candidate road section of matching degree P be with it is described
The section that current anchor point matches.
The matching degree for calculating each candidate road section in each anchor point and respective candidate road section set, according to
Determine that the section to match with each anchor point includes: with degree
Each anchor point in multiple anchor points is successively chosen as current anchor point:
Carry out at least one of following three kinds of calculating, and the calculated result based at least one of following three kinds calculating
To determine the matching degree of each candidate road section in current anchor point and candidate road section set:
The matching degree of each candidate road section distance in current anchor point and candidate road section set is calculated, is obtained in matching degree
The maximum value of probability value is P1, P1={ p11, p12..., p1m, wherein m is candidate road section quantity；
The registration for calculating path and each candidate road section that historical trajectory data is included obtains general in registration
The maximum value of rate value is P2, P2={ p21, p22..., p2m}；
The matching degree of operating range is calculated, the maximum value for obtaining probability value in matching degree is P3, P3={ p31,
p32..., p3m}。
Anchor point is closer at a distance from candidate road section, then the probability that anchor point and the candidate road section match is bigger；
The registration in path and candidate road section that historical trajectory data is included is higher, then anchor point and the candidate road section
The probability to match is bigger；And
Road network distance associated with anchor point and the matching degree of operating range are higher, then anchor point and the candidate road section
The probability to match is bigger.
According on the other hand, the present invention provides a kind of computer program product comprising the executable program of processor,
It is characterized in that, the program performs the steps of when being executed by processor
It carries out multilevel splitting to road network according to road mileage to divide to obtain multiple grids, and according to the area surface with grid
The corresponding code length of product encodes each grid；
Track data to be processed is obtained, each anchor point for being included by the track data encodes；
The prefix matching that each anchor point and each grid are encoded, with returning for each anchor point of determination
Belong to grid and adjacent mesh；
All candidate road sections in the ownership grid and adjacent mesh of each anchor point are extracted, it is each to constitute each anchor point
From candidate road section set；
The matching degree for calculating each candidate road section in each anchor point and respective candidate road section set, according to matching degree
The determining section to match with each anchor point；And
It corrects position in the track data by the way that each anchor point to be associated with the section progress position to match and loses
Quasi- anchor point, to complete the processing of the track data.
According on the other hand, the present invention provides a kind of processing system of track data, which is characterized in that the processing system
System includes:
Processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to: carry out any one method as mentioned above.
According on the other hand, the present invention provides a kind of processing unit of track data characterized by comprising
Trellis encoding unit carries out multilevel splitting to road network according to road mileage and divides to obtain multiple grids, and according to
Code length corresponding with the region area of grid encodes each grid；
Anchor point coding unit obtains track data to be processed, each anchor point for being included by the track data
It is encoded；
Dot grid determination unit is positioned, the prefix matching that each anchor point and each grid are encoded, with true
The ownership grid and adjacent mesh of fixed each anchor point；
Candidate road section set Component units extract all candidate roads in the ownership grid and adjacent mesh of each anchor point
Section, to constitute the respective candidate road section set of each anchor point；
Section determination unit is matched, each candidate road section in each anchor point and respective candidate road section set is calculated
Matching degree, according to the determining section to match with each anchor point of matching degree；And
Processing unit corrects the track data by the way that each anchor point to be associated with the section progress position to match
The anchor point of middle positional misalignment, to complete the processing of the track data.
The processing method of track data provided by the present invention carries out multilevel splitting to road net data according to road mileage and draws
Point, and extract the candidate road section comprising road circuit node.Calculate the matching degree of each anchor point Yu respective each candidate road section, root
According to the determining section to match with each anchor point of matching degree, by the way that each anchor point is carried out position pass with the section to match
Join to correct the anchor point of positional misalignment in the track data.By the above-mentioned means, method of the invention is by completing track
The processing of data solves the problems, such as that the accuracy of track data of the existing technology is low and track data lacks.
Detailed description of the invention
Fig. 1 is the flow chart of the processing method of track data provided in an embodiment of the present invention；
Fig. 2 be the present embodiments relate to city road network schematic diagram；
Fig. 3 be the present embodiments relate to building road network multiple index mode schematic diagram；
Fig. 4 be the present embodiments relate to geographic area area and Geohash code length corresponding relationship signal
Figure；
Fig. 5 be the present embodiments relate to road network multiple index binary tree structure schematic diagram；
Fig. 6 be the present embodiments relate to anchor point and the matched flow diagram of candidate road section；And
Fig. 7 be another embodiment of the present invention provides track data processing method flow chart；
Fig. 8 is the structural schematic diagram of the processing unit of track data provided in an embodiment of the present invention.
Specific embodiment
In the following description, numerous specific details are set forth in order to facilitate a full understanding of the present invention.But the present invention can be with
Much it is different from other way described herein to implement, those skilled in the art can be without prejudice to intension of the present invention the case where
Under do similar popularization, therefore the present invention is not limited to the specific embodiments disclosed below.
Referring to Figure 1, Fig. 1 is the flow chart of the preprocess method of track data provided in an embodiment of the present invention.It ties below
Fig. 1 is closed method provided in an embodiment of the present invention is described in detail.
Step S101 carries out multilevel splitting to road network according to road mileage and divides to obtain multiple grids, and according to net
The corresponding code length of the region area of lattice encodes each grid.
Road network is specific region, such as city, rural area etc., the reticular structure that interior road is constituted.Road network is city model
In enclosing by different function, grade, position road, the network architecture formed with certain density and form appropriate.Road
Reticular density is used to indicate the density of road in whole region, partial region or the selection area of road network.It is opened up from the city road network of Fig. 2
It flutters in hum pattern as can be seen that the road network of urban central zone is more intensive, then road mileage is larger, and the road network of urban fringe
More sparse, then road mileage is smaller.In general, road and intersection included in the biggish region of road mileage compares
It is more.
For the technical problems to be solved by the invention, when deviations occur big for positioning system location data obtained
Or can not positioning scenarios when, obtain track data just will appear accuracy it is low and missing the problem of.To the place of track data
Reason, exactly when there are these problems, the data that timely correction has the track data of error or supplement to lack are so that positioning system
The track data of output is corrected.So, when solving the problems, such as, it is necessary first to find out track data pair from current road network
The candidate road section answered, the step of then passing through below is further to be calculated, to complete the processing of track data.Candidate road section is
Finger and section similar in track data, these sections are most likely to be the true operation rail that the track data to go wrong is belonged to
Mark.But when being matched track data with candidate road section, if matched in entire city road network, wait
Routing section will be very more, will lead to that calculation amount is very big, influence the computational efficiency of system.
So in order to improve the computational efficiency of system, it is only necessary to will be candidate in track data and a certain range of road network
Section is matched.If entire road network is carried out average division, in the big region of road mileage, track number using grid
According to the matched candidate road section Region Matching lower than road mileage certainly candidate road section it is more, equally also will affect system
Computational efficiency.So the present embodiment proposes the Meshing Method based on road mileage, multilevel splitting division is carried out to road network.
This method includes: that the grid dividing of current level is carried out to road network, counts road-net node in the grid of each current level
Quantity；If the quantity of the road-net node in the grid of arbitrary current level is more than specified amount threshold, to described any
Current level grid carry out next stage grid dividing, until the other grid of arbitrary afterbody in road-net node quantity
Until no more than specified threshold value, so that the multilevel splitting for completing the road network divides.For example, carrying out multi-level network to road net data
Lattice division includes: to carry out the 1st grade of grid dividing to road net data, counts the quantity of road-net node in the 1st grade of each grid；If the 1st
The quantity of road-net node is more than specified amount threshold in any grid of grade, then carries out the 2nd grade of grid dividing to the grid,
And and so on, until the quantity of road-net node in last 1 grade of any grid is less than specified threshold value, to complete
The division of the road net data multilevel splitting.
Since the present embodiment carries out multilevel splitting division to road network, acquired multiple grids may and be not belonging to together
One grid rank.As shown in figure 3, the rank of grid WY level-one higher than the rank of grid WX1, and the rank of grid WY compares net
The high two-stage of the rank of lattice WX12.It will be appreciated that the grid of different stage corresponds to the index of different stage, and not at the same level
Other index corresponds to different code lengths.For example, grid WY corresponding to level-one index, grid WX1 correspond to secondary index,
Grid WX12 corresponds to three level list and grid WX111 is indexed corresponding to level Four.
Therefore, the present embodiment encodes each grid according to code length corresponding with the region area of grid.
Firstly, determining the code length of grid according to grid rank.Grid rank where grid is different, then the code length of grid
Also different.It is then possible to be encoded according to the code length of grid to each grid using Geohash.In this way, each grid
There is respective independent coding.In addition, the present embodiment can determine the index level of each grid by code length, thus
Construct the multiple index of road network.In general, the region area of grid is bigger, then index level corresponding to grid is higher, and compiles
Code length is shorter.In Geohash encoding scheme, the code length of each rank both corresponds to preset geographic area area.
In actual coding, the present embodiment selects code length according to the actual area area of each grid divided.According to not
Each coding is indexed the building of rank by same code length, to realize multilevel index structure.For example, code length compared with
Short coding is located at the upper level of multilevel index structure, and the longer coding of code length is located at the next of multilevel index structure
Grade.
As shown in figure 3, grid WY is indexed corresponding to level-one, code length is that the region area of 2 and grid WY is road network
The 1/2 of area (using the region in Fig. 2 as entire road network).Grid WX1 corresponds to secondary index, and code length is 3 and net
The region area of lattice WX1 is the 1/4 of road network area.Grid WX12 corresponds to three level list, and code length is 4 and grid WX12
Region area be the 1/8 of road network area.Grid WX111 is indexed corresponding to level Four, and code length is 5 and grid WX111's
Region area is the 1/16 of road network area.
It will be appreciated that the present embodiment is illustrated by taking Geohash encoding scheme as an example, but it can actually use and appoint
What close or similar encoding scheme.Therefore, the encoding scheme of the present embodiment is not limited to Geohash encoding scheme.
Specifically, each grid is encoded according to code length corresponding with the region area of grid, comprising: pre-
First establish the corresponding relationship of geographic area area and code length；Calculate the geographic area area of each grid；According to described right
Answer the code length of each grid of Relation acquisition；It is compiled using coordinate of the code length to the center of the grid
Code.In general, the geocoding scheme of such as Geohash can be compiled according to the area of the division grid generated to road network to distribute
Code length or encoding levels.For this purpose, the geographic area area that geocoding scheme usually pre-establishes is corresponding with code length
Relationship is as shown in Figure 4.First is classified as code length and the 4th and is classified as region area in Fig. 4.
The geographic area area of each grid is calculated by following formula:
S=dist (max (lng), min (lng)) * dist (max (lat), min (lat))
Wherein, max (lng) is the maximum value of grid longitude, and min (lng) is the minimum value of grid longitude, and max (lat) is
The maximum value of grid latitude, min (lat) are the minimum value of grid latitude.In the present embodiment, the geographic area of grid is square
Shape, therefore above-mentioned formula determines the geographic area area of grid by calculating the area of rectangle.The ground of the grid of current level
Manage the geographic area area that region area is greater than the other grid of next stage.It will be appreciated that the present embodiment is with current level
The geographic area area of grid is that 2 times of geographic area area of the other grid of next stage are illustrated, but fields technology
Personnel are it will be appreciated that the geographic area area of the geographic area area and other grid of next stage of the grid of current level
Ratio can be any reasonable ratio.
By the geographic area area S for the grid that above formula is calculated, with the preset area surface in Fig. 4
ProductIt can not exactly match.Therefore it needs to be determined that with preset region area region area the most approximate, with determination
Code length.For example, the geographic area area S for the grid being calculated by above formula is 9700 sq-kms, then compile
Code length should be determined as 3.It is by the table with Fig. 4 so obtaining the code length of each grid according to corresponding relationship
Each item be compared, extract it is immediate with SIt finds againCode length of the corresponding code length as grid.
Calculation formula beWherein region areaUnit is sq-km, elng
For latitude error, elatFor longitude error.The corresponding code length of region area is set in advance in Geohash encoding scheme in Fig. 4
Fixed corresponding relationship.It in practical applications, can be according to the increase of the index level of road network, to the ranging variety of region area
Increased.
Next the coordinate of the grid element center position, i.e. its longitude and latitude are used according to the code length of grid
Geohash is encoded.Coding mode is as shown in figure 3, using the code length to the coordinate of the center of the grid
It is encoded, for the two-dimentional longitude and latitude of the coordinate of the center of the grid to be converted into character string.The wherein character
Go here and there it is longer, then it represents that range it is more accurate.In the present embodiment, it when being encoded using Geohash, uses
The coding mode of Geohashbase32.For example, in road network region grid encoding example are as follows: grid WY, grid WX1, grid
WX12 and grid WX111 etc..
The multilevel index structure of road network, additionally it is possible to be indicated using binary tree structure, as shown in Figure 5.The wherein bottom
Structure can be understood as the entire road network in city, and then entire road network is divided into two, construct road network level-one index (for example,
Grid WY), then level-one index is divided into two, the secondary index (for example, grid WX1) of road network is constructed, and so on, construct road
The n grade of net indexes.It can be seen that multiple index can be binary tree structure.Wherein, it indexes before being divided for every grade, according to
The size relation of the number of nodes of road network to be divided and specified quantity threshold values, judges whether to next stage index structure
It divides.
Step S102 obtains track data to be processed, and each anchor point for being included by the track data is compiled
Code.The each anchor point for wherein being included by track data carries out coding and comprises determining that the track data each of is included
The position coordinates of anchor point, and the character string that longitude to the position coordinates of each anchor point and latitude are constituted encodes.
It will be appreciated that step S101 and step S102 do not need according in the present embodiment time sequencing or order of order come into
Row, but can execute concurrently or in other sequences.For example, step S102 can be executed before step S101, or step
Rapid S102 can be performed simultaneously with step S101.
Currently, the positioning system of mainstream has Beidou satellite navigation system (the English name BeiDou Navigation of China
Satellite System, abridge BDS), the global positioning system (GPS) in the U.S. etc..Track data is exactly by these positioning systems
What system or similar positioning system were exported.By taking on-vehicle navigation apparatus as an example, output of the on-vehicle navigation apparatus as positioning system
Device, during being positioned, positioning system timing or positioned with position of the predetermined time interval to current vehicle.
In general, there are the time differences between positioning twice.For example, obtaining the position of a current vehicle every 3 seconds, 5 seconds, 8 seconds or 10 seconds etc.
It sets, i.e. the time difference is 3 seconds, 5 seconds, 8 seconds or 10 seconds etc..So although the location information of output seem be it is continuous, it is in fact defeated
Location information out is the track data being formed by connecting by multiple and different anchor points.
After obtaining the track data that positioning system is exported, each anchor point for being included by track data is compiled
Code.In the present embodiment, the coding mode encoded to anchor point is identical as the coding mode encoded to grid, so that
The coding of the coding and grid that obtain anchor point is able to carry out prefix matching.For example, the coding mode that anchor point is encoded with
The coding mode encoded to grid is Geohash base32 coding.Specifically, it is determined that the longitude of each anchor point and
Latitude, and encoded according to the character string that longitude and latitude of the Geohash encoding scheme to each anchor point are constituted, with
Generate the Geohash coding of each anchor point.
Step S103, the prefix matching that each anchor point and each grid are encoded, with each positioning of determination
The ownership grid and adjacent mesh of point.For example, anchor point is encoded to WX168, then by the coding of anchor point and all grids
Coding carries out prefix matching (that is, being matched on the left of the coding) it was determined that anchor point matches with grid WX1.
Then grid WX1 is the ownership grid of anchor point.In addition, grid WX12 and grid WX111 is the adjacent mesh of anchor point.This be because
For although the front three of grid WX12 and grid WX111 are matched with the coding WX168 of anchor point, and subsequent character is not
Match, therefore is the adjacent mesh of anchor point.
From figure 3, it can be seen that the similarity degree that the Geohash of grid similar in same road network index level is encoded is higher,
And the distance of the Geohash coding higher grid of similarity degree is closer.Geohash coding is the character for meeting preset rules
String, so the ownership grid and adjacent mesh of each anchor point can be obtained by the matched method of string prefix.In addition
Example in, the specific method of prefix matching is, for example, the Geohash of anchor point is encoded to wx4g0ec1, its prefix
Wx4g0ec represents the grid that anchor point is currently located, and includes that the grid of prefix wx4g0e is construed as anchor point
Grid near wx4g0ec1, so by the method for prefix matching, the adjacent mesh of available anchor point.
Step S104 extracts all candidate road sections in the ownership grid and adjacent mesh of each anchor point, every to constitute
A respective candidate road section set of anchor point.
As described above, determining the ownership grid and adjacent mesh of each anchor point by the method for prefix matching.Because
Include the candidate road section that is constituted of at least one road circuit node in each grid, thus extract each anchor point ownership grid and
In adjacent mesh included all road circuit nodes, then institute associated with road circuit node is determined based on each road circuit node
There is candidate road section.Road circuit node typically belongs to some section.The set in these sections associated with each anchor point is just constituted
Each anchor point respective candidate road section set.
Step S105 calculates the matching degree of each candidate road section in each anchor point and respective candidate road section set,
According to the determining candidate road section to match with each anchor point of matching degree.
Accuracy in order to solve the problems, such as track data of the existing technology is low and track data lacks, it is thus necessary to determine that
The physical location of each anchor point in the track data obtained.It can determine use by the physical location of each anchor point
The actual path at family carries the track that the user of positioning device is actually passed through.For this reason, it may be necessary to by each anchor point with
Its may relevant all candidate road sections matched, and based on determining each anchor point through result determined by overmatching
Physical location.
Firstly, choosing current anchor point from multiple anchor points, obtained in its candidate road section set for current anchor point
Each candidate road section.In order to which track data to be corrected, the present embodiment carries out each anchor point in track data
The matching primitives of candidate road section.In order to illustrate, the present embodiment using some anchor point in multiple anchor points as current anchor point into
Row explanation.It will be appreciated that the present embodiment can carry out positive sequence according to the time sequencing of anchor point or the selection of backward is each fixed
Site.That is, after carrying out matching primitives to current anchor point, then successively to the carry out matching primitives of remaining each anchor point.
The process of anchor point and the matching primitives of candidate road section is as shown in Figure 6.For example, calculating current anchor point and candidate road
The matching degree of each candidate road section distance in Duan Jihe includes:
Step S601 calculates current anchor point at a distance from each candidate road section in candidate road section set.Specifically, lead to
Following formula is crossed to calculate,
Wherein, (x0, y0) it is current anchor point coordinate, A=x1-x2, B=y1-y2, C=x1y2-x2y1, wherein (x1, y1),
(x2, y2) be candidate road section on any two coordinate points.
Current anchor point is carried out ascending sort by step S602 at a distance from each candidate road section.Under normal conditions, with work as
Prelocalization point apart from nearest candidate road section be the candidate road section that current anchor point actually matches probability it is larger.In order to
Computational efficiency is enough promoted, the present embodiment rises at a distance from each candidate road section after step S601, by current anchor point
Sequence sequence, so that more forward apart from closer candidate road section ranking.
Step S603 calculates the matching degree of current anchor point and each candidate road section.In calculating current anchor point and each
When the matching degree of candidate road section, the present embodiment determines the three of current anchor point and each candidate road section by three kinds of calculations
A initial matching probability.Then, current anchor point and three initial matching probability of each candidate road section are subjected to composite computing
To determine the matching degree of current anchor point Yu each candidate road section.
Firstly, can determine current anchor point after current anchor point is calculated at a distance from candidate road section and wait
The distance of routing section is closer, then matched probability is bigger.Wherein, the probability value of the first probability is P1={ p11,p12,…,
p1m, wherein m is candidate road section quantity.First probability be used to indicate current anchor point and each candidate road section based on away from
From matching probability.
Then, the path and each candidate road section that historical trajectory data is included successively are calculated according to previously obtained sequence
Registration.Historical trajectory data refer to current anchor point before all anchor points composition track data.It is current fixed to obtain
The path of the historical trajectory data in site and the registration of candidate road section.Specifically, historical track number is judged according to ranking results
According to path in each anchor point (xn, yn) whether in candidate road section.In all anchor points i.e. before current anchor point
Whether each anchor point is in candidate road section.
Specifically, it is first determined(θ is threshold value), wherein (x1, y1), (x2, y2) it is specific
Any two coordinate points in candidate road section.Whether above-mentioned formula is used to judge the path in historical trajectory data in candidate road section
On.When being less than threshold θ, it can be determined that in specific candidate road section, then next proceed to carry out curve fitting sentences in path
It is disconnected；Conversely, judging judgement of the path not in specific candidate road section, without curve matching.
The path and candidate road section for include to historical trajectory data carry out curve fitting, and obtain historical trajectory data and include
The curve y=f (x) in path and candidate road section.By to curve derivation, the center of curvature of calculated curve, calculation formula is as follows:
Wherein α is the center of curvature in the path that historical trajectory data includes, and β is the center of curvature in candidate road section path.It goes through
The center of curvature in the path of history track data is dist ((α with candidate road section center of curvature distance1,β1),(α2,β2)).Wherein
(α1,β1),(α2,β2) be respectively two curves center of curvature coordinate, described apart from smaller, then historical trajectory data includes
The registration of path and candidate road section is higher, then current anchor point and the matching probability of the candidate road section are bigger, and second is initial
The probability value of probability is P2={ p21,p22,…,p2m}.Second probability is used to indicate current anchor point and each candidate road section
The matching probability based on registration.
Finally, due to which operating range matching degree is also the important indicator of the similarity of determining anchor point and candidate road section, it is
Matching probability of this present embodiment based on operating range matching primitives current anchor point and candidate road section.According to operating range when
The distance between two adjacent moments that preceding speed calculates.Road network distance is the positioning of two adjacent moments of positioning system output
The distance between point.Calculate operating range and road network apart from when, the time value of two adjacent moments is identical.Positioning system
For system in output trajectory data, the adjacent anchor point of any two is having time interval.It, can basis by taking vehicle mounted guidance as an example
The position of two neighboring anchor point and time interval determine the travel speed of equipment or vehicle, then according to equipment or the row of vehicle
It sails speed and running time calculates the operating range of equipment or vehicle.
In such a way that operating range matching degree determines the matching probability of current anchor point and candidate road section are as follows: calculate and work as
The difference of prelocalization point associated road network distance and operating range,Wherein ct-1For candidate
The anchor point of previous moment, c on sectiontFor the current anchor point at current time in candidate road section, vt-1Before current anchor point
One moment speed, vtFor the current time speed of current anchor point.Difference is smaller, then the matching degree of operating range is higher.Traveling
The matching degree of distance is higher, then the probability for matching the candidate road section is bigger.The probability value of third probability is P3={ p31,
p32,…,p3m}.Third probability be used to indicate current anchor point and each candidate road section based on operating range matching degree
Matching probability.
The probability value of above three probability is comprehensively considered, that is, can determine the candidate road section to match with current anchor point.
That is, the matching degree of current anchor point and each candidate road section is P=P1P2P3={ p11p21p31,p12p22p32,…,p1mp2mp3m,
Wherein P1For the first probability, P2For the second probability and P3For third probability.
The maximum candidate road section of the numerical value of matching degree P is the candidate road section to match with the current anchor point.It should
Solution, when calculating the matching degree P of current anchor point and each candidate road section, the probability value of above three probability is
When calculating matching degree P, wherein three in all probability values, and when calculating, at least take any one in all matching degrees.
That is, the present embodiment can pass through P1、P2And P3At least one of determine the matching degree of current anchor point Yu each candidate road section
P.In addition, the present embodiment is illustrated by taking three probabilities as an example, one of ordinary skill in the art are it will be appreciated that can make
With the probability of any fair amount.In general, anchor point is closer at a distance from candidate road section, then anchor point and the candidate road
The probability that section matches is bigger.The registration in path and candidate road section that historical trajectory data is included is higher, then anchor point with
The probability that the candidate road section matches is bigger.Road network distance associated with anchor point and the matching degree of operating range are higher,
The probability that then anchor point and the candidate road section match is bigger.
Next according to the above-mentioned method for determining candidate road section for current anchor point, the phase with each anchor point is successively obtained
Matched candidate road section.
Each anchor point is carried out position with the section to match and is associated with to correct position in the track data by step S106
The anchor point for setting misalignment completes the processing of the track data.Each anchor point is carried out position with the section to match to be associated with,
This is because the associated candidate road section in actually each only one position of anchor point, that is, carry the equipment or vehicle of positioning system
A section is pertaining only in synchronization.In this embodiment, to each anchor point in track data to be processed according to when
Between sequentially handled.That is, time earliest anchor point starts to process from track data to be processed, until rail to be processed
The anchor point of time the latest is until processing terminate in mark data.In general, some anchor point in the track data to be processed is not
In section (that is, not can advance, walk or the position of form in) when, determine this anchor point be positional misalignment positioning
Point.In addition, further include, when in track data to be processed previous anchor point and the latter anchor point in the A of section, and
When current anchor point is in the B of section, it can also determine that current anchor point is the anchor point of positional misalignment.That is, the present embodiment is by position
It sets coordinate and is clearly present the anchor point of problem and be determined as the anchor point of positional misalignment.
When handling current anchor point, if it is determined that when current anchor point is the anchor point of positional misalignment, it is determined that
The section that current anchor point is belonged to.According to the previous anchor point before current anchor point the section belonged to position
Set and user (or mobile terminal, carry mobile terminal vehicle) speed, determine current anchor point in the section belonged to
On correct position.Using correct position of the current anchor point on the section belonged to as the actual bit of current anchor point
It sets, to correct the current anchor point of positional misalignment in track data.
In general, technical solution provided by the present embodiment is to prepare after having acquired track data to track data
When being analyzed and being handled, started when being pre-processed to track data.However, in some cases, when track number
One or more anchor points when obvious misalignment occurs in locating point position in, such as in track data appear in clear mistake
Position when, in response to data processing request from the user, anchor point and candidate can be calculated by step S101-S106
The matching degree in section, the acquisition matched candidate road section of anchor point are a, are associated with then establishing anchor point with the position of section a.So
Afterwards, it is associated with by position, anchor point is re-moved into section a, thus to correct positional misalignment in the track data
Anchor point, to complete the processing of the track data.For another example having one section of track data in section a where track data
Lacked due to being blocked etc. information, can by step S101-S106, calculate path that historical trajectory data includes with
The registration of candidate road section obtains in track data and has the matched candidate road section of anchor point for a, then establishes existing anchor point
It is associated with the position of section a.Then, it is associated with by position, existing anchor point is determined all on a of section, then determining that missing
That section of track data also on a of section, to the anchor point lacked in the track data is filled, described in completion
The processing of track data.
The processing method of track data provided in this embodiment mainly includes two links, as shown in fig. 7, when there is rail
When the problem of accuracy of mark data is low and track data lacks, by carrying out selection S701 to candidate road section on road network, so
S702 is calculated to the matching degree of anchor point and candidate road section afterwards, the highest section of matching probability is chosen in candidate road section, is used
The data in the highest section of matching probability are modified the track data to go wrong, and the accuracy for compensating for track data is low
The problem of with track data missing, keep the track data of positioning system more accurate.
Corresponding with the processing method of a kind of track data provided above, the present embodiment also provides a kind of track data
Processing unit 800.As shown in Figure 8, comprising:
Trellis encoding unit 810 carries out multilevel splitting to road network according to road mileage and divides to obtain multiple grids, and root
Each grid is encoded according to index level, to construct the multiple index of road network；
Anchor point coding unit 820 obtains track data to be processed, each positioning for being included by the track data
Point is encoded；
Dot grid determination unit 830 is positioned, the prefix matching that each anchor point and each grid are encoded, with
Determine the ownership grid and adjacent mesh of each anchor point；
Candidate road section set Component units 840 extract all times in the ownership grid and adjacent mesh of each anchor point
Routing section, to constitute the respective candidate road section set of each anchor point；
Section determination unit 850 is matched, the candidate road of each of each anchor point and respective candidate road section set is calculated
The matching degree of section, according to the determining section to match with each anchor point of matching degree；And
Processing unit 860 corrects the track by the way that each anchor point to be associated with the section progress position to match
The anchor point of positional misalignment in data, to complete the processing of the track data.
In addition, the present embodiment also provides a kind of computer program product comprising the executable program of processor, feature
It is, which performs the steps of when being executed by processor
It carries out multilevel splitting to road network according to road mileage to divide to obtain multiple grids, and according to the area surface with grid
The corresponding code length of product encodes each grid；
Track data to be processed is obtained, each anchor point for being included by the track data encodes；
The prefix matching that each anchor point and each grid are encoded, with the home network of each anchor point of determination
Lattice and adjacent mesh；
All candidate road sections in the ownership grid and adjacent mesh of each anchor point are extracted, it is each to constitute each anchor point
From candidate road section set；
The matching degree for calculating each candidate road section in each anchor point and respective candidate road section set, according to matching degree
The determining section to match with each anchor point；And
It corrects position in the track data by the way that each anchor point to be associated with the section progress position to match and loses
Quasi- anchor point, to complete the processing of the track data.
Further, the present embodiment also provides a kind of processing system of track data, which is characterized in that the processing system
Include:
Processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to: carry out the combination of any one method or step as mentioned above.
Claims (10)
1. a kind of processing method of track data characterized by comprising
It carries out multilevel splitting to road network according to road mileage to divide to obtain multiple grids, and according to the region area phase with grid
Corresponding code length encodes each grid；
Track data to be processed is obtained, each anchor point for being included by the track data encodes；
The prefix matching that each anchor point and each grid are encoded, with the ownership grid of each anchor point of determination and
Adjacent mesh；
All candidate road sections in the ownership grid and adjacent mesh of each anchor point are extracted, it is respective to constitute each anchor point
Candidate road section set；
The matching degree for calculating each candidate road section in each anchor point and respective candidate road section set is determined according to matching degree
The section to match with each anchor point；And
Each anchor point is carried out position with the section to match to be associated with to correct the positioning of positional misalignment in the track data
Point completes the processing of the track data.
2. processing method according to claim 1, which is characterized in that described to carry out multi-level network to road network according to road mileage
Lattice divide
The grid dividing that current level is carried out to road network, counts the quantity of road-net node in the grid of each current level；
If the quantity of the road-net node in the grid of arbitrary current level is more than specified amount threshold, to described arbitrary
The grid of current level carries out next stage grid dividing, until the quantity of road-net node is not in the other grid of arbitrary afterbody
Until more than specified amount threshold, so that the multilevel splitting for completing the road network divides.
3. processing method according to claim 1, which is characterized in that the basis is corresponding with the region area of grid
Code length encodes each grid, comprising:
Pre-establish the corresponding relationship of geographic area area and code length；
Calculate the geographic area area of each grid；
The code length of each grid is obtained according to the corresponding relationship；
It is encoded using coordinate of the code length to the center of each grid.
4. processing method according to claim 1 or 3, which is characterized in that the wherein geographic area of the grid of current level
Area is greater than the geographic area area of the other grid of next stage.
5. processing method according to claim 1, which is characterized in that each anchor point for being included by the track data
It is encoded, comprising:
Determine the position coordinates for each anchor point that the track data is included, and the warp of the position coordinates to each anchor point
The character string that degree and latitude are constituted is encoded.
6. processing method according to claim 1, which is characterized in that described to calculate each anchor point and respective candidate road
The matching degree of each candidate road section in Duan Jihe determines that the section to match with each anchor point includes: according to matching degree
Each anchor point in multiple anchor points is successively chosen as current anchor point:
The matching degree of each candidate road section distance in current anchor point and candidate road section set is calculated, probability in matching degree is obtained
The maximum value of value is P1, P1={ p11, p12..., p1m, wherein m is candidate road section quantity；
The registration for calculating path and each candidate road section that historical trajectory data is included, obtains probability value in registration
Maximum value be P2, P2={ p21, p22..., p2m}；
The matching degree of operating range is calculated, the maximum value for obtaining probability value in matching degree is P3, P3={ p31, p32...,
p3m}；
Three probability values of current anchor point are subjected to COMPREHENSIVE CALCULATING, obtain the matching degree of current anchor point and each candidate road section
P, P=P1P2P3={p11p21p31, p12p22p32..., p1mp2mp3m, the maximum candidate road section of matching degree P be with it is described current
The section that anchor point matches.
7. processing method according to claim 1, which is characterized in that described to calculate each anchor point and respective candidate road
The matching degree of each candidate road section in Duan Jihe determines that the section to match with each anchor point includes: according to matching degree
Each anchor point in multiple anchor points is successively chosen as current anchor point:
At least one of following three kinds of calculating is carried out, and the calculated result based at least one of following three kinds calculating is come really
Determine the matching degree of each candidate road section in current anchor point and candidate road section set:
The matching degree of each candidate road section distance in current anchor point and candidate road section set is calculated, probability in matching degree is obtained
The maximum value of value is P1, P1={ p11, p12..., p1m, wherein m is candidate road section quantity；
The registration for calculating path and each candidate road section that historical trajectory data is included, obtains probability value in registration
Maximum value be P2, P2={ p21, p22..., p2m}；
The matching degree of operating range is calculated, the maximum value for obtaining probability value in matching degree is P3, P3={ p31, p32...,
p3m}。
8. a kind of computer program product comprising the executable program of processor, which is characterized in that the program is held by processor
It is performed the steps of when row
It carries out multilevel splitting to road network according to road mileage to divide to obtain multiple grids, and according to the region area phase with grid
Corresponding code length encodes each grid；
Track data to be processed is obtained, each anchor point for being included by the track data encodes；
The prefix matching that each anchor point and each grid are encoded, with the ownership grid of each anchor point of determination and
Adjacent mesh；
All candidate road sections in the ownership grid and adjacent mesh of each anchor point are extracted, it is respective to constitute each anchor point
Candidate road section set；
The matching degree for calculating each candidate road section in each anchor point and respective candidate road section set is determined according to matching degree
The section to match with each anchor point；And
Positional misalignment in the track data is corrected by the way that each anchor point to be associated with the section progress position to match
Anchor point, to complete the processing of the track data.
9. a kind of processing system of track data, which is characterized in that the processing system includes:
Processor；
Memory for storage processor executable instruction；
Wherein, the processor is configured to: carry out method described in any one of claim 1 to 7.
10. a kind of processing unit of track data characterized by comprising
Trellis encoding unit carries out multilevel splitting to road network according to road mileage and divides to obtain multiple grids, and according to net
The corresponding code length of the region area of lattice encodes each grid；
Anchor point coding unit obtains track data to be processed, and each anchor point for being included by the track data carries out
Coding；
Dot grid determination unit is positioned, the prefix matching that each anchor point and each grid are encoded is every to determine
The ownership grid and adjacent mesh of a anchor point；
Candidate road section set Component units extract all candidate road sections in the ownership grid and adjacent mesh of each anchor point,
To constitute the respective candidate road section set of each anchor point；
Section determination unit is matched, the matching of each candidate road section in each anchor point and respective candidate road section set is calculated
Degree, according to the determining section to match with each anchor point of matching degree；And
Processing unit corrects position in the track data by the way that each anchor point to be associated with the section progress position to match
The anchor point of misalignment is set, to complete the processing of the track data.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111292356A (en) * | 2020-02-20 | 2020-06-16 | 清华大学 | Method and device for matching motion trail with road |
| CN111309780A (en) * | 2020-01-21 | 2020-06-19 | 腾讯云计算（北京）有限责任公司 | Track data processing method and device |
| CN111341120A (en) * | 2019-12-04 | 2020-06-26 | 上海悦骑智能科技有限公司 | Vehicle reverse running detection method and system and vehicle |
| CN111649750A (en) * | 2020-04-29 | 2020-09-11 | 中国平安财产保险股份有限公司 | Vehicle GPS data map matching method, device, terminal and storage medium |
| CN111856521A (en) * | 2019-11-22 | 2020-10-30 | 北京嘀嘀无限科技发展有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN111854791A (en) * | 2020-07-21 | 2020-10-30 | 北京卡路里信息技术有限公司 | Motion trajectory determination method and device, terminal equipment and storage medium |
| CN112035467A (en) * | 2020-08-12 | 2020-12-04 | 武汉依迅北斗时空技术股份有限公司 | Vehicle driving mileage acquisition method and device |
| CN112082564A (en) * | 2020-08-11 | 2020-12-15 | 东莞理工学院 | Interactive map matching method and system |
| CN112214537A (en) * | 2020-09-16 | 2021-01-12 | 拓尔思信息技术股份有限公司 | Track characteristic modeling method and system for track retrieval and electronic device |
| CN112948361A (en) * | 2021-02-02 | 2021-06-11 | 北京三快在线科技有限公司 | Data restoration method and device |
| CN112947485A (en) * | 2021-03-31 | 2021-06-11 | 亿海蓝（北京）数据技术股份公司 | Path planning method and system |
| CN113326343A (en) * | 2021-06-17 | 2021-08-31 | 北京连山科技股份有限公司 | Road network data storage method and system based on multi-level grids and file indexes |
| CN113747382A (en) * | 2021-08-18 | 2021-12-03 | 北京九栖科技有限责任公司 | Mobile signaling trajectory denoising method, medium and computing device based on multistage filtering |
| CN114664104A (en) * | 2022-03-23 | 2022-06-24 | 阿里云计算有限公司 | Road network matching method and device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105628033A (en) * | 2016-02-26 | 2016-06-01 | 广西鑫朗通信技术有限公司 | Map matching method based on road connection relationship |
| CN106225791A (en) * | 2016-08-03 | 2016-12-14 | 福建工程学院 | A kind of GPS based on stress and strain model location and road matching method |
| CN106595680A (en) * | 2016-12-15 | 2017-04-26 | 福州大学 | Vehicle GPS data map matching method based on hidden markov model |
| CN107291842A (en) * | 2017-06-01 | 2017-10-24 | 武汉理工大学 | The track querying method encoded based on track |
| CN109029472A (en) * | 2018-07-10 | 2018-12-18 | 天津大学 | Map-matching method based on low sampling rate GPS track point |
| CN109916413A (en) * | 2019-03-18 | 2019-06-21 | 华南师范大学 | Road matching method, system, device and storage medium based on grid dividing |
-
2019
- 2019-06-28 CN CN201910575595.6A patent/CN110427360B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105628033A (en) * | 2016-02-26 | 2016-06-01 | 广西鑫朗通信技术有限公司 | Map matching method based on road connection relationship |
| CN106225791A (en) * | 2016-08-03 | 2016-12-14 | 福建工程学院 | A kind of GPS based on stress and strain model location and road matching method |
| CN106595680A (en) * | 2016-12-15 | 2017-04-26 | 福州大学 | Vehicle GPS data map matching method based on hidden markov model |
| CN107291842A (en) * | 2017-06-01 | 2017-10-24 | 武汉理工大学 | The track querying method encoded based on track |
| CN109029472A (en) * | 2018-07-10 | 2018-12-18 | 天津大学 | Map-matching method based on low sampling rate GPS track point |
| CN109916413A (en) * | 2019-03-18 | 2019-06-21 | 华南师范大学 | Road matching method, system, device and storage medium based on grid dividing |
Non-Patent Citations (2)
| Title |
|---|
| 中国科学技术信息研究所: "《科技信息研究前沿聚焦》", 30 June 2018, 科学技术文献出版社 * |
| 侯雄文: ""交通路网中移动对象的QMon-tree索引技术研究"", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111856521A (en) * | 2019-11-22 | 2020-10-30 | 北京嘀嘀无限科技发展有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN111341120A (en) * | 2019-12-04 | 2020-06-26 | 上海悦骑智能科技有限公司 | Vehicle reverse running detection method and system and vehicle |
| CN111309780A (en) * | 2020-01-21 | 2020-06-19 | 腾讯云计算（北京）有限责任公司 | Track data processing method and device |
| CN111292356A (en) * | 2020-02-20 | 2020-06-16 | 清华大学 | Method and device for matching motion trail with road |
| CN111292356B (en) * | 2020-02-20 | 2024-03-19 | 清华大学 | Method and device for matching motion trail with road |
| CN111649750A (en) * | 2020-04-29 | 2020-09-11 | 中国平安财产保险股份有限公司 | Vehicle GPS data map matching method, device, terminal and storage medium |
| CN111649750B (en) * | 2020-04-29 | 2023-08-08 | 中国平安财产保险股份有限公司 | Vehicle GPS data map matching method, device, terminal and storage medium |
| CN111854791A (en) * | 2020-07-21 | 2020-10-30 | 北京卡路里信息技术有限公司 | Motion trajectory determination method and device, terminal equipment and storage medium |
| CN112082564B (en) * | 2020-08-11 | 2022-09-06 | 东莞理工学院 | Interactive map matching method and system |
| CN112082564A (en) * | 2020-08-11 | 2020-12-15 | 东莞理工学院 | Interactive map matching method and system |
| CN112035467A (en) * | 2020-08-12 | 2020-12-04 | 武汉依迅北斗时空技术股份有限公司 | Vehicle driving mileage acquisition method and device |
| CN112214537A (en) * | 2020-09-16 | 2021-01-12 | 拓尔思信息技术股份有限公司 | Track characteristic modeling method and system for track retrieval and electronic device |
| CN112948361A (en) * | 2021-02-02 | 2021-06-11 | 北京三快在线科技有限公司 | Data restoration method and device |
| CN112947485A (en) * | 2021-03-31 | 2021-06-11 | 亿海蓝（北京）数据技术股份公司 | Path planning method and system |
| CN113326343A (en) * | 2021-06-17 | 2021-08-31 | 北京连山科技股份有限公司 | Road network data storage method and system based on multi-level grids and file indexes |
| CN113747382A (en) * | 2021-08-18 | 2021-12-03 | 北京九栖科技有限责任公司 | Mobile signaling trajectory denoising method, medium and computing device based on multistage filtering |
| CN113747382B (en) * | 2021-08-18 | 2022-08-19 | 北京九栖科技有限责任公司 | Mobile signaling trajectory denoising method, medium and computing device based on multistage filtering |
| CN114664104A (en) * | 2022-03-23 | 2022-06-24 | 阿里云计算有限公司 | Road network matching method and device |
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