CN110475198B - Urban road user track deviation correction processing method and device - Google Patents
Urban road user track deviation correction processing method and device Download PDFInfo
- Publication number
- CN110475198B CN110475198B CN201810430970.3A CN201810430970A CN110475198B CN 110475198 B CN110475198 B CN 110475198B CN 201810430970 A CN201810430970 A CN 201810430970A CN 110475198 B CN110475198 B CN 110475198B
- Authority
- CN
- China
- Prior art keywords
- road
- intersection
- information
- user
- road intersection
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
Abstract
The embodiment of the invention discloses a method and a device for correcting a track of an urban road user, wherein the method comprises the following steps: determining the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence in a preset time period according to the acquired reference data, and screening out road users according to the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence; determining a road intersection passed by the road user according to the position information reported by the road user; and correcting the road intersection passed by the road user according to the position information of the road user so as to enable the position data of the road user to fall on the actual road. According to the embodiment of the invention, the position data of the road user falls into the actual road by performing the correction processing on the road intersection passed by the screened road user, so that the accuracy of road intersection identification and the accuracy of road correction are improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of communication, in particular to a method and a device for correcting a user track of an urban road.
Background
Because of the problem of positioning accuracy of the current XDR (XML Data Representation ), errors are more than ten meters averagely, and the width of a common road is less than ten meters, so that the longitude and latitude of the XDR of a user part on the road are not on the road; on the other hand, since the user does not perform a service or the coverage is not good, the position information of the user is discontinuous, and finally, a deviation occurs when functions such as single-user track playback, virtual test, road index statistics and the like are realized.
The position identification of the road user is the basis of the functions of single-user track playback, virtual test, road index statistics and the like. The prior art mainly includes the following technologies for identifying user tracks: the method comprises the steps of obtaining a user segmented track through a service cell change sequence and service cell longitude and latitude of a user, calculating the user segmented track and a cell sequence on each road, and taking a line with the highest similarity as a line of the segment of track; according to the other scheme, the position information and the road layer information reported by the user are directly used, and the position of the foot is used as the road position information of the user according to a foot calculation formula of points and straight lines.
The method using the approximate trajectory fitting of the user has similar drawbacks to the method using the drop foot position as the road position information of the user: in dense urban areas, particularly on two adjacent and close parallel roads, under the current positioning accuracy, the road on which a user is located at the end cannot be correctly identified, so that errors are caused.
Disclosure of Invention
Because the existing method has the problems, the embodiment of the invention provides a method and a device for correcting the urban road user track.
In a first aspect, an embodiment of the present invention provides a method for correcting an urban road user trajectory, including:
determining the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence in a preset time period according to the acquired reference data, and screening out road users according to the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence;
determining a road intersection passed by the road user according to the position information reported by the road user;
and correcting the road intersection passed by the road user according to the position information of the road user so as to enable the position data of the road user to fall on the actual road.
Optionally, the determining, according to the location information reported by the road user, a road intersection through which the road user passes specifically includes:
generating a road intersection position library according to the road map layer;
generating a road intersection level fingerprint database according to the road intersection position database, the drive test data and the work parameter information in the area;
and determining the road intersection passed by the road user according to the longitude and latitude information, the cell information and the level information of the sampling point reported by the road user, the road intersection position base and the road intersection level fingerprint base.
Optionally, the determining a road intersection where the road user passes according to the longitude and latitude information, the cell information, and the level information of the sampling point reported by the road user, the road intersection position library, and the road intersection level fingerprint library specifically includes:
acquiring first road intersection information which is passed by the road user according to the longitude and latitude information and the road intersection position library;
acquiring second road intersection information which is passed by the road user according to the level information and the road intersection level fingerprint database;
and merging the first road intersection information and the second road intersection information according to the positioning precision to obtain a confidence intersection and an unconfirmed intersection.
Optionally, the performing, according to the plurality of pieces of location information of the road user, a deviation rectification process on a road intersection where the road user passes through so that the location data of the road user falls on an actual road specifically includes:
generating an adjacent road intersection relation library according to the road intersection position library and the positioning data, and determining a confidence road section according to the adjacent road intersection relation library;
and correcting the deviation of the road user passing through the road intersection according to the confidence road section, the confidence intersection, the non-confidence intersection and the drop foot calculation formula of the point and line segment.
Optionally, before determining the outdoor cell traversal number and the linear distance of the outdoor cell sequence within a preset time period according to the acquired reference data, and screening the road users according to the outdoor cell traversal number and the linear distance of the outdoor cell sequence, the method further includes:
and if the work parameter information in the area is judged and known to change or the wireless environment is judged to change, the reference data is acquired again.
Optionally, the determining, according to the location information reported by the road user, a road intersection through which the road user passes specifically includes:
determining road intersection passed by the road user according to longitude and latitude information, cell information and level information of the sampling points reported by the road user, and generating a road intersection sequence of the road user;
determining an interruption part of the line of the road user according to the road intersection sequence of the road user, supplementing intersection information according to the interruption part, generating a road intersection traversal sequence of the road user, and taking all intersection information in the road intersection traversal sequence as the road intersections passed by the road user.
In a second aspect, an embodiment of the present invention further provides an urban road user trajectory rectification processing apparatus, including:
the user screening module is used for determining the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence in a preset time period according to the acquired reference data, and screening road users according to the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence;
the road intersection determining module is used for determining the road intersection passed by the road user according to the position information reported by the road user;
and the deviation rectifying module is used for rectifying the deviation of the road intersection passed by the road user according to the plurality of pieces of position information of the road user so as to enable the position data of the road user to fall into the actual road.
Optionally, the road intersection determining module specifically includes:
the position library generating unit is used for generating a road intersection position library according to the road map layer;
the fingerprint database generating unit is used for generating a road intersection level fingerprint database according to the road intersection position database, the road test data and the work parameter information in the area;
and the intersection determining unit is used for determining the road intersection passed by the road user according to the longitude and latitude information, the cell information and the level information of the sampling point reported by the road user, the road intersection position base and the road intersection level fingerprint base.
In a third aspect, an embodiment of the present invention further provides an electronic device, including:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein:
the memory stores program instructions executable by the processor, which when called by the processor are capable of performing the above-described methods.
In a fourth aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium storing a computer program, which causes the computer to execute the above method.
According to the technical scheme, the embodiment of the invention has the advantages that the road intersection passed by the screened road users is subjected to deviation rectification treatment, so that the position data of the road users fall on the actual road, and the accuracy of road intersection identification and the precision of road deviation rectification are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for correcting the urban road user trajectory according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a deviation rectifying processing method for urban road user tracks according to another embodiment of the present invention;
fig. 3 is a schematic structural diagram of an urban road user trajectory deviation rectifying device according to an embodiment of the present invention;
fig. 4 is a logic block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The following further describes embodiments of the present invention with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
Fig. 1 shows a schematic flow chart of a deviation rectifying processing method for urban road user tracks provided by this embodiment, which includes:
s101, determining the outdoor cell traversal number and the straight-line distance of the outdoor cell sequence in a preset time period according to the acquired reference data, and screening out road users according to the outdoor cell traversal number and the straight-line distance of the outdoor cell sequence.
The reference data does not need to be acquired frequently, and can be used for a long time after being acquired once. When the work parameters in the area change or the wireless environment changes significantly, the reference data needs to be acquired again.
Specifically, after reference data are obtained, corresponding data are selected from the reference data to be calculated, the outdoor cell traversal number and the straight-line distance of the outdoor cell sequence within a preset time period are obtained, the outdoor cell traversal number and the straight-line distance of the outdoor cell sequence are screened according to a threshold value, a road user is obtained, and the outdoor cell traversal sequence of the user within one hour is counted in time sequence; and screening out users and user data of which the traversal number of the outdoor cells is greater than a threshold value (default is 5, and the modification is available) and the sum of the linear distances of the outdoor cell sequences is greater than the threshold value (default is 5km, and the modification is available) within one hour.
S102, determining the road intersection passed by the road user according to the position information reported by the road user.
Specifically, the position information reported by the road user is received, and the road intersection passed by the road user is determined according to the position information.
The position information comprises longitude and latitude information, cell information and level information.
The road intersection is an intersection of at least two roads.
S103, correcting the road intersection passed by the road user according to the plurality of pieces of position information of the road user, so that the position data of the road user falls into the actual road.
Specifically, because of the precision reason of location, accurate location can not be accomplished, and the actual position that partial positional information corresponds is not in the road, consequently through carrying out the processing of rectifying to road intersection, can obtain the road intersection of high accuracy, further obtains accurate user's orbit on the road through the road intersection of high accuracy, makes road user's position data fall into on the actual road.
In the embodiment, the road intersection passed by the screened road user is subjected to deviation rectification, so that the position data of the road user falls into the actual road, and the accuracy of road intersection identification and the precision of road deviation rectification are improved.
Further, on the basis of the above method embodiment, S102 specifically includes:
and S1021, generating a road intersection position library according to the road map layer.
And S1022, generating a road intersection level fingerprint database according to the road intersection position database, the drive test data and the work parameter information in the area.
And S1022, determining the road intersection passed by the road user according to the longitude and latitude information, the cell information and the level information of the sampling point reported by the road user, the road intersection position library and the road intersection level fingerprint library.
Specifically, as shown in fig. 2, the data sources include four types: mass OTT (Over The Top, which means providing various application services for users through The Internet) positioning data, road layer information, drive test data and regional work parameter information; there are three types of data output: the system comprises an adjacent road intersection relation library, a road intersection position library of road intersection names and road intersection longitudes and latitudes and a road intersection level fingerprint library.
The generating of the road intersection position library according to the road map layer specifically comprises: extracting all road name information in a target area from the road layer data; and calling a known map API (application program interface) to acquire longitude and latitude information of intersection of every two roads.
Taking an Application Programming Interface (API) Interface as an example, transmitting a "XXXX path and yyyy path intersection" to the Baidu, returning a longitude and latitude and a confidence value, removing the record with the confidence value lower than the threshold value, and setting the threshold value of the Baidu map to be 0.5.
If the longitude and latitude is not in a WGS-84(World geographic System 1984, a geocentric coordinate System adopted internationally) coordinate System, the longitude and latitude are firstly converted into the WGS-84 coordinate System from the non-WGS-84 coordinate System;
the road intersection position data obtained are shown in the following table:
| CrosssRoads (road intersection) | Longituude (Longitude) | Latitude (Latitude) |
| Route | 121.406679 | 31.177038 |
| …… | …… | …… |
| …… | …… | …… |
| …… | …… | …… |
Generating a dictionary according to a [ crossheads ] field in the road intersection position library, recording the dictionary as DIC _ crossheads, wherein a key (key) of the dictionary is a value in the [ crossheads ] field in the road intersection position library, and a key value is a natural number from 1, so that the road intersection position library is obtained as shown in the following table:
the method for generating the road intersection level fingerprint database according to the road intersection position database, the road test data and the work parameter information in the area specifically comprises the following steps:
a1, according to a road intersection position library, taking the position as a center, extending a meters up, down, left and right (a refers to the width of an intersection, the distance between two adjacent MR sampling points when a test vehicle passes through the intersection and the positioning error, the default is 25, and the positioning error can be set) as a screening range, and screening out records at the road intersection position in the net pulling data;
a2, converting the frequency point and PCI (Peripheral Component Interconnect) of the adjacent region in the record of the road intersection position into cell ECI (Electronic Conversion Interface) according to the engineering parameter information;
a3, counting the average level and sample points of a main service cell of each road intersection, and the average level and sample points of each adjacent cell;
a4, recording the cell with the most sample points and the average level in the main service cell as the main service cell, the average level and the standard deviation of the road intersection; in the adjacent cells, the n cells with the largest sample points, the average level and the standard deviation are recorded as the first adjacent cell, the first adjacent cell level and the first adjacent cell standard deviation of the road intersection according to the average level being larger than the maximum value, the second adjacent cell level and the second adjacent cell standard deviation are sequentially analogized, and n is equal to 2 in the example;
a5, generating a dictionary for the cell ECI in the regional work parameter information, recording the dictionary as DIC _ ECI, wherein the key (key) of the dictionary is the cell ECI in the regional work parameter information, and the key is a natural number from 1;
a6, generating row road intersection information and column sparse matrixes of cell level information according to the data in the step A4 and the step A5 (the mth row of the matrix represents road intersections with key values of m in a dictionary DIC _ CrossRoads, and the nth column of the matrix represents the average level and standard deviation of cells with key values of n in a dictionary DIC _ ECI);
and A7, storing the sparse matrix generated in the step A6, namely the road intersection level fingerprint database, in a ternary array mode, wherein the first column represents the row number m of the sparse matrix, the second column represents the column number n of the sparse matrix, and the third column represents the value of the mth row and the nth column of the sparse matrix.
The format of the road intersection level fingerprint database is shown in the following table:
| 1 | 1 | -103|3.5 |
| 1 | 3 | -109|4.1 |
| 1 | 4 | -120|5.2 |
| 3 | 15 | -89|5.7 |
| …… | …… | …… |
further, on the basis of the foregoing method embodiment, S1022 specifically includes:
s10221, obtaining the first road intersection information passed by the road user according to the longitude and latitude information and the road intersection position library.
S10222, obtaining second road intersection information passed by the road user according to the level information and the road intersection level fingerprint database.
S10223, according to the positioning precision, the first road intersection information and the second road intersection information are merged to obtain a confidence intersection and an unconfirmed intersection.
For example, first, road intersection information a that the user passes is acquired according to the longitude and latitude information:
according to a road intersection position library, taking the position as a center, extending a meters (default 25, which can be set) up, down, left and right respectively as a screening range, screening records at the road intersection position, road intersection information and time corresponding to each record and the linear distance between a sampling point and the road intersection in the user reported data, and sequencing according to the recorded time; if the same record number of the adjacent record road intersections exceeds 1, the intersection is considered to be an equal stop intersection, and the equal stop time is the time span of the same record number of the adjacent record road intersections; the adjacent record of the same intersection keeps the straight line distance to be minimum.
Then, acquiring road intersection information B passed by the user according to the level information:
according to the road intersection level fingerprint library, three cells with road fingerprints exist at the same time, and the level value of each cell is in the range of [ average level value-standard deviation, average level value + standard deviation ] as a screening condition, so that records at the road intersection position, road intersection information corresponding to each record, time and Euclidean distance between sampling point level information and the road intersection level fingerprint library in the user reported data are screened out; if the same record number of the adjacent record road intersections exceeds 1, the intersection is considered to be an equal stop intersection, and the equal stop time is the time span of the same record number of the adjacent record road intersections; the adjacent record has the minimum Euclidean distance reserved at the same intersection.
And then merging the road intersection information A and the road intersection information B according to the positioning precision:
if the positioning accuracy is high (OTT positioning is used), according to the road intersection information A which is acquired in the step a) and is passed by the user and the time at a certain intersection, taking [ time-k seconds, time + k seconds ] as a time window (k is an empirical value, default is 5 seconds, and the intersection is considered as a confidence intersection if the same intersection can be found in the result B, otherwise, the intersection is considered as an unconfirmed intersection;
otherwise, according to the acquired road intersection information B passed by the user and the time at a certain intersection, taking [ time-k seconds, time + k seconds ] as a time window (k is an empirical value, default is 5 seconds), and if the similar intersection can be found in the result A, the intersection is considered as a confidence intersection, otherwise, the intersection is considered as an untrusted intersection.
Further, on the basis of the above method embodiment, S103 specifically includes:
and S1031, generating an adjacent road intersection relation library according to the road intersection position library and the positioning data, and determining a confidence road section according to the adjacent road intersection relation library.
S1032, correcting the deviation of the road user passing through the road intersection according to the confidence road section, the confidence intersection, the non-confidence intersection and the drop foot calculation formula of the point and line segment.
The foot calculation formula of the point and the line segment can be expressed as the following formula:
wherein D is the coordinate of the point and the foot of the line segment, F is the direction vector of the line segment, FTIs the transposed vector of vector F, P is the coordinate vector of a point, P0Is a coordinate vector of a point on the straight line where the line segment is located.
Specifically, an adjacent road intersection relation library is generated according to a road intersection position library and mass OTT positioning data; screening out records of the OTT positioning data in the road intersection positions according to a road intersection position library; according to the road intersection change rule of each user, two adjacent road intersections (hereinafter referred to as road sections) belonging to a single row are identified; and identifying two adjacent road intersections according to an adjacent road intersection identification algorithm.
According to the one-way road information, correcting the adjacent road intersection, generating an adjacent road intersection relation library of the relation between the current intersection and the next intersection, and storing key values corresponding to the road intersection in a dictionary DIC _ CrossRoads; calculating the line distance L of two adjacent intersections by combining the road layer information to obtain an adjacent road intersection relation library, wherein the format of the adjacent road intersection relation library is shown as the following table:
| current intersection | Next way mouth | Distance road (m) |
| 1 | 2 | 350 |
| 2 | 1 | 350 |
| 1 | 3 | 295 |
| 1 | 4 | 378 |
| 4 | 1 | 378 |
| …… | …… |
The road intersection sequence is composed of a confidence intersection or an unconfirmed intersection according to a time sequence, and at the moment, the adjacent road intersection is corrected according to the adjacent road intersection relation library in sequence, wherein the correction principle is as follows:
two adjacent intersections in the traversal road intersection sequence have an adjacent relation in the adjacent road intersection relation library, and the road section between the two intersections is considered as a confidence road section; the confidence links with common road intersection are merged, and if A → B and B → C are two confidence links, the merged link is the link A → B → C.
Connecting the confidence road section and the confidence road junction or the confidence road section and the confidence road section by inserting the road junction according to the following principle:
if the average speed of a newly inserted path is greater than P times of the speed of the original path (default is 3 and configurable) or the average speed is greater than V (default is 120km/h and configurable), deleting the confidence intersection and executing again;
if an unconfirmed intersection exists between the confident intersection and the confident road section, two methods of inserting the road intersection or inserting the road intersection after removing the unconfirmed road intersection are selected to be simultaneously carried out, the principle is shown as the principle of inserting the road intersection, and if the average speed of a newly inserted path is greater than P times of the speed of the previous path (default is 3 and can be configured) or the average speed is greater than V (default is 60km/h and can be configured), the confident intersection is deleted and the method is executed again.
And (3) directly connecting the two confidence road sections, and inserting a road intersection between the two confidence road sections by adopting the following 'principle of inserting the road intersection':
firstly, inserting a road intersection, wherein the road intersection and the near-end point of the previous road intersection or the confidence road section have an adjacent relation in an adjacent road intersection relation library, and the road intersection and the near-end point of the next road intersection or the confidence road section have an adjacent relation in an adjacent road intersection relation library, so that the inserted intersection, the confidence road intersection and the confidence road section form a new confidence road section, and if a plurality of intersections meet the condition at the same time, the path distance is minimum to serve as the new confidence road section; otherwise, inserting two intersections and analogizing in sequence; stopping the insertion if a suitable path is found; inserting intersection time, taking the time of a near-end point of a previous intersection or a confidence road section as inspiration time, taking the MR (measurement report) record reported by a user in a time range as ending time, calculating Euclidean distance with the level fingerprint of the intersection inserted in the intersection level fingerprint library (taking n +1 cell in the level fingerprint of the inserted intersection as reference, only calculating the Euclidean distance on the n +1 cell, if the MR does not report a certain cell level, considering the level value of the MR on the cell to be 0), and taking the recorded time with the minimum Euclidean distance as the time of the user at the inserted intersection; the road intersection is considered as an unequal stopping intersection.
When the road intersection is subjected to road deviation correction, according to the time information of the road intersection traversal sequence of the user obtained in the previous step, the event of the user on any road section is screened out, and the road section position information of a road layer is combined, and according to the positioning precision, the position information of the event is corrected on the road (which can be manually selected through configuration control), and the principle is as follows:
if the positioning precision is high (OTT positioning is used), calculating a foot according to a point and line segment vertical point calculation formula, wherein the foot is the position of the event on the road section; if the drop foot falls outside the line segment, taking the near end point of the line segment as the position of the event on the road segment;
otherwise, considering that the user drives at a constant speed except for the waiting time, and calculating the average speed of the user in a road section:
wherein, L is the length of the road section, and T is the time for walking the road section. Then according to
(where, t is the time difference between the time when a certain event occurs and the starting point of the road segment), obtaining the distance S between the user and the starting point of the road segment when the certain event occurs, and then using the position on the road segment from the starting point S as the position information of the event; and taking the longitude and latitude of the parking intersection as the position information of the event in the parking waiting time.
Further, on the basis of the above embodiment of the method, before S101, the method further includes:
and S100, if the work parameter information in the area is judged and known to change or the wireless environment is judged and known to change, the reference data is acquired again.
The preparation of the reference data mainly provides the reference data for subsequent data processing, and the data processing is a process of correcting the user record after the completion of an adjacent road intersection relation library, a road intersection position library of road intersection names and road intersection longitudes and latitudes and a road intersection level fingerprint library. The preparation of the reference data is performed prior to the data processing, and the preparation is not required to be performed frequently, and the reference data can be used for a long time after being generated once. The adjacent road intersection relation library, the road intersection name + road intersection longitude and latitude position library are in the same area and can be used for a long time; the road intersection level fingerprint library can be used within a period of time, and when the work parameters in the area change or the wireless environment changes remarkably, the fingerprint library needs to be regenerated.
Further, on the basis of the above method embodiment, S102 specifically includes:
s1021, determining road intersection passed by the road user according to the longitude and latitude information, the cell information and the level information of the sampling point reported by the road user, and generating a road intersection sequence of the road user.
S1022, determining an interruption part of the line of the road user according to the road intersection sequence of the road user, supplementing intersection information according to the interruption part, generating a road intersection traversal sequence of the road user, and taking all intersection information in the road intersection traversal sequence as the road intersection passed by the road user.
Specifically, in the prior art, the method of using the user's approximate trajectory fitting needs to obtain the cell traversal sequence of each line in advance, the data acquisition cost is high, and the data change is fast due to the problem of adding new sites, and is not easy to maintain, so that the problem of user trajectory interruption cannot be solved. The embodiment is divided into two aspects of data preparation and data correction, wherein the data preparation mainly provides reference data for the data correction and belongs to early work; the data correction firstly screens out road users, then determines all road intersections passed by the users, generates a road intersection sequence of the users, finds out the interrupted part of a user line according to the road intersection sequence of the users, supplements intersection information, generates a road intersection traversal sequence of the users, and finally uses a point-to-straight-line foot drop calculation formula or the displacement calculation of the users on the road to enable the data of the users to fall on the road.
According to the embodiment, the passing road intersection sequence of the user is automatically identified by using the longitude and latitude of the road intersection or the road intersection fingerprint, so that the identification accuracy of the road intersection sequence is improved; and automatically selecting a road deviation rectifying mode according to the positioning precision, thereby improving the road deviation rectifying precision.
Fig. 3 shows a schematic structural diagram of an urban road user trajectory rectification processing device provided in this embodiment, where the device includes: user screening module 301, road intersection determine module 302 and processing module 303 of rectifying, wherein:
the user screening module 301 is configured to determine the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence in a preset time period according to the acquired reference data, and screen out road users according to the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence;
the road intersection determining module 302 is configured to determine a road intersection through which the road user passes according to the location information reported by the road user;
the deviation rectifying module 303 is configured to rectify a deviation of a road intersection where the road user passes according to the plurality of position information of the road user, so that the position data of the road user falls on an actual road.
Specifically, the user screening module 301 determines the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence in a preset time period according to the acquired reference data, and screens out the road users according to the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence; the road intersection determining module 302 determines the road intersection passed by the road user according to the position information reported by the road user; the deviation rectifying module 303 rectifies the road intersection passed by the road user according to the position information of the road user, so that the position data of the road user falls into the actual road.
In the embodiment, the road intersection passed by the screened road user is subjected to deviation rectification, so that the position data of the road user falls into the actual road, and the accuracy of road intersection identification and the precision of road deviation rectification are improved.
Further, on the basis of the above device embodiment, the road intersection determining module 302 specifically includes:
the position library generation unit is used for generating a road intersection position library according to the road map layer;
the fingerprint database generating unit is used for generating a road intersection level fingerprint database according to the road intersection position database, the road test data and the work parameter information in the area;
and the intersection determining unit is used for determining the road intersection passed by the road user according to the longitude and latitude information, the cell information and the level information of the sampling point reported by the road user, the road intersection position base and the road intersection level fingerprint base.
Further, on the basis of the above apparatus embodiment, the intersection determining unit is specifically configured to:
acquiring first road intersection information which is passed by the road user according to the longitude and latitude information and the road intersection position library;
acquiring second road intersection information which is passed by the road user according to the level information and the road intersection level fingerprint database;
and merging the first road intersection information and the second road intersection information according to the positioning precision to obtain a confidence intersection and an unconfirmed intersection.
Further, on the basis of the above device embodiment, the deviation rectifying module 303 specifically includes:
the confidence road section determining unit is used for generating an adjacent road intersection relation library according to the road intersection position library and the positioning data and determining a confidence road section according to the adjacent road intersection relation library;
and the deviation rectifying processing unit is used for rectifying the deviation of the road user passing through the road intersection according to the confidence road section, the confidence road intersection, the non-confidence road intersection and the drop foot calculation formula of the point and line segment.
Further, on the basis of the above embodiment of the apparatus, the apparatus further comprises:
and the data updating module is used for acquiring the reference data again if the work parameter information in the region is judged to be changed or the wireless environment is judged to be changed.
Further, on the basis of the above device embodiment, the road intersection determining module 302 specifically includes:
the intersection sequence generating unit is used for determining the road intersection passed by the road user according to the longitude and latitude information, the cell information and the level information of the sampling point reported by the road user and generating a road intersection sequence of the road user;
and the road intersection determining unit is used for determining an interruption part of the line of the road user according to the road intersection sequence of the road user, supplementing intersection information according to the interruption part, generating a road intersection traversal sequence of the road user, and taking all intersection information in the road intersection traversal sequence as the road intersections passed by the road user.
The urban road user trajectory deviation rectifying processing device described in this embodiment may be used to implement the above method embodiments, and the principle and technical effect are similar, which are not described herein again.
Referring to fig. 4, the electronic device includes: a processor (processor)401, a memory (memory)402, and a bus 403;
wherein the content of the first and second substances,
the processor 401 and the memory 402 complete communication with each other through the bus 403;
the processor 401 is configured to call program instructions in the memory 402 to perform the methods provided by the above-described method embodiments.
The present embodiments disclose a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the methods provided by the above-described method embodiments.
The present embodiments provide a non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the methods provided by the method embodiments described above.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
It should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A deviation rectifying processing method for urban road user tracks is characterized by comprising the following steps:
determining the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence in a preset time period according to the acquired reference data, and screening out road users according to the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence;
determining a road intersection passed by the road user according to the position information reported by the road user;
correcting the road intersection passed by the road user according to the position information of the road user so as to enable the position data of the road user to fall on the actual road;
the reference data includes: the system comprises an adjacent road intersection relation library, a road intersection position library of road intersection names and road intersection longitudes and latitudes, and a road intersection level fingerprint library;
the determining the road intersection passed by the road user according to the position information reported by the road user specifically comprises:
and determining the road intersection passed by the road user according to the longitude and latitude information, the cell information and the level information of the sampling point reported by the road user, the road intersection position base and the road intersection level fingerprint base.
2. The method according to claim 1, wherein the determining the road intersection passed by the road user according to the longitude and latitude information, the cell information and the level information of the sampling point reported by the road user, the road intersection position library and the road intersection level fingerprint library specifically comprises:
acquiring first road intersection information which is passed by the road user according to the longitude and latitude information and the road intersection position library;
acquiring second road intersection information which is passed by the road user according to the level information and the road intersection level fingerprint database;
and merging the first road intersection information and the second road intersection information according to the positioning precision to obtain a confidence intersection and an unconfirmed intersection.
3. The method according to claim 2, wherein the performing of the deviation rectification processing on the road intersection passed by the road user according to the plurality of pieces of position information of the road user so as to make the position data of the road user fall on the actual road specifically comprises:
determining a confidence road section according to the adjacent road intersection relation library;
and correcting the deviation of the road user passing through the road intersection according to the confidence road section, the confidence intersection, the non-confidence intersection and the drop foot calculation formula of the point and line segment.
4. The method according to claim 1, wherein before determining the outdoor cell traversal number and the straight-line distance of the outdoor cell sequence within a preset time period according to the acquired reference data, and screening the road users according to the outdoor cell traversal number and the straight-line distance of the outdoor cell sequence, the method further comprises: acquiring reference data;
the acquiring of the reference data specifically includes:
generating a road intersection position library according to the road map layer;
generating an adjacent road intersection relation library according to the road intersection position library and the positioning data;
generating a road intersection level fingerprint database according to the road intersection position database, the drive test data and the work parameter information in the area;
further comprising:
and if the work parameter information in the area is judged and known to change or the wireless environment is judged to change, the reference data is acquired again.
5. The method according to any one of claims 1 to 4, wherein the determining the road intersection passed by the road user according to the location information reported by the road user specifically comprises:
determining road intersection passed by the road user according to longitude and latitude information, cell information and level information of the sampling points reported by the road user, and generating a road intersection sequence of the road user;
determining an interruption part of the line of the road user according to the road intersection sequence of the road user, supplementing intersection information according to the interruption part, generating a road intersection traversal sequence of the road user, and taking all intersection information in the road intersection traversal sequence as the road intersections passed by the road user.
6. The utility model provides an urban road user's orbit processing apparatus that rectifies which characterized in that includes:
the user screening module is used for determining the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence in a preset time period according to the acquired reference data, and screening road users according to the traversal number of the outdoor cells and the linear distance of the outdoor cell sequence;
the road intersection determining module is used for determining the road intersection passed by the road user according to the position information reported by the road user;
the correction processing module is used for correcting the road intersection passed by the road user according to a plurality of pieces of position information of the road user so as to enable the position data of the road user to fall on an actual road;
the reference data includes: the system comprises an adjacent road intersection relation library, a road intersection position library of road intersection names and road intersection longitudes and latitudes, and a road intersection level fingerprint library;
the road intersection determining module specifically comprises:
and the intersection determining unit is used for determining the road intersection passed by the road user according to the longitude and latitude information, the cell information and the level information of the sampling point reported by the road user, the road intersection position base and the road intersection level fingerprint base.
7. An electronic device, comprising:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein:
the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of any of claims 1 to 5.
8. A non-transitory computer-readable storage medium storing a computer program that causes a computer to perform the method according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810430970.3A CN110475198B (en) | 2018-05-08 | 2018-05-08 | Urban road user track deviation correction processing method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810430970.3A CN110475198B (en) | 2018-05-08 | 2018-05-08 | Urban road user track deviation correction processing method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110475198A CN110475198A (en) | 2019-11-19 |
| CN110475198B true CN110475198B (en) | 2021-01-26 |
Family
ID=68503244
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810430970.3A Active CN110475198B (en) | 2018-05-08 | 2018-05-08 | Urban road user track deviation correction processing method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110475198B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113194532B (en) * | 2021-04-13 | 2023-04-28 | 中国移动通信集团陕西有限公司 | User positioning method and device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101308029A (en) * | 2007-05-16 | 2008-11-19 | 北京英华慧通科技发展有限公司 | Road network grid matching, road status messages and introduction route information acquisition method |
| WO2010044188A1 (en) * | 2008-10-17 | 2010-04-22 | 三菱電機株式会社 | Navigation device |
| CN101819042A (en) * | 2009-02-26 | 2010-09-01 | 爱信艾达株式会社 | Guider and navigation program |
| CN102589554A (en) * | 2010-11-24 | 2012-07-18 | 株式会社电装 | Road estimation device and method for estimating road |
| CN104427513A (en) * | 2013-08-30 | 2015-03-18 | 华为技术有限公司 | Identification method, device, network equipment and network system |
-
2018
- 2018-05-08 CN CN201810430970.3A patent/CN110475198B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101308029A (en) * | 2007-05-16 | 2008-11-19 | 北京英华慧通科技发展有限公司 | Road network grid matching, road status messages and introduction route information acquisition method |
| WO2010044188A1 (en) * | 2008-10-17 | 2010-04-22 | 三菱電機株式会社 | Navigation device |
| CN101819042A (en) * | 2009-02-26 | 2010-09-01 | 爱信艾达株式会社 | Guider and navigation program |
| CN102589554A (en) * | 2010-11-24 | 2012-07-18 | 株式会社电装 | Road estimation device and method for estimating road |
| CN104427513A (en) * | 2013-08-30 | 2015-03-18 | 华为技术有限公司 | Identification method, device, network equipment and network system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110475198A (en) | 2019-11-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2021017679A1 (en) | Address information parsing method and apparatus, system and data acquisition method | |
| CN107103754B (en) | Road traffic condition prediction method and system | |
| CN106997466A (en) | Method and apparatus for detecting road | |
| CN106844781B (en) | Data processing method and device | |
| CN111212383B (en) | Method, device, server and medium for determining number of regional permanent population | |
| CN102799890A (en) | Image clustering method | |
| CN104599002B (en) | Method and equipment for predicting order value | |
| CN112541852B (en) | Urban people stream monitoring method and device, electronic equipment and storage medium | |
| CN115374375B (en) | Track clustering method, system and storage medium based on deep learning | |
| CN109740479A (en) | A kind of vehicle recognition methods, device, equipment and readable storage medium storing program for executing again | |
| CN115130711A (en) | Data processing method and device, computer and readable storage medium | |
| CN111353620A (en) | Method, device and equipment for constructing network point component prediction model and storage medium | |
| CN112486338A (en) | Medical information processing method and device and electronic equipment | |
| CN111858814A (en) | Method, device and equipment for repairing motion trail and storage medium | |
| CN110475198B (en) | Urban road user track deviation correction processing method and device | |
| CN109344255B (en) | Label filling method and terminal equipment | |
| CN111325255B (en) | Specific crowd delineating method and device, electronic equipment and storage medium | |
| CN110990651B (en) | Address data processing method and device, electronic equipment and computer readable medium | |
| CN112287503A (en) | Dynamic space network construction method for traffic demand prediction | |
| CN110955804A (en) | Adaboost method for detecting user spatio-temporal data behaviors | |
| CN106887184B (en) | Route update method and device | |
| CN114141235A (en) | Voice corpus generation method and device, computer equipment and storage medium | |
| CN112712855A (en) | Joint training-based clustering method for gene microarray containing deletion value | |
| CN117596551B (en) | Green road network user behavior restoration method and device based on mobile phone signaling data | |
| CN110366094B (en) | Method and device for determining coordinate system, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |