CN112629553A - Vehicle co-location method, system and device under intelligent network connection environment - Google Patents
Vehicle co-location method, system and device under intelligent network connection environment Download PDFInfo
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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
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
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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
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
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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
- G01S19/46—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being of a radio-wave signal type
Abstract
The invention relates to a vehicle cooperative positioning method, a system, a device and a computer readable storage medium under an intelligent network connection environment, wherein the method comprises the following steps: acquiring the distance between intelligent networking devices, and acquiring a preliminary estimated position of a vehicle to be positioned at the current moment and a preliminary estimated position of the vehicle to be positioned after a preset time according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle; acquiring another preliminary estimated position of the vehicle to be positioned after a preset time according to the preliminary estimated position of the vehicle to be positioned at the current moment and a dead reckoning algorithm; and carrying out data fusion on the preliminary estimation position and the other preliminary estimation position to obtain the final estimation position of the vehicle to be positioned after the preset time. The vehicle co-location method in the intelligent network connection environment improves the location precision of the vehicle.
Description
Technical Field
The present invention relates to the field of vehicle positioning technologies, and in particular, to a method, a system, an apparatus, and a computer-readable storage medium for vehicle co-positioning in an intelligent networking environment.
Background
With the rapid development of intelligent transportation systems and car networking technologies, the demand for improving the vehicle positioning accuracy by intelligent application based on the intelligent network networking technology is also increasingly urgent. Existing vehicle positioning methods include vehicle positioning by means of a reference position such as a lane line, a guardrail, and the like, and satellite positioning methods. For the former, the wireless signal is actually interfered by the environment outside the vehicle, the wireless signal has an attenuation phenomenon, and the strength of the signal received by the vehicle may be greatly different from a theoretical value, so that the positioning accuracy of the vehicle is not high. For the latter, during the positioning process, the pseudorange correction and the position correction need to be measured, and then the correction is compared and corrected with the measurement data of the user in real time, which depends on the statistical information in the measurement link, and meanwhile, due to the interference factor in the measurement process, a certain data error exists in the calculation, and the positioning accuracy of the vehicle is greatly reduced.
Disclosure of Invention
In view of the above, it is desirable to provide a method, a system, a device and a computer readable storage medium for vehicle co-location in an intelligent network environment, so as to solve the problem of low vehicle location accuracy in the prior art.
The invention provides a vehicle cooperative positioning method under an intelligent network connection environment, which comprises the following steps:
acquiring the distance between intelligent networking devices, and acquiring a preliminary estimated position of a vehicle to be positioned at the current moment and a preliminary estimated position of the vehicle to be positioned after a preset time according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle;
acquiring another preliminary estimated position of the vehicle to be positioned after a preset time according to the preliminary estimated position of the vehicle to be positioned at the current moment and a dead reckoning algorithm;
and carrying out data fusion on the preliminary estimation position and the other preliminary estimation position to obtain the final estimation position of the vehicle to be positioned after the preset time.
Further, the obtaining of the distance between the intelligent networking devices specifically includes:
the method comprises the steps of obtaining an RSS value in real time through communication between the OBU equipment and the RSU equipment, and estimating the distance between the two OBU equipment and the RSU equipment at the current moment according to the RSS valued，
Wherein, in the step (A),
in order to be the RSS value,
is gaussian ambient noise.
Further, obtaining a preliminary estimated position of the vehicle to be positioned at the current moment according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle, specifically comprising:
obtaining the current moment according to the distance between the intelligent network equipment, the longitude and latitude information of the vehicle and a position preliminary estimation formulatPreliminary estimated position of a vehicle to be positioned
(ii) a The preliminary location estimation formula
Wherein the content of the first and second substances,
，
is the position coordinates of the RSU device,
for the OBU device GPS location coordinates,
as the current timetDistance between two OBU devices and an RSU device.
Further, according to the preliminary estimated position of the vehicle to be positioned at the current moment and a dead reckoning algorithm, another preliminary estimated position of the vehicle to be positioned after a predetermined time is obtained, which specifically comprises:
obtaining the speed, course angle and acceleration of the vehicle to be positioned through the OBU equipment according totThe vehicle initial estimation position, the dead reckoning algorithm formula, the vehicle speed, the course angle and the acceleration at the moment are obtained for a preset time
Another preliminary estimated position of the vehicle to be located at the time.
Further, the dead reckoning algorithm is formulated as
Wherein, in the step (A),
，
after a predetermined time
Another preliminary estimated position of the vehicle to be located at the time,
as the current timetThe preliminary estimated position of the vehicle to be located,
、
、
respectively, vehicle speed, course angle and acceleration.
Further, performing data fusion on the preliminary estimated position and the other preliminary estimated position to obtain a final estimated position of the vehicle to be positioned after the predetermined time, specifically comprising:
performing data fusion on the preliminary estimated position and the other preliminary estimated position by using a data fusion formula to obtain a final estimated position of the vehicle to be positioned after the preset time; the data fusion formula is
Wherein, in the step (A),
for a preliminary estimated position of the vehicle to be located after a predetermined time,
another preliminary estimate of the position of the vehicle to be located after a predetermined time,
are fusion coefficients.
Further, the vehicle co-location method under the intelligent networking environment further comprises the steps of after obtaining the preliminary estimation position of the vehicle to be located at the current moment and the preliminary estimation position of the vehicle to be located after the preset time, respectively carrying out Bayesian filtering processing on the preliminary estimation position of the vehicle to be located at the current moment and the preliminary estimation position of the vehicle to be located after the preset time, and obtaining the preliminary estimation position of the vehicle to be located at the current moment after the Bayesian filtering processing and the preliminary estimation position of the vehicle to be located after the preset time after the Bayesian filtering processing.
The invention also provides a vehicle cooperative positioning system under the intelligent network connection environment, which comprises a first preliminary estimation module, a second preliminary estimation module and a position determination module;
the first preliminary estimation module is used for acquiring the distance between the intelligent networking devices and acquiring a preliminary estimation position of a vehicle to be positioned at the current moment and a preliminary estimation position of the vehicle to be positioned after a preset time according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle;
the second preliminary estimation module is used for acquiring another preliminary estimation position of the vehicle to be positioned after the preset time according to the preliminary estimation position of the vehicle to be positioned at the current moment and a dead reckoning algorithm;
and the position determining module is used for carrying out data fusion on the preliminary estimated position and the other preliminary estimated position to obtain the final estimated position of the vehicle to be positioned after the preset time.
The invention also provides a vehicle co-location device under the intelligent network connection environment, which comprises a processor and a memory, wherein the memory is stored with a computer program, and when the computer program is executed by the processor, the vehicle co-location method under the intelligent network connection environment is realized according to any technical scheme.
The invention also provides a computer readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for the cooperative positioning of the vehicles in the intelligent network connection environment is realized.
Compared with the prior art, the invention has the beneficial effects that: acquiring a preliminary estimation position of a vehicle to be positioned at the current moment and a preliminary estimation position of the vehicle to be positioned after a preset time according to the distance between the intelligent network connection devices and the longitude and latitude information of the vehicle; acquiring another preliminary estimated position of the vehicle to be positioned after a preset time according to the preliminary estimated position of the vehicle to be positioned at the current moment and a dead reckoning algorithm; performing data fusion on the preliminary estimated position and the other preliminary estimated position to obtain a final estimated position of the vehicle to be positioned after the preset time; the positioning accuracy of the vehicle is improved.
Drawings
FIG. 1 is a schematic flow chart of a vehicle co-location method in an intelligent network environment according to the present invention;
FIG. 2 is a calculation provided by the present inventiontSchematic diagram of a method of estimating a location at a time;
fig. 3 is a block diagram of a vehicle cooperative positioning system in an intelligent network environment according to the present invention.
Detailed Description
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate preferred embodiments of the invention and together with the description, serve to explain the principles of the invention and not to limit the scope of the invention.
Example 1
The embodiment of the invention provides a vehicle co-location method in an intelligent network connection environment, which has a flow diagram, as shown in fig. 1, and comprises the following steps:
s1, obtaining the distance between the intelligent networking devices, and obtaining the preliminary estimation position of the vehicle to be positioned at the current moment and the preliminary estimation position of the vehicle to be positioned after the preset time according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle;
s2, acquiring another preliminary estimation position of the vehicle to be positioned after the preset time according to the preliminary estimation position of the vehicle to be positioned at the current moment and a dead reckoning algorithm;
and S3, carrying out data fusion on the preliminary estimation position and the other preliminary estimation position to obtain the final estimation position of the vehicle to be positioned after the preset time.
Preferably, the acquiring the distance between the intelligent networking devices specifically includes:
the method comprises the steps of obtaining an RSS value in real time through communication between the OBU equipment and the RSU equipment, and estimating the distance between the two OBU equipment and the RSU equipment at the current moment according to the RSS valued，
Wherein, in the step (A),
in order to be the RSS value,
is gaussian ambient noise.
In a specific embodiment, the path loss model is subjected to fitting calibration by collecting RSS (Received Signal Strength) values fusing an On-Board Unit (On-Board Unit) device and an intelligent road Side Unit (rsu) (road Side Unit) device of a network connection vehicle under the condition of different communication distances, so that the relation between the RSS value and the propagation distance is obtained according to the following formula
Wherein the content of the first and second substances,
in order to be the RSS value,
the intelligent road side equipment RSU equipment is distributed at an urban road intersection or a road section for Gaussian environmental noise;
the distance between two intelligent networking devices at the current moment can be estimated through the RSS value obtained in real time through communication between the OBU device and the RSU deviced，
Preferably, the obtaining of the preliminary estimated position of the vehicle to be positioned at the current moment according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle specifically includes:
obtaining the current moment according to the distance between the intelligent network equipment, the longitude and latitude information of the vehicle and a position preliminary estimation formulatPreliminary estimated position of a vehicle to be positioned
(ii) a The preliminary location estimation formula
Wherein the content of the first and second substances,
，
is the position coordinates of the RSU device,
for the OBU device GPS location coordinates,
as the current timetDistance between two OBU devices and an RSU device.
In one embodiment, computingtEstimated position of time of day
A schematic of the process, as shown in fig. 2,
、
for GPS position coordinates of different locations, the precise position coordinates of the RSU are
，tThe GPS position coordinate (namely the longitude and latitude information of the vehicle given by the GPS module of the OBU device) at the moment is
When the OBU receives RSA or MAP messages from the RSU, the distance between the OBU and the RSU equipment at the moment can be calculated through the RSS value of the signal
Distance between devices by using RSU accurate coordinate position as center of circle
If the radius is a circle, the vehicle should be at a certain position on the circle, and the estimated position of the vehicle can be determined by combining the direction of the vehicle position point relative to the RSU device and the intersection point of a ray and the circle.
According totDistance between OBU device and RSU device at time
In RSU device coordinates
Is used as the center of a circle,
making a circle with a radius, the formula is as follows
According to GPS coordinates
And the RSU coordinates can determine a straight line, the formula is as follows
The formula (3) and the formula (4) are combined, and the vehicle can be obtained by solving the equation settPreliminary estimate of location of time of day
As shown in formula 5:
preferably, after the preliminary estimated position of the vehicle to be positioned at the current moment and the preliminary estimated position of the vehicle to be positioned after the preset time are obtained, bayesian filtering is respectively performed on the preliminary estimated position of the vehicle to be positioned at the current moment and the preliminary estimated position of the vehicle to be positioned after the preset time, so that the preliminary estimated position of the vehicle to be positioned at the current moment after the bayesian filtering and the preliminary estimated position of the vehicle to be positioned after the preset time are obtained.
In one embodiment, a vehicle is obtainedtPreliminary estimate of location of time of day
Bayesian filtering is carried out, and errors caused by serious fluctuation of RSS data are reduced; suppose that
Indicating a measurementkA set of one or more coordinate values,
measured values for respective coordinates;
is shown inkIn the case of a secondary position estimate, the node to be positioned is at
A probability of a location;
then it is a priori probability, expressed at a known time
In the case of secondary position estimation, i.e. unknownkThe prediction probability of the position point to be positioned under the condition of the secondary position estimation result;
for posterior probability, indicating that the point at which the vehicle is to be located is at the position
Then, a set of position estimates is obtained
The probability of (c).
Because the noise probability distributions of the RSS data and the GPS position are in accordance with the Gaussian probability distribution, the prior probability, the posterior probability and the like are in accordance with the Gaussian probability distribution, and under the premise that the position estimation values are independent from each other, a formula (6) is established according to the Bayesian theory
First, the Bayesian prior probability needs to be determined
Here is provided with
，
Then the prior probability can be calculated by equation (7):
in the formula (I), the compound is shown in the specification,
is a firstkEstimating the distance from the secondary position to the RSU equipment;qdistance of vehicle from RSU equipment
；
To measure the uncertainty variance of the distance.
Based on the above information, the probability distribution function of the estimated coordinates of the vehicle to be positioned can be calculated by bayesian posterior probability, as shown in equations (8) and (9):
by calculation
Estimated coordinates of the position of the vehicle having the maximum value astVehicle position estimation coordinates of time of day
(ii) a Since the exponential function is monotonous, it is only necessary to be able to make
Position coordinates with maximum value
That is, more accurate solution can be achievedP 1And (4) coordinates. The solving process is as follows: hypothesis function
In the near fieldSimilar position point
Taking a maximum value, ordering the target function
Non-linear factor in
And at an approximate location point
Taking Taylor expansion, linearly approximating the part of non-linear part, and making the process as shown in formulas (10) - (13)
Order to
，
，
Will contain a non-linear factor
Approximating a linear function, as shown in equation (14),
order to
In that
Where the first derivative is 0, then there is equation (15),
the linear equation system of the above formula is solved to obtain the preliminary estimation position coordinate processed by the Bayesian filtering
As shown in the formula (16),
at this time, let the coordinates processed by the Bayesian filtering
As vehiclestPreliminary estimate of location of time of day
，
、
Are parameter values. By means of Bayesian filteringWave processing may improve the accuracy of the position estimate.
In one embodiment, since the frequency of the acquired data by the GPS module of the on-board OBU is 10 Hz, the OBU can acquire the coordinates of the next GPS position after 100 ms (i.e. the preset time), and the distance between the OBU device and the RSU device at this time can be estimated by implementing the acquired RSS data
Then pass through
After a time of (100 ms) the time,
preliminary vehicle position estimate location at time of day
And the distance between the intelligent networking devices and the longitude and latitude information of the vehicle can be obtained.
Preferably, the method for obtaining another preliminary estimated position of the vehicle to be positioned after the predetermined time according to the preliminary estimated position of the vehicle to be positioned at the current moment and a dead reckoning algorithm specifically includes:
obtaining the speed, course angle and acceleration of the vehicle to be positioned through the OBU equipment according totThe vehicle initial estimation position, the dead reckoning algorithm formula, the vehicle speed, the course angle and the acceleration at the moment are obtained for a preset time
Another preliminary estimated position of the vehicle to be located at the time.
Preferably, the dead reckoning algorithm formula is
Wherein, in the step (A),
，
after a predetermined time
Another preliminary estimated position of the vehicle to be located at the time,
as the current timetThe preliminary estimated position of the vehicle to be located,
、
、
respectively, vehicle speed, course angle and acceleration.
In one embodiment, vehicle status data is obtained via a vehicle CAN bus based on OBU equipment, the vehicle status data including vehicle speed
Angle of course
And acceleration
Can be based ontVehicle preliminary positioning position at time
And dead reckoning to obtain
Time of day, another position estimate of the vehicle
。
In the implementation, assuming that the vehicle travels straight in the period, the travel distance can be calculated by the formula (17)
Another position estimation coordinate of the vehicle
Can be obtained by calculation of the formula (18)
Preferably, the data fusion is performed on the preliminary estimated position and the other preliminary estimated position to obtain a final estimated position of the vehicle to be positioned after the predetermined time, and specifically includes:
performing data fusion on the preliminary estimated position and the other preliminary estimated position by using a data fusion formula to obtain a final estimated position of the vehicle to be positioned after the preset time; the data fusion formula is
Wherein, in the step (A),
for a preliminary estimated position of the vehicle to be located after a predetermined time,
another preliminary estimate of the position of the vehicle to be located after a predetermined time,
are fusion coefficients.
In a specific embodiment, in
At that moment, the preliminary position estimates of two vehicles to be positioned are obtained, respectively
And
and performing data fusion on the two initial estimation positions to obtain final vehicle positioning coordinates
。
During specific implementation, the final positioning coordinates of the vehicle are fused with the two obtained initial positioning coordinates by using a weighted average method, so that the vehicle position positioning with higher precision is obtained. Final vehicle location coordinates
The calculation of (d) is shown below.
Example 2
The embodiment of the invention provides a vehicle cooperative positioning system in an intelligent network connection environment, which has a structural block diagram, as shown in fig. 3, and comprises a first preliminary estimation module 1, a second preliminary estimation module 2 and a position determination module 3;
the first preliminary estimation module 1 is used for acquiring the distance between the intelligent networking devices, and acquiring a preliminary estimation position of a vehicle to be positioned at the current moment and a preliminary estimation position of the vehicle to be positioned after a preset time according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle;
the second preliminary estimation module 2 is used for acquiring another preliminary estimation position of the vehicle to be positioned after a preset time according to the preliminary estimation position of the vehicle to be positioned at the current moment and a dead reckoning algorithm;
and the position determining module 3 is used for carrying out data fusion on the preliminary estimated position and the other preliminary estimated position to obtain the final estimated position of the vehicle to be positioned after the preset time.
Example 3
The embodiment of the invention provides an intelligent network connection environment vehicle cooperative positioning device, which comprises a processor and a memory, wherein the memory is stored with a computer program, and when the computer program is executed by the processor, the intelligent network connection environment vehicle cooperative positioning method in the embodiment 1 is realized.
Example 4
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for cooperative vehicle positioning in an intelligent network connection environment as described in embodiment 1.
The invention discloses a vehicle cooperative positioning method, a system, a device and a computer readable storage medium under an intelligent network connection environment.A primary estimated position of a vehicle to be positioned at the current moment and a primary estimated position of the vehicle to be positioned after preset time are obtained by obtaining the distance between intelligent network connection devices and according to the distance between the intelligent network connection devices and the longitude and latitude information of the vehicle; acquiring another preliminary estimated position of the vehicle to be positioned after a preset time according to the preliminary estimated position of the vehicle to be positioned at the current moment and a dead reckoning algorithm; performing data fusion on the preliminary estimated position and the other preliminary estimated position to obtain a final estimated position of the vehicle to be positioned after the preset time; the positioning accuracy of the vehicle is improved.
According to the invention, by using the intelligent road side equipment arranged at the intersection or the road section of the urban road, only 1 RSU equipment is needed for assistance, and on the premise of not increasing additional positioning/distance measuring equipment, through fusing the GPS module data of the vehicle-mounted OBU of the internet and the received signal strength data of the communication between the OBU and the RSU, the cost for realizing the positioning method is greatly saved, and the positioning precision of the internet vehicle in the environment of the internet is improved.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (10)
1. A vehicle cooperative positioning method under an intelligent network connection environment is characterized by comprising the following steps:
acquiring the distance between intelligent networking devices, and acquiring a preliminary estimated position of a vehicle to be positioned at the current moment and a preliminary estimated position of the vehicle to be positioned after a preset time according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle;
acquiring another preliminary estimated position of the vehicle to be positioned after a preset time according to the preliminary estimated position of the vehicle to be positioned at the current moment and a dead reckoning algorithm;
and carrying out data fusion on the preliminary estimation position and the other preliminary estimation position to obtain the final estimation position of the vehicle to be positioned after the preset time.
2. The method as claimed in claim 1, wherein the obtaining of the distance between the intelligent networking devices specifically comprises:
the method comprises the steps of obtaining an RSS value in real time through communication between the OBU equipment and the RSU equipment, and estimating the distance between the two OBU equipment and the RSU equipment at the current moment according to the RSS valued，
Wherein, in the step (A),
RSS value, gaussian ambient noise.
3. The method as claimed in claim 1, wherein the step of obtaining the preliminary estimated location of the vehicle to be located at the current time according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle comprises:
obtaining the current moment according to the distance between the intelligent network equipment, the longitude and latitude information of the vehicle and a position preliminary estimation formulatPreliminary estimated position of a vehicle to be positioned
(ii) a The preliminary location estimation formula
Wherein the content of the first and second substances,
，
is the position coordinates of the RSU device,
for the OBU device GPS location coordinates,
as the current timetDistance between two OBU devices and an RSU device.
4. The method as claimed in claim 1, wherein the step of obtaining another preliminary estimated position of the vehicle to be located after a predetermined time according to the preliminary estimated position of the vehicle to be located at the current time and a dead reckoning algorithm comprises:
obtaining the speed, course angle and acceleration of the vehicle to be positioned through the OBU equipment according totThe vehicle preliminary estimation position, the dead reckoning algorithm formula, the vehicle speed, the course angle and the acceleration at the moment are obtained to obtain the presetAfter a period of time
Another preliminary estimated position of the vehicle to be located at the time.
5. The method as claimed in claim 4, wherein the dead reckoning algorithm is expressed as
Wherein, in the step (A),
，
after a predetermined time
Another preliminary estimated position of the vehicle to be located at the time,
as the current timetThe preliminary estimated position of the vehicle to be located,
、
、
respectively, vehicle speed, course angle and acceleration.
6. The method as claimed in claim 1, wherein the step of performing data fusion between the preliminary estimated position and another preliminary estimated position to obtain a final estimated position of the vehicle to be located after a predetermined time includes:
performing data fusion on the preliminary estimated position and the other preliminary estimated position by using a data fusion formula to obtain a final estimated position of the vehicle to be positioned after the preset time; the data fusion formula is
Wherein, in the step (A),
for a preliminary estimated position of the vehicle to be located after a predetermined time,
another preliminary estimate of the position of the vehicle to be located after a predetermined time,
are fusion coefficients.
7. The method as claimed in claim 1, further comprising, after obtaining the preliminary estimated position of the vehicle to be positioned at the current time and the preliminary estimated position of the vehicle to be positioned after the predetermined time, performing bayesian filtering on the preliminary estimated position of the vehicle to be positioned at the current time and the preliminary estimated position of the vehicle to be positioned after the predetermined time, respectively, to obtain the preliminary estimated position of the vehicle to be positioned at the current time after the bayesian filtering and the preliminary estimated position of the vehicle to be positioned after the predetermined time after the bayesian filtering.
8. A vehicle cooperative positioning system under an intelligent network connection environment is characterized by comprising a first preliminary estimation module, a second preliminary estimation module and a position determination module;
the first preliminary estimation module is used for acquiring the distance between the intelligent networking devices and acquiring a preliminary estimation position of a vehicle to be positioned at the current moment and a preliminary estimation position of the vehicle to be positioned after a preset time according to the distance between the intelligent networking devices and the longitude and latitude information of the vehicle;
the second preliminary estimation module is used for acquiring another preliminary estimation position of the vehicle to be positioned after the preset time according to the preliminary estimation position of the vehicle to be positioned at the current moment and a dead reckoning algorithm;
and the position determining module is used for carrying out data fusion on the preliminary estimated position and the other preliminary estimated position to obtain the final estimated position of the vehicle to be positioned after the preset time.
9. An apparatus for co-locating vehicles in an intelligent network connection environment, comprising a processor and a memory, wherein the memory stores a computer program, and the computer program, when executed by the processor, implements the method for co-locating vehicles in an intelligent network connection environment according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method for co-locating vehicles in an intelligent network-connected environment according to any one of claims 1 to 7.
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Denomination of invention: A method, system, and device for vehicle collaborative positioning in an intelligent networked environment Effective date of registration: 20231010 Granted publication date: 20210615 Pledgee: Bank of China Limited Wuhan Economic and Technological Development Zone sub branch Pledgor: ISMARTWAYS (WUHAN) TECHNOLOGY Co.,Ltd. Registration number: Y2023980060478 |