CN106707301A - Positioning data based service line patrol assessment method - Google Patents
Positioning data based service line patrol assessment method Download PDFInfo
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- CN106707301A CN106707301A CN201611224916.0A CN201611224916A CN106707301A CN 106707301 A CN106707301 A CN 106707301A CN 201611224916 A CN201611224916 A CN 201611224916A CN 106707301 A CN106707301 A CN 106707301A
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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
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/13—Receivers
- G01S19/14—Receivers specially adapted for specific applications
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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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Abstract
The invention relates to positioning data based mobile police service management, and particularly relates to a positioning data based service line patrol assessment method. The positioning data based service line patrol assessment method comprises buffer area establishment and segmentation of a line patrol path, mapping of positioning data, interpolation compensation of the positioning data and restoration compensation of the line patrol path; the line patrol path forms a grid through establishing and segmenting a buffer area, the positioning data is mapped to the grid according to the spatial position and distance, labeling is performed on the grid, data coverage of the grid is compensated in an interpolation manner so as to form relatively complete grid data mapping, and finally a line patrol path is fitted through the grid. The method provided by the invention emphatically solves a problem of positioning data based multi-vehicle line patrol attendance matching in service management, problems of positioning data line matching of multiple vehicles on multiple lines, insufficient positioning data coverage density, loss of positioning data and the like exist when attendance checking is performed on service patrolling through the positioning data, and the problems are solved through data buffering for the line patrol path and compensation for positioning data coverage.
Description
Technical field
The present invention relates to public security duties line walking examination field, more particularly to a kind of duties line walking examination based on location data
Method.
Background technology
With the continuous improvement of computer information level, government organs or enterprise in the way to manage of internal staff to going out
A certain degree of innovation is showed, especially to the work attendance appraisal management aspect of personnel.With GPS or the Big Dipper positioning, radio communication with
And the technology such as GIS GIS-Geographic Information System turns into the important channel of many industry internal controls for the mobile examination work attendance of core, leads to
The historical track of the real-time position information and personnel of following the trail of personnel in time is crossed, auxiliary internal administrative staff hold task in time
Execution state.
Used as the alignment system of the important component of system application, the precision and continuity of its positioning directly determine movement
The effect that examination work attendance business is carried out.Although current alignment system has the ability of accurate, round-the-clock, real-time positioning higher,
And also achieve GPS to be positioned with Big Dipper bimodulus, but there is fix drift and signal blind zone in itself due to alignment system (in height
When building or the masking local such as overhead, signal receiver can not in time be captured and trace into framing signal, cause positioning function to fail
Etc. inherent shortcoming, mobile communications network has that network signal is weak and the performance issue such as dropout in itself, so as to cause to position number
According to loss or invalid, thus location data there are problems that it is discontinuous;Additionally, route matching above, most side
Method is mapped on route by location data, and the matching of route is carried out by the connection of mapping point, and the method can be effective
Bicycle patrol problem is solved, there is deviation for the situation of many cars patrol.
The content of the invention
The present invention is to overcome above-mentioned weak point, it is therefore intended that provide a kind of duties line walking examination based on location data
Method, the first reference path to artificial setting enter the structure of row buffer, and segmentation formation is carried out to buffer area with horizon radius
Several grids;Location data is mapped in grid according to Euclidean distance, the grid to having covered carries out virtualization mark, complete
The grid that will have been covered after into mapping is digitized, and the Interpolation compensation of line of going forward side by side forms actual patrol path, finally presses
According to the facts patrol path in border matches path with the virtualization coverage rate of reference path, obtains last result.This method emphasis is solved
The examination matching problem of many car patrol missions during movable police examination.
The present invention is to reach above-mentioned purpose by the following technical programs:A kind of duties line walking examination side based on location data
Method, comprises the following steps:
(1) path space data and Manual definition's line walking path are initialized, line walking path is passed through with path space data
Euclidean distance carries out parallel mapping matching with track, generates the line walking reference path L with travel directioni, wherein, i=1,2 ...,
n;
(2) to line walking reference path LiEnter the structure of row buffer, gridding is carried out to buffer area with horizon radius, split
Form several grids;
(3) obtain location data and cleaning compensation deals are carried out to location data, location data is mapped in grid, it is right
The grid that every line walking reference path has mapped covering carries out virtualization mark, generator matrixWherein, k represents kth
Car, j represents j-th grid, and r is vehicle fleet, miIt is line walking reference path LiOn grid sum, according to positioning data of vehicles
Whether map in grid, matrix interior element is digitized;
(4) non-grid coverage data correlation degree δ is calculated, and linear interpolation compensation is carried out to matrix using δ and obtain new
Matrix;
(5) new matrix is carried out or operates and obtain line walking reference path LiCoverage rate pi;
(6) to forming actual patrol path after examination associated vehicle path interpolation compensation, and with line walking reference path Li's
Coverage rate piIt is overlapped and is calculated average coverage rateWillWith pmIt is compared and obtains the result of appraisal, wherein, pmIt is default
Coverage rate threshold value.
Preferably, described path space data are including road axis data, with directive road data, space
Point digit according to this and space block data, using original road axis data as elementary path space number after initialization
According to.
Preferably, the step (2) is to line walking reference path LiThe method for entering the structure of row buffer is:With line walking base
Quasi- path LiIt is reference, to line walking reference path LiPointwise carries out vertical radiation, and the radius of radiation is R, is distinguished along vertical direction
Radiation, builds reference path LiBuffering area Ai;And according to reference path LiBearing mark buffering area direction;If running into slow
Area overlapping is rushed, the differentiation of buffering area is made a distinction with the direction for marking.
Preferably, the step (2) carries out gridding to buffer area with horizon radius, segmentation forms several grids
Method is as follows:
A () is by line walking reference path LiRespectively extend L outward along two end points and generate new reference path, and select wherein
An end points be starting point, carry out cutting along reference path direction with 2*L as radius and acquire intersection point to be designated as Li1, wherein L
It is cut radius;
B () is according to Li1Centered on point, be that radius obtains intersection point L along the cutting of reference path direction with 2*Li2;According to above-mentioned
Method is iterated the intersection point set that computing is acquired in reference path, is designated as { Lij, wherein i=1,2 ..., n;J=1,
2,…,mi;
C () carries out vertical radiation generation grid lines to the point on the basis of the point in set, and indicia grid is Gij。
Preferably, the step (3) is as follows the step for the treatment of the location data for obtaining:
1) to line walking reference path LiTraveled through, the location data of associated vehicle in examination time window is obtained successively, and
Classification is carried out according to unique positioning sign to sum up, according to time ascending sort, form location data set { Ckt, wherein k=1,
2 ... r;T=1,2 ... q, k represent kth vehicle, and t represents t-th time point, location data CktUnique positioning mark is included,
Position longitude and latitude (xkt,ykt) and data acquisition time Tkt;
2) traversal location data set { Ckt, spatial accessibility verification is carried out to two position datas of point of time order and function,
If spatial accessibility is when can not reach, to filter location data;Otherwise retain location data;Described spatial accessibility verification side
Method is the speed by obtaining point-to-point transmission, is judged whether in interval [0, Vmax] in, the acquisition methods of speed are as follows:
Wherein VmaxIt is speed reachability threshold, works as v>VmaxRepresentation space accessibility is to reach;3) by Ck(t-1)And Ckt
Location data be mapped to reference path, if the mapping distance of location data and reference path is less than 2R (R is radiation radius)
Then mapped, the mapping point in reference path is designated as p respectivelyi(t-1)And pitStep 4 is performed afterwards);When more than 2R, to this
Point carries out abandoning treatment, performs step 2);
4) judge whether vehicle goes offline:To step 3) treatment after location data set Ckt, Δ t=Tkt-Tk(t-1)It is number
According to upload be spaced;If Δ t > 2Tm, wherein TmIt is the time judgment threshold that goes offline, then judges that the car goes offline, perform step 5);
Otherwise perform step 2);
5) interception reference path is between point pi(t-1)With point pitThe spatial data of section, calculates its length, is combined using length
Ck(t-1)And CktBetween time interval obtain passage rateIf passage rateThen according toDistance obtain
The point that point in reference path is repaired as compensation.
Preferably, the step (3) is traveling through location data set CktIn all location datas after will position number
The method for obtaining digitizing matrix according to matching network is as follows:
(A) location data is mapped to by reference path L to line beeline according to pointiOn, by reference path LiOn point institute
Grid make virtualization mark, and generator matrixWherein k is represented and reference path LiThe kth vehicle of association, j generations
J-th grid of table, r is vehicle fleet, miIt is line walking reference path LiOn grid sum;Need in this step to putting to benchmark
The beeline in path enters row constraint, and beeline is constrained to less than 2*L, and the location data of right >=2*L is abandoned;
(B) matrix for generating is digitized, when k car has mapping point position on j-th grid, then marks ak*j
It is 1, otherwise labeled as 0.
Preferably, the formula that the step (4) calculates non-grid coverage data correlation degree δ is as follows:
Wherein:TfFor there are data before non-grid coverage data time point in same direction grid in maximum time number
Strong point;TbFor there are data after non-grid coverage data time point grid in minimum time data point;T is compensation grid number
According to time point, by stepping TfAnd TbBetween time point acquired in, b and f represent respectively where grid sequence number;J is represented and worked as
The sequence number of preceding grid;The center position for obtaining non-grid coverage is designated as (x, y), and the adjacent data point for having data grids is remembered respectively
It is (xi, yi), viThere is the speed put in data grids to adjacent not cover data grids;By calculating adjacent net in time window
Spatial accessibility v between latticei, finally to spatial accessibility and absolute accessibilityCorrelation degree obtain degree of association δ.
Preferably, the step (4) using δ matrix is carried out Interpolation compensation obtain new matrix method be to association
Degree is directly repaired higher than the matrix element of confidential interval;Element to the degree of association in confidential interval enters row interpolation benefit
Repay, Interpolation compensation method is to extracting matrixThe data of middle row k and labelled element value are the interval between 1, when
Then it is to carry out physical compensation by the mark that the matrix element in interval is 0 value when less than 3, generates new matrix.
Preferably, the 1st row in matrix is carried out or operated by concretely comprising the following steps for the step (5) with row k respectively, will
Result set replaces the first row data, makees finally according to the ratio of the element and total number of grid for being is marked in the first row data
On the basis of path LiOverlay capacity, total amount and coverage rate pi。
Preferably, the step (6) willWith pmBe compared obtain the result of appraisal be specially work asWhen, representing should
Line walking task has been completed, and the mark result of appraisal are completion, otherwise labeled as unfinished;Wherein pmFor default.
The beneficial effects of the present invention are:(1) examination is moved by GPS location data, reduces the work of artificial examination
Measure, improve operating efficiency;(2) by the Interpolation compensation of location data, the degree of accuracy of line walking examination is improve, is made by fixed
The mode of position data examination is more rationally and effective;(3) by the compensation to mesh fitting data, improve grid data matching
Precision, improve location data examination accuracy.
Brief description of the drawings
Fig. 1 is the structure reference path grid flow chart of the embodiment of the present invention;
Fig. 2 is that the reference path of the embodiment of the present invention builds buffering area schematic diagram;
Fig. 3 is the buffering area gridding schematic diagram of the embodiment of the present invention;
Fig. 4 is the location data mesh fitting flow chart of the embodiment of the present invention;
Fig. 5 is the calculating result of appraisal flow chart of the embodiment of the present invention.
Specific embodiment
With reference to specific embodiment, the present invention is described further, but protection scope of the present invention is not limited in
This:
Embodiment:A kind of duties line walking wire examination method based on location data is related to the mobile duties based on location information to examine
Core, by location data and the Auto-matching of patrol route, realizes the examination work attendance of duties management, specifically includes following steps:
(1) the step of building reference path grid, as shown in Figure 1:
Step 1-1, path space data initialization
Path space data include road axis data, with directive road data, point position in space data and
Space block data.This method needs to match reference path by original path space data, using original road
Centreline data is used as elementary path spatial data.
Step 1-2, reference path matching generation
Before examination business is carried out, line walking path is defined by user;Due to manually draw line walking path when, with
There are some deviations in road luv space data, the line walking path of Manual definition and path space data are passed through Euclidean by this method
Distance carries out parallel mapping matching with track, generates the line walking reference path L with travel directioni(i=1,2 ..., n).
Step 1-3, structure reference path buffering area
As shown in Fig. 2 with reference path as reference, to line walking reference path LiThe method for entering the structure of row buffer is:
With line walking reference path LiIt is reference, to line walking reference path LiPointwise carries out vertical radiation, and the radius of radiation is R, along vertical
Direction radiates respectively, builds reference path LiBuffering area Ai;And according to reference path LiBearing mark buffering area direction;
If running into buffering area overlapping, the differentiation of buffering area is made a distinction with the direction for marking..
Step 1-4, gridding is carried out to buffering area
As shown in figure 3, for the buffering area of step 1-3 generations, to buffering area AiSplit, generated the net of buffering area
Lattice.Specific method is by line walking reference path LiRespectively extend L outward along two end points and generate new reference path, and select it
In an end points be starting point, carry out cutting along reference path direction with 2*L as radius and acquire intersection point to be designated as Li1, wherein
L is cut radius;According to Li1Centered on point, be that radius obtains intersection point L along the cutting of reference path direction with 2*Li2;According to upper
The method of stating is iterated the intersection point set that computing is acquired in reference path, is designated as { Lij, wherein i=1,2 ..., n;J=1,
2,…,m;Grid lines (create-rule is to carry out vertical radiation to the point), and indicia grid are generated on the basis of the point in set
It is Gij。
(2) the step of location data mesh fitting, as shown in Figure 4:
Step 2-1, acquisition position history data, and sort
To line walking reference path LiTraveled through, the location data of associated vehicle in examination time window is obtained successively, and pressed
Classification is carried out according to unique positioning sign to sum up, according to time ascending sort, form location data set { Ckt, wherein k=1,
2 ... r;T=1,2 ... q, k represent kth vehicle, and t represents t-th time point, location data CktUnique positioning mark is included,
Position longitude and latitude (xkt,ykt) and data acquisition time Tkt;.
Step 2-2, judge whether noise data, Exception Filter data
Traversal location data set { Ckt, spatial accessibility verification is carried out to two data of point of time order and function, work as space
Accessibility is when can not reach, to filter location data.Spatial accessibility method of calibration is the velocity estimated by obtaining point-to-point transmission
Whether in interval [0, Vmax] in, the acquisition methods of speed are as follows:
Step 2-3, location data mapping reference path
By Ck(t-1)And CktLocation data be mapped to reference path, if location data is small with the mapping distance of reference path
Then mapped when 2R (R is radiation radius), the mapping point in reference path is designated as p respectivelyi(t-1)And pitAfter perform step
4);When more than 2R, the point is carried out to abandon treatment, perform step 2);
Step 2-4, judge whether to go offline
To step 3) treatment after location data set Ckt, Δ t=Tkt-Tk(t-1)For the upload of data is spaced;If Δ t
> 2Tm, wherein Tm is the time judgment threshold that goes offline, then judge that the car goes offline, and performs step 5);Otherwise perform step 2);
Step 2-5, location data compensation
Interception reference path is between point pi(t-1)With point pitThe spatial data of section, calculates its length, is combined using length
Ck(t-1)And CktBetween time interval obtain passage rateIf passage rateThen according toDistance obtain base
The point that point on quasi- path is repaired as compensation.
Step 2-6, location data matching network, generator matrix
Location data is mapped to reference path L by matching location data according to point in grid to line beelineiOn,
By reference path LiOn point where grid make virtualization mark, and generator matrixWherein k is represented and reference path
LiThe kth vehicle of association, j represents j-th grid, and r is vehicle fleet, miIt is line walking reference path LiOn grid sum;Herein
Need to enter the beeline of reference path row constraint to putting in step, beeline is constrained to less than 2*L, the positioning of right >=2*L
Data are abandoned.Matrix to generating is digitized, and when kth vehicle has mapping point position on j-th grid, then marks
ak*jIt is 1, otherwise labeled as 0.
(3) checking-in result is calculated, as shown in Figure 5:
Step 3-1, the non-grid coverage Data mutuality degree of calculating
The degree of correlation of grid data is main to be solved from the correlation in time and space, and method for solving is as follows:
Wherein:TfFor there are data before non-grid coverage data time point in same direction grid in maximum time number
Strong point;TbFor there are data after non-grid coverage data time point grid in minimum time data point;T is compensation grid number
According to time point, by stepping TfAnd TbBetween time point acquired in, b and f represent respectively where grid sequence number;J is represented and worked as
The sequence number of preceding grid;The center position for obtaining non-grid coverage is designated as (x, y), and the adjacent data point for having data grids is remembered respectively
It is (xi, yi), viThere is the speed put in data grids to adjacent not cover data grids;By calculating adjacent net in time window
Spatial accessibility v between latticei, finally to spatial accessibility and absolute accessibilityCorrelation degree obtain degree of association δ.
Step 3-2, according to degree of association δ to matrix interpolation compensate
Using δ matrix is carried out Interpolation compensation obtain new matrix method be to the degree of association higher than confidential interval matrix
Element is directly repaired;Element to the degree of association in confidential interval carries out Interpolation compensation, and Interpolation compensation method is to carrying
Take matrixThe data of middle row k and labelled element value are the interval between 1, when interval is less than W, then by interval
Matrix element is that the mark of 0 value is to compensate, and generates new matrix, and wherein W is backoff interval threshold value.
Step 3-3, acquisition grid coverage rate
1st row in matrix is carried out or operated with row k respectively, result set is replaced into the first row data, finally according to the
The ratio of the element and total number of grid for being is marked in data line as reference path LiOverlay capacity, total amount and covering
Rate pi。
Step 3-4, the calculating result of appraisal
According to the path of examination associated vehicle, the Interpolation compensation that step 3-2 is carried out respectively is calculated, and reference path is covered
Lid rate is overlapped calculating, and the method for calculating is average coverage rateWillWith pm(predetermined threshold value) is compared and obtains examination knot
Fruit is specially works asWhen, representing that the line walking task has been completed, the mark result of appraisal are completion, otherwise labeled as not complete
Into..
It is specific embodiment of the invention and the know-why used described in above, if conception under this invention institute
The change of work, function produced by it still without departing from specification and accompanying drawing covered it is spiritual when, should belong to of the invention
Protection domain.
Claims (10)
1. a kind of duties line walking wire examination method based on location data, it is characterised in that comprise the following steps:
(1) path space data and Manual definition's line walking path are initialized, line walking path and path space data is passed through into Euclidean
Distance carries out parallel mapping matching with track, generates the line walking reference path L with travel directioni, wherein, i=1,2 ..., n, n
It is line walking reference path number;
(2) to line walking reference path LiEnter the structure of row buffer, gridding is carried out to buffer area with horizon radius, segmentation is formed
Several grids;
(3) obtain location data and cleaning compensation deals are carried out to location data, location data is mapped in grid, to every
The grid that line walking reference path has mapped covering carries out virtualization mark, generator matrixWherein, k represents kth vehicle, j
J-th grid is represented, r is vehicle fleet, miIt is line walking reference path LiOn grid sum, according to positioning data of vehicles whether
Map in grid, matrix interior element is digitized;
(4) non-grid coverage data correlation degree δ is calculated, and Interpolation compensation is carried out to matrix using δ and obtain new matrix;
(5) new matrix is carried out or operates and obtain line walking reference path LiCoverage rate pi;
(6) to forming actual patrol path after examination associated vehicle path interpolation compensation, and with line walking reference path LiCoverage rate
piIt is overlapped and is calculated average coverage rateWillWith pmIt is compared and obtains the result of appraisal, wherein, pmIt is default covering
Rate threshold value.
2. a kind of duties line walking wire examination method based on location data according to claim 1, it is characterised in that:Described
Path space data are including road axis data, with directive road data, point position in space data and space block counts
According to using original road axis data as elementary path spatial data after initialization.
3. a kind of duties line walking wire examination method based on location data according to claim 1, it is characterised in that:The step
Suddenly (2) are to line walking reference path LiThe method for entering the structure of row buffer is:With line walking reference path LiIt is reference, to line walking base
Quasi- path LiPointwise carries out vertical radiation, and the radius of radiation is R, is radiated respectively along vertical direction, builds reference path LiIt is slow
Rush area Ai;And according to reference path LiBearing mark buffering area direction;If running into buffering area overlapping, the differentiation of buffering area with
The direction of mark makes a distinction.
4. a kind of duties line walking wire examination method based on location data according to claim 1, it is characterised in that:The step
Suddenly (2) carry out gridding to buffer area with horizon radius, and the method that segmentation forms several grids is as follows:
A () is by line walking reference path LiRespectively extend L outward along two end points and generate new reference path, and select therein one
Individual end points is starting point, carries out cutting along reference path direction with 2*L as radius and acquire intersection point to be designated as Li1, wherein L is to cut
Cut radius;
B () is according to Li1Centered on point, be that radius obtains intersection point L along the cutting of reference path direction with 2*Li2;Enter according to the method described above
Row iteration computing acquires the intersection point set in reference path, is designated as { Lij, wherein i=1,2 ..., n;J=1,2 ..., mi;
C () carries out vertical radiation generation grid lines to the point on the basis of the point in set, and indicia grid is Gij。
5. a kind of duties line walking wire examination method based on location data according to claim 1, it is characterised in that:The step
Suddenly the step of (3) are processed the location data for obtaining is as follows:
1) to line walking reference path LiTraveled through, the location data of associated vehicle in examination time window is obtained successively, and according to only
One positioning sign carries out classification and sums up, and according to time ascending sort, forms location data set { Ckt, wherein k=1,2 ... r;t
=1,2 ... q, k represent kth vehicle, and t represents t-th time point, location data CktInclude unique positioning mark, position longitude and latitude
Degree (xkt,ykt) and data acquisition time Tkt;
2) traversal location data set { Ckt, spatial accessibility verification is carried out to two position datas of point of time order and function, if empty
Between accessibility for can not reach when, filter location data;Otherwise retain location data;Described spatial accessibility method of calibration is
By obtaining the speed of point-to-point transmission, judge whether in interval [0, Vmax] in, the acquisition methods of speed are as follows:
Wherein VmaxIt is speed reachability threshold, works as v>VmaxRepresentation space accessibility is to reach;
3) by Ck(t-1)And CktLocation data be mapped to reference path, if location data is less than with the mapping distance of reference path
Then mapped during 2R (R is radiation radius), the mapping point in reference path is designated as p respectivelyi(t-1)And pitAfter perform step
4);When more than 2R, the point is carried out to abandon treatment, perform step 2);
4) judge whether vehicle goes offline:To step 3) treatment after location data set Ckt, Δ t=Tkt-Tk(t-1)It is upper for data
Pass interval;If Δ t > 2Tm, wherein TmIt is the time judgment threshold that goes offline, then judges that the car goes offline, perform step 5);Otherwise hold
Row step 2);
5) interception reference path is between point pi(t-1)With point pitThe spatial data of section, calculates its length, using length combination Ck(t-1)
And CktBetween time interval obtain passage rateIf passage rateThen according toDistance obtain benchmark road
The point that point on footpath is repaired as compensation.
6. a kind of duties line walking wire examination method based on location data according to claim 5, it is characterised in that:The step
Suddenly (3) are traveling through location data set CktIn all location datas after by location data matching network obtain digitize matrix
Method it is as follows:
(A) location data is mapped to by reference path L to line beeline according to pointiOn, by reference path LiOn point where
Grid makees virtualization mark, and generator matrixWherein k is represented and reference path LiThe kth vehicle of association, j represents jth
Individual grid, r is vehicle fleet, miIt is line walking reference path LiOn grid sum;Need in this step to putting to reference path
Beeline enters row constraint, and beeline is constrained to less than 2*L, and the location data of right >=2*L is abandoned;
(B) matrix for generating is digitized, when kth vehicle has mapping point position on j-th grid, then marks ak*jFor
1, otherwise labeled as 0.
7. a kind of duties line walking wire examination method based on location data according to claim 1, it is characterised in that:The step
Suddenly the formula of the non-grid coverage data correlation degree δ of (4) calculating is as follows:
Wherein:TfFor there are data before non-grid coverage data time point in same direction grid in maximum time data point;
TbFor there are data after non-grid coverage data time point grid in minimum time data point;T is compensation grid data
Time point, by stepping TfAnd TbBetween time point acquired in, b and f represent respectively where grid sequence number;J represents current net
The sequence number of lattice;The center position for obtaining non-grid coverage is designated as (x, y), and the adjacent data point for having data grids is designated as respectively
(xi, yi), viThere is the speed put in data grids to adjacent not cover data grids;By calculating adjacent mesh in time window
Between spatial accessibility vi, finally to spatial accessibility and absolute accessibilityCorrelation degree obtain degree of association δ.
8. a kind of duties line walking wire examination method based on location data according to claim 1, it is characterised in that:The step
Suddenly (4) using δ matrix is carried out Interpolation compensation obtain new matrix method be to the degree of association higher than confidential interval matrix element
Element is directly repaired;Element to the degree of association in confidential interval carries out Interpolation compensation, and Interpolation compensation method is to extracting
MatrixThe data of middle row k and labelled element value are the interval between 1, when interval is less than W, then by the square in interval
Array element element is to compensate for the mark of 0 value, generates new matrix, and wherein W is backoff interval threshold value.
9. a kind of duties line walking wire examination method based on location data according to claim 1, it is characterised in that:The step
Suddenly the 1st row in matrix is carried out or operated by concretely comprising the following steps for (5) with row k respectively, result set is replaced into the first row data, most
Afterwards according to marking the ratio of the element and total number of grid for being in the first row data as reference path LiOverlay capacity, total
Amount and coverage rate pi。
10. a kind of duties line walking wire examination method based on location data according to claim 1, it is characterised in that:It is described
Step (6) willWith pmBe compared obtain the result of appraisal be specially work asWhen, represent that the line walking task has been completed, mark
The note result of appraisal are completion, otherwise labeled as unfinished.
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Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107154066A (en) * | 2017-06-27 | 2017-09-12 | 中国电子科技集团公司第五十四研究所 | A kind of two-dimentional display methods of parallel lines buffering area patrol route |
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CN108829966A (en) * | 2018-06-07 | 2018-11-16 | 国网上海市电力公司 | A kind of enhanced grid for power-line patrolling system determines method |
CN108921386A (en) * | 2018-06-07 | 2018-11-30 | 国网上海市电力公司 | A kind of line walking efficiency automatic examination method for power-line patrolling |
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WO2020083402A1 (en) * | 2018-10-26 | 2020-04-30 | 江苏智通交通科技有限公司 | Method for deploying traffic police on urban roads |
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Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100324752A1 (en) * | 2008-03-27 | 2010-12-23 | Toyota Jidosha Kabushiki Kaisha | Gradient information calculating system, vehicle running control system, navigation system, and gradient information calculating method |
CN102147261A (en) * | 2010-12-22 | 2011-08-10 | 南昌睿行科技有限公司 | Method and system for map matching of transportation vehicle GPS (Global Position System) data |
CN103500507A (en) * | 2013-09-30 | 2014-01-08 | 宝鸡市公安局交通警察支队 | Portable mobile section speed measurement realization method and system based on satellite positioning system and GIS (Geographic Information System) |
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 |
-
2016
- 2016-12-27 CN CN201611224916.0A patent/CN106707301B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20100324752A1 (en) * | 2008-03-27 | 2010-12-23 | Toyota Jidosha Kabushiki Kaisha | Gradient information calculating system, vehicle running control system, navigation system, and gradient information calculating method |
CN102147261A (en) * | 2010-12-22 | 2011-08-10 | 南昌睿行科技有限公司 | Method and system for map matching of transportation vehicle GPS (Global Position System) data |
CN103500507A (en) * | 2013-09-30 | 2014-01-08 | 宝鸡市公安局交通警察支队 | Portable mobile section speed measurement realization method and system based on satellite positioning system and GIS (Geographic Information System) |
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 |
Non-Patent Citations (2)
Title |
---|
孙玉奎: "利用GPS、GIS、GSM/GPRS实现高速公路交巡警指挥调度、勤务管理的研究与应用", 《道路交通管理》 * |
金国伟等: "无人机巡线技术与路径定位巡线技术对比分析", 《信息化研究》 * |
Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
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WO2020083402A1 (en) * | 2018-10-26 | 2020-04-30 | 江苏智通交通科技有限公司 | Method for deploying traffic police on urban roads |
CN109615723A (en) * | 2018-11-30 | 2019-04-12 | 泰华智慧产业集团股份有限公司 | Inspection route coverage condition automatic analysis method and system |
CN111291143A (en) * | 2020-01-16 | 2020-06-16 | 深圳市华傲数据技术有限公司 | Grid data acquisition method and system |
CN113945153A (en) * | 2020-07-16 | 2022-01-18 | 远景网格有限公司 | Method and device for determining distance and position by image tracking for automatic driving |
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