CN111522044B - Vehicle positioning method and device - Google Patents
Vehicle positioning method and device Download PDFInfo
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- CN111522044B CN111522044B CN202010374011.1A CN202010374011A CN111522044B CN 111522044 B CN111522044 B CN 111522044B CN 202010374011 A CN202010374011 A CN 202010374011A CN 111522044 B CN111522044 B CN 111522044B
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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
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
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Abstract
In order to solve the problem of low positioning accuracy of a detection vehicle in the current road defect detection, the invention provides a vehicle positioning method and a device, wherein the method comprises the following steps: determining a covariance matrix of initial speed and position of a road detection vehicle; calculating to obtain prediction data of the current moment according to the covariance matrix of the speed and the position at the previous moment; the prediction data at the initial moment is obtained by calculation according to the covariance matrix of the initial speed and position; acquiring observation data of the current moment output by positioning equipment, wherein the observation data comprises observation position and speed information of a road detection vehicle; and fusing the prediction data and the observation data to obtain the fused positioning information at the current moment and a covariance matrix of the position and the speed, wherein the fused positioning information comprises the position and the speed information of the road detection vehicle after fusion. This application has improved the degree of accuracy and the accuracy of detecting the car location.
Description
Technical Field
The invention relates to the field of road defect detection, in particular to a vehicle positioning method and device.
Background
Along with the increasing popularization of automobiles, the pressure borne by roads is increased, and the surface of some roads with longer service time is damaged by cracks, broken marks and the like, so that great traffic hidden troubles are brought to people going out. The road maintenance department mostly adopts methods such as manual observation and detection to detect the road damage, which not only has low efficiency, but also has high cost. For the automatic road detection System, although the detection efficiency is improved, since the Positioning data of the vehicle-mounted GPS (Global Positioning System) has the characteristics of unstable data, inaccurate data and the like, the distance between the highway mileage stake marks is too long, and accurate Positioning information cannot be provided for the aspects of road maintenance, detection and the like.
Disclosure of Invention
In order to solve the problem that the positioning accuracy of a detection vehicle is low in the current road defect detection, the embodiment of the application provides a vehicle positioning method and device, so that the positioning accuracy of the detection vehicle is improved, road maintenance personnel can accurately find the position of a road defect, and the road maintenance efficiency is improved.
In a first aspect, an embodiment of the present application provides a vehicle positioning method, including:
determining a covariance matrix of initial speed and position of a road detection vehicle;
calculating to obtain prediction data of the current moment according to the covariance matrix of the speed and the position of the previous moment, wherein the prediction data comprises the prediction position and the speed information of the road detection vehicle and the covariance matrix of the position and the speed of the current moment; the prediction data at the initial moment is obtained by calculation according to the covariance matrix of the initial speed and position;
acquiring observation data of the current moment output by positioning equipment, wherein the observation data comprises observation position and speed information of the road detection vehicle;
and fusing the prediction data and the observation data to obtain the fused positioning information at the current moment and a covariance matrix of the position and the speed, wherein the fused positioning information comprises the position and the speed information of the road detection vehicle after fusion.
Wherein the determining of the covariance matrix of the initial speed and position of the road detection vehicle comprises:
collecting positioning information of a stationary state and a moving state of a road detection vehicle, wherein the positioning information comprises position and speed information of the road detection vehicle, and the road detection vehicle is provided with positioning equipment;
and carrying out statistical analysis on the positioning information of the stationary state and the moving state of the road detection vehicle to obtain a first covariance matrix, wherein the first covariance matrix is a covariance matrix of the initial speed and position of the road detection vehicle.
Wherein, still include:
acquiring position information of a highway mileage pile;
and when the road detection vehicle runs to a second road mileage stake, correcting the fusion positioning information of the road detection vehicle by using the position of the second road mileage stake.
Wherein, still include: generating a plurality of road mileage piles between the second road mileage pile and a first road mileage pile, the first road mileage pile being a last road mileage pile of the second road mileage pile.
Wherein, still include:
and displaying the fusion positioning information, the first road mileage pile, the second road mileage pile and a plurality of road mileage piles generated between the second road mileage pile and the first road mileage pile.
Wherein the positioning device is a GPS device.
In a second aspect, an embodiment of the present application provides a vehicle positioning apparatus, including:
a determining unit for determining a covariance matrix of an initial speed and position of the road detection vehicle;
the calculation unit is used for calculating and obtaining prediction data of the current moment according to the covariance matrix of the speed and the position of the previous moment, wherein the prediction data comprises the prediction position and the speed information of the road detection vehicle and the covariance matrix of the position and the speed of the current moment; the prediction data at the initial moment is obtained by calculation according to the covariance matrix of the initial speed and position;
the acquisition unit is used for acquiring observation data of the current moment output by the positioning equipment, wherein the observation data comprises the observation position and the speed information of the road detection vehicle;
and the fusion unit is used for fusing the prediction data and the observation data to obtain the fused positioning information at the current moment and a covariance matrix of the position and the speed, wherein the fused positioning information comprises the position and the speed information of the road detection vehicle after fusion.
Wherein the determination unit is configured to:
collecting positioning information of a static state and a motion state of a road detection vehicle, wherein the positioning information comprises position and speed information of the road detection vehicle, and the road detection vehicle is provided with positioning equipment;
and carrying out statistical analysis on the positioning information of the static state and the motion state of the road detection vehicle to obtain a first covariance matrix, wherein the first covariance matrix is the covariance matrix of the initial speed and position of the road detection vehicle.
In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and the computer program is used for implementing the steps of any one of the above methods when executed by a processor.
In a fourth aspect, an embodiment of the present application provides an electronic device, which includes a storage unit, a processing unit, and a computer program stored on the storage unit and executable on the processing unit, where the processing unit implements the steps of any one of the methods when executing the program.
The vehicle positioning method and the vehicle positioning device have the following beneficial effects:
according to the vehicle positioning method, the prediction data of the current moment are obtained through calculation according to the covariance matrix of the speed and the position of the last moment, the observation data of the current moment output by the positioning equipment are obtained, the prediction data and the observation data are fused, so that the fusion positioning information of the current moment and the covariance matrix of the position and the speed of the current moment are obtained, namely the positioning information of the current moment is obtained through fusion of the covariance of the speed and the position of the last moment and the measured data of the positioning equipment at the current moment, therefore, the accuracy and the precision of vehicle positioning are improved, a basis is provided for a road maintenance department to make a reasonable road maintenance plan, and the road maintenance efficiency is improved.
Drawings
FIG. 1 is a schematic flow chart of a vehicle positioning method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a method for obtaining a covariance matrix of speed and position at an initial time of a road detection vehicle in an embodiment of the present application;
FIG. 3 is a schematic representation of predicted data and observed data according to a Gaussian distribution in the present application;
FIG. 4 is a schematic illustration of the mileage stake numbers generated and displayed in the present application;
FIG. 5 is a diagram illustrating the result of track fusion in the present application;
FIG. 6 is a schematic structural diagram of a vehicle positioning device according to an embodiment of the present application.
Detailed Description
The present application is further described with reference to the following figures and examples.
In the following description, the terms "first" and "second" are used for descriptive purposes only and are not intended to indicate or imply relative importance. The following description provides embodiments of the invention, which may be combined or substituted for various embodiments, and this application is therefore intended to cover all possible combinations of the same and/or different embodiments described. Thus, if one embodiment includes features a, B, C and another embodiment includes features B, D, then this application should also be construed to include embodiments that include all other possible combinations of one or more of a, B, C, D, although such embodiments may not be explicitly recited in the following text.
The following description provides examples, and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of elements described without departing from the scope of the disclosure. Various examples may omit, substitute, or add various procedures or components as appropriate. For example, the described methods may be performed in an order different than the order described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.
With the promotion of vehicle popularity and the increase of road service time, great pressure is brought to traffic management departments and road maintenance departments. With the wide use of the civil GPS, the traffic management department can monitor the vehicle track in real time according to the positioning information transmitted by the GPS positioning equipment on the vehicle, thereby realizing scientific road traffic management; the road maintenance department can also install GPS equipment on the automatic road detection vehicle to carry out vehicle real-time positioning, and road maintenance personnel formulate a reasonable road maintenance plan according to the road defect positioning data.
In addition, the highway mileage pile is a scientific and effective highway positioning means, and a road detection department can quickly position the position range of the defect according to the number of the highway mileage pile. Highway mile posts are generally labeled along the line at a certain location on the highway with a long forward extension of one kilometer length.
Because the positioning data of the vehicle-mounted GPS has the characteristics of unstable data, inaccurate data and the like, the distance between the highway mileage stake marks is too long, accurate position information cannot be provided for the aspects of road maintenance, detection and the like, the road detection vehicle cannot be accurately positioned, the road maintenance personnel cannot accurately find the position of the road defect, and the road maintenance efficiency is reduced.
The existing vehicle positioning method has the defects of inaccurate positioning, unstable data, overlong distance between road mileage stake marks and the like. The method and the device aim to provide an accurate vehicle positioning method and device through a method of fusing a GPS and a highway mileage stake number, improve the accuracy and precision of vehicle positioning, provide basis for making a reasonable road maintenance plan for a road maintenance department, and improve the road maintenance efficiency.
The vehicle positioning method of the embodiment of the application comprises the following steps: determining a covariance matrix of initial speed and position of a road detection vehicle; according to the covariance matrix of the speed and the position at the previous moment, calculating to obtain prediction data of the current moment, wherein the prediction data comprises the prediction position and the speed information of a road detection vehicle and the covariance matrix of the position and the speed at the current moment; the prediction data at the initial moment is obtained by calculation according to the covariance matrix of the initial speed and position; acquiring observation data of the current moment output by positioning equipment, wherein the observation data comprises observation position and speed information of a road detection vehicle; and fusing the prediction data and the observation data to obtain the fused positioning information at the current moment and a covariance matrix of the position and the speed, wherein the fused positioning information comprises the position and the speed information of the road detection vehicle after fusion.
According to the vehicle positioning method, the prediction data of the current moment are obtained through calculation according to the covariance matrix of the speed and the position of the previous moment, the observation data of the current moment output by the positioning equipment are obtained, the prediction data and the observation data are fused to obtain the fusion positioning information of the current moment and the covariance matrix of the position and the speed of the current moment, namely, the positioning information of the current moment is obtained through fusion of the covariance of the speed and the position of the previous moment and the actually measured data of the positioning equipment at the current moment, so that the accuracy and the precision of vehicle positioning are improved, a basis is provided for a road maintenance department to make a reasonable road maintenance plan, and the road maintenance efficiency is improved.
Fig. 1 is a schematic flowchart of a vehicle positioning method according to an embodiment of the present application, and fig. 2 is a schematic flowchart of a vehicle positioning method according to an embodiment of the present application for obtaining a covariance matrix of a speed and a position of a road detection vehicle at an initial time, as shown in fig. 1-2, the vehicle positioning method according to the embodiment of the present application includes the steps of: s101, determining a covariance matrix of initial speed and position of a road detection vehicle; s103, calculating to obtain prediction data of the current moment according to the covariance matrix of the speed and the position of the previous moment, wherein the prediction data comprises the prediction position and the speed information of the road detection vehicle and the covariance matrix of the position and the speed of the current moment; the prediction data at the initial moment is obtained by calculation according to the covariance matrix of the initial speed and position; s105, acquiring observation data of the current moment output by the positioning equipment, wherein the observation data comprises the observation position and the speed information of the road detection vehicle; and S107, fusing the prediction data and the observation data to obtain the fused positioning information at the current moment and a covariance matrix of the position and the speed, wherein the fused positioning information comprises the position and the speed information of the road detection vehicle after fusion. Each step is described below.
S101, determining a covariance matrix of the initial speed and the initial position of the road detection vehicle.
In the method, the prediction data of the current moment is obtained through calculation according to the covariance matrix of the speed and the position of the previous moment, and the determination of the covariance matrix of the initial speed and the initial position of the road detection vehicle in the step is used for subsequently calculating the prediction data of the initial moment, because the initial moment has no previous moment. The covariance matrix of the initial speed and position of the road detection vehicle may be preset according to empirical values, or may be determined through the following steps S301 to S302:
as shown in fig. 2, in step S301, positioning information of a stationary state and a moving state of a road detection vehicle is collected, where the positioning information includes position and speed information of the road detection vehicle, and the road detection vehicle is equipped with a positioning device.
In some embodiments, the positioning device is a GPS device, and may also be a beidou satellite navigation device, a galileo satellite navigation device, a global navigation satellite device, or the like, and the positioning device is a GPS device as an example for description below. Data collection is carried out on a vehicle provided with a specific GPS device, and data statistical analysis is needed to be carried out on the data of a new GPS device under different states due to different characteristics of different devices. Setting the receiving frequency of GPS positioning equipment to be 10hz, converting the acquired position data into a plane rectangular coordinate system of a universal transverse ink card grid supporting system, wherein the positioning sequence acquired at one time is F = { F = (F) } 1 ,...,f t ,...f T H, where the anchor point data information is f t ＝[t,x,y,vel,yaw]And t represents the vehicle traveling to collection point f t Time of (c), [ x, y]Representing position information, vel velocity information, and yaw current angle information, where the vehicle travels to the collection point f t The instantaneous deflection angle of the phase relative to the positive north direction is that v = [ v = x ,v y ]Wherein the transverse (east-ward) velocity v x = vel sin (yaw), longitudinal (due north) velocity v y = vel × cos (yaw). Let p = [ x, y]，
Representing point f t And point f τ The distance between them.
Data acquisition in a static state is used for acquiring a positioning value and distribution thereof; data acquisition in a motion state is used for acquiring speed values and distribution thereof. For static state data acquisition, the detection vehicle is driven to an open area, the GPS device is fixed at the center of the vehicle roof, the GPS device is started, a specific time interval, such as 30 minutes, is set, and a position information sequence [ x, y ] output by the GPS device is recorded. For data acquisition in a moving state, the vehicle is driven at a fixed speed, such as 60km/h, and the speed value output by the GPS device is recorded.
Sequence of points f of the trajectory with respect to statistical analysis of the orientation values and distributions, velocity values and distributions t ＝[t,x,y,vel,yaw]Position information of [ x, y ]]Is random and follows a Gaussian distribution, i.e. there is a mean value p μ ＝[x μ ,y μ ]Representing the centre of the random distribution, and the variance σ p 2 Representing uncertainty; similarly, the uncertainty of the velocity information is random and follows Gaussian distribution, and the mean value v of the velocity information exists μ And variance σ v 2 。
The curves following a one-dimensional gaussian distribution are represented as follows:
for the positioning value and its distribution, take
By the same way, obtain
Variance (variance)
S302, statistical analysis is carried out on the positioning information of the road detection vehicle in the static state and the moving state to obtain a first covariance matrix, and the first covariance matrix is the covariance matrix of the initial speed and position of the road detection vehicle. The subsequent steps of the process of performing statistical analysis on the positioning information of the stationary state and the moving state of the road detection vehicle are introduced.
S103, calculating to obtain prediction data of the current moment according to the covariance matrix of the speed and the position of the previous moment, wherein the prediction data comprises the prediction position and the speed information of the road detection vehicle and the covariance matrix of the position and the speed of the current moment; and the prediction data at the initial moment is obtained by calculation according to the covariance matrix of the initial speed and position. And S105, acquiring the observation data of the current moment output by the positioning equipment, wherein the observation data comprises the observation position and the speed information of the road detection vehicle. And S107, fusing the prediction data and the observation data to obtain the fused positioning information at the current moment and a covariance matrix of the position and the speed, wherein the fused positioning information comprises the position and the speed information of the road detection vehicle after fusion.
The execution sequence of steps S103 and S105 is not sequential, and may be executed simultaneously.
FIG. 3 is a schematic diagram of the present application in which the predicted data and the observed data conform to a Gaussian distribution, and as shown in FIG. 3, the uncertainty of the position data collected by the GPS positioning device, i.e., the "observed value" is random and conforms to a Gaussian distribution; according to the positioning position information and the speed at the previous moment, the uncertainty of the positioning position information and the speed at the next moment, namely the predicted value, is also random and conforms to Gaussian distribution.
The vehicle with the specific GPS positioning device installed is in the following state at the last moment when the vehicle runs:
p represents a position, v represents a speed, the position information has correlation with the speed, and the faster the speed is, the farther the current time is, the position information and speed point covariance matrix is obtained:
let P 1 = Cov (p, v), the current time "prediction data" is:
for two fusions that obey a gaussian distribution:
N(x,μ′,σ′)＝N(x,μ 0 ,σ 0 )*N(x,μ 1 ,σ 1 )
let K = P 2 H T (HP 2 H T +P 1 ) Wherein here
The fusion result is a conversion matrix of the predicted value and the observed value:
P 2 ′＝P 2 -KHP 2 ，
for the fused position and velocity information at the present moment, P 2 ' this time position and velocity covariance matrix. Thereby obtaining a more accurate position and distribution thereof at the present moment.
In some embodiments, the vehicle localization method of the present application further comprises: acquiring position information of a highway mileage pile; and when the road detection vehicle runs to the second road mileage stake, correcting the fusion positioning information of the road detection vehicle by using the position of the second road mileage stake. And generating a plurality of road mileage piles between the second road mileage pile and the first road mileage pile, wherein the first road mileage pile is the last road mileage pile of the second road mileage pile.
Roads typically have one mile post per kilometer for marking location, and the following description will take the example of one mile post per kilometer for roads. In the application, the position data (position and speed) after fusion and the position data of the highway mile post are fused every kilometer to achieve the correction effect. In the process of vehicle driving, each kilometer of the highway has one kilometer of stake number, so that the secondary fusion correction is carried out on the fusion result of the previous step according to the kilometer of stake number, more accurate positioning can be obtained, hundred-meter stakes are automatically generated within the range of the previous kilometer, and because the GPS data has accumulated errors, the system can automatically take the new mile stake number as a starting point to carry out the superposition of prediction fusion again every time the new mile stake number is encountered.
Fig. 4 is a schematic diagram of mile post numbers generated and displayed in the application, and fig. 5 is a schematic diagram of a track fusion result in the application, as shown in fig. 4-5, a vehicle starts to travel from a certain road mile post number position, positioning fusion is performed according to the fusion method in the previous step, a current scene camera shoots the mile post number, then the track between two mile post numbers is corrected, and hundred-meter posts are generated in the track. If the vehicle starts to drive from the milepost number K0+000 and the milepost number K1+000 is shot, the track of the previous mile is adjusted, and the milepost numbers K0+000, K0+100, \8230, K1+000 are generated in the track, and the data is stored.
The number of the mileage stake marks generated in the track is determined according to the distance between adjacent mileage stake marks shot by the foreground camera, if the hundred-meter stake marks are shot, the hundred-meter stake marks are generated at the positions where the hundred-meter stake marks are shot, and in addition, ten-meter stake marks can be generated according to requirements. If the foreground camera continuously shoots the mile post numbers K1+000 and K1+100, the mile post numbers of K1+000 and K1+100 meters are generated in the last hundred-meter track, and the mile post numbers of K1+010, K1+020, \ 8230and K1+090 are added according to requirements.
The GPS data has accumulated errors, the fusion mentioned above is to perform 'prediction' according to the fusion result value of the previous step, and the accumulated errors are generated along with the increase of the prediction times, so when the camera shoots a new mileage stake mark, the fusion times are cleared, and the fusion calculation is performed again by taking the new mileage stake mark as an origin.
In some embodiments, the vehicle localization method of the present application further comprises: and displaying the fusion positioning information, the first road mileage pile, the second road mileage pile and a plurality of road mileage piles generated between the second road mileage pile and the first road mileage pile.
An embodiment of the present application further provides a vehicle positioning apparatus, as shown in fig. 6, including:
a determination unit 201 for determining a covariance matrix of initial speed and position of the road detection vehicle;
a calculating unit 202, configured to calculate prediction data at the current time according to a covariance matrix of a previous time of speed and position, where the prediction data includes predicted position and speed information of a road detection vehicle and a covariance matrix of a current time of position and speed; the prediction data at the initial moment is obtained by calculation according to the covariance matrix of the initial speed and position;
an obtaining unit 203, configured to obtain observation data of the current time output by the positioning device, where the observation data includes an observation position and speed information of a road detection vehicle;
and the fusion unit 204 is configured to fuse the predicted data and the observation data to obtain current fused positioning information and a covariance matrix of the position and the speed, where the fused positioning information includes the position and the speed information of the road detection vehicle after fusion.
The determination unit is to:
collecting positioning information of a static state and a motion state of a road detection vehicle, wherein the positioning information comprises position and speed information of the road detection vehicle, and the road detection vehicle is provided with positioning equipment;
and carrying out statistical analysis on the positioning information of the stationary state and the moving state of the road detection vehicle to obtain a first covariance matrix, wherein the first covariance matrix is the covariance matrix of the initial speed and the initial position of the road detection vehicle.
In some embodiments, the application includes a model training system, a data fusion system, a hectometer stake number generation system, a display system. The model training system comprises a data acquisition module and a model training module. The data acquisition module is responsible for acquiring data in a static state and a motion state; the model training module obtains a vehicle position covariance matrix by carrying out statistical analysis on the acquired data, and carries out data fusion on the predicted value and the observed value according to the vehicle position covariance matrix; the data storage module stores covariance matrix parameters of the positioning position and the speed of the sensor and processed road positioning data; the highway pile number fusion module performs secondary fusion on the fusion positioning result of the previous step and the highway mile piles, and automatically generates hectometer piles in the previous kilometer; and the fusion result display module is used for displaying the road fusion result.
In the application, data acquisition of a static state, a motion state and a road pile number position is carried out on a vehicle provided with a certain specific GPS positioning device; and then, carrying out statistical analysis on the acquired data to obtain a positioning value and distribution, a speed value and distribution of the specific GPS positioning equipment. And recording the position corresponding to the highway stake number, the positioning value and distribution of the GPS positioning equipment, and the speed value and distribution in a database. The positioning value and the distribution at the current moment are obtained by calculating the positioning value and the distribution, the speed value and the distribution at the previous moment, and data fusion is carried out on the positioning value and the distribution obtained by measuring at the current moment to obtain a more accurate positioning value and distribution at the current moment, so that more accurate vehicle positioning is realized; if the vehicle runs to the position of the whole kilometer, the fused data and the pile number position data are fused, and the effect of correction per kilometer is achieved.
In the present application, embodiments of a vehicle positioning apparatus are substantially similar to embodiments of a vehicle positioning method, and reference is made to the description of the embodiments of the vehicle positioning method for relevant points.
The embodiment of the application further provides a vehicle, which comprises the vehicle positioning device.
It is clear to a person skilled in the art that the solution according to the embodiments of the invention can be implemented by means of software and/or hardware. The "unit" and "module" in this specification refer to software and/or hardware that can perform a specific function independently or in cooperation with other components, where the hardware may be, for example, an FPGA (Field-Programmable Gate Array), an IC (Integrated Circuit), or the like.
Each processing unit and/or module according to the embodiments of the present invention may be implemented by an analog circuit that implements the functions described in the embodiments of the present invention, or may be implemented by software that executes the functions described in the embodiments of the present invention.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the vehicle positioning method described above. The computer-readable storage medium may include, but is not limited to, any type of disk including floppy disks, optical disks, DVD, CD-ROMs, microdrive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
The embodiment of the invention also provides electronic equipment which comprises a storage unit, a processing unit and a computer program which is stored on the storage unit and can run on the processing unit, and the steps of the vehicle positioning method are realized when the processing unit executes the program. In the embodiment of the present invention, the processing unit and the memory unit may be integrated into one device, or may be located in two devices.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only one logical functional division, and other division ways may be implemented in practice, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
All functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated into one unit; the integrated unit may be implemented in the form of hardware, or in the form of hardware plus a software functional unit.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made to the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. A vehicle positioning method, characterized by comprising the steps of:
determining a covariance matrix of initial speed and position of a road detection vehicle;
calculating to obtain prediction data of the current moment according to the covariance matrix of the speed and the position of the previous moment, wherein the prediction data comprises the prediction position and the speed information of the road detection vehicle and the covariance matrix of the position and the speed of the current moment; the prediction data at the initial moment is obtained by calculation according to the covariance matrix of the initial speed and position;
acquiring observation data of a current moment output by positioning equipment, wherein the observation data comprises observation position and speed information of the road detection vehicle;
fusing the prediction data and the observation data to obtain positioning information fused at the current moment and a covariance matrix of the position and the speed, wherein the fused positioning information comprises the position and the speed information of the road detection vehicle;
further comprising:
acquiring position information of a highway mileage pile;
when the road detection vehicle runs to a second road mileage stake, correcting the fusion positioning information of the road detection vehicle by using the position of the second road mileage stake;
further comprising: generating a plurality of road mileage piles between the second road mileage pile and a first road mileage pile, wherein the first road mileage pile is a previous road mileage pile of the second road mileage pile;
the method comprises the following steps that a vehicle starts to run from the position of a mileage stake mark of a certain highway, positioning fusion is carried out according to a fusion method, a current scene camera shoots the mileage stake mark, then the track between two mileage stake marks is corrected, and a hundred-meter stake mark is generated in the track; the number of the mileage stake marks generated in the track is determined according to the distance between the adjacent mileage stake marks shot by the foreground camera; and when the camera shoots a new mileage stake mark, the fusion times are cleared, and the fusion calculation is started again by taking the new mileage stake mark as an original point.
2. The vehicle localization method of claim 1, wherein determining the covariance matrix of the initial speed and position of the road sensing vehicle comprises:
collecting positioning information of a static state and a motion state of a road detection vehicle, wherein the positioning information comprises position and speed information of the road detection vehicle, and the road detection vehicle is provided with positioning equipment;
and carrying out statistical analysis on the positioning information of the static state and the motion state of the road detection vehicle to obtain a first covariance matrix, wherein the first covariance matrix is the covariance matrix of the initial speed and position of the road detection vehicle.
3. The vehicle positioning method according to claim 1, further comprising:
and displaying the fusion positioning information, the first road mileage pile, the second road mileage pile and a plurality of road mileage piles generated between the second road mileage pile and the first road mileage pile.
4. The vehicle positioning method according to any one of claims 1 to 3, characterized in that the positioning device is a GPS device.
5. A vehicle positioning device, comprising:
a determining unit for determining a covariance matrix of an initial speed and position of the road detection vehicle;
the calculation unit is used for calculating and obtaining prediction data of the current moment according to the covariance matrix of the speed and the position of the previous moment, wherein the prediction data comprises the prediction position and the speed information of the road detection vehicle and the covariance matrix of the position and the speed of the current moment; the prediction data at the initial moment is obtained by calculation according to the covariance matrix of the initial speed and position;
the acquisition unit is used for acquiring observation data of the current moment output by the positioning equipment, wherein the observation data comprises the observation position and the speed information of the road detection vehicle;
the fusion unit is used for fusing the prediction data and the observation data to obtain the fused positioning information at the current moment and a covariance matrix of the position and the speed, wherein the fused positioning information comprises the position and the speed information of the road detection vehicle;
further comprising:
acquiring position information of a highway mileage pile;
when the road detection vehicle runs to a second road mileage stake, correcting the fusion positioning information of the road detection vehicle by using the position of the second road mileage stake;
further comprising: generating a plurality of road mileage piles between the second road mileage pile and a first road mileage pile, wherein the first road mileage pile is a previous road mileage pile of the second road mileage pile;
the method comprises the following steps that a vehicle starts to run from the position of a mileage stake mark of a certain highway, positioning fusion is carried out according to a fusion method, a current scene camera shoots the mileage stake mark, then the track between two mileage stake marks is corrected, and a hundred-meter stake mark is generated in the track; the number of the mileage stake marks generated in the track is determined according to the distance between the adjacent mileage stake marks shot by the foreground camera; and when the camera shoots a new mileage stake number, the fusion times are cleared, and the fusion calculation is started again by taking the new mileage stake number as an original point.
6. The vehicle positioning apparatus according to claim 5, wherein the determination unit is configured to:
collecting positioning information of a stationary state and a moving state of a road detection vehicle, wherein the positioning information comprises position and speed information of the road detection vehicle, and the road detection vehicle is provided with positioning equipment;
and carrying out statistical analysis on the positioning information of the stationary state and the moving state of the road detection vehicle to obtain a first covariance matrix, wherein the first covariance matrix is a covariance matrix of the initial speed and position of the road detection vehicle.
7. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
8. An electronic device comprising a storage unit, a processing unit and a computer program stored on the storage unit and executable on the processing unit, characterized in that the steps of the method according to any of claims 1-4 are implemented when the program is executed by the processing unit.
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| CN112731456B (en) * | 2020-12-30 | 2021-08-31 | 上海同陆云交通科技有限公司 | Method for accurately calculating road pile number in reverse mode according to GNSS coordinates |
| CN112558125B (en) * | 2021-02-22 | 2021-05-25 | 腾讯科技（深圳）有限公司 | Vehicle positioning method, related device, equipment and storage medium |
| CN113257044B (en) * | 2021-07-09 | 2022-02-11 | 中航信移动科技有限公司 | Filtering method and device of ADS-B data, computer equipment and storage medium |
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| CN116772895B (en) * | 2023-08-25 | 2023-11-03 | 北京三岭基业科技发展有限公司 | Method and system for acquiring current running mileage and speed by rail transit |
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