CN118046890A - Vehicle positioning method and device and vehicle - Google Patents
Vehicle positioning method and device and vehicle Download PDFInfo
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Abstract
The disclosure relates to a vehicle positioning method, a device and a vehicle, wherein the method comprises the following steps: after the vehicle is electrified, acquiring first positioning information of the vehicle and second positioning information stored before last power-off; determining a target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between preset deviation thresholds; and determining the target positioning information of the vehicle according to the target positioning mode. According to the method and the device for positioning the vehicle, the deviation value between the first positioning information acquired after the vehicle is electrified and the second positioning information stored before the vehicle is electrified is used as the basis for selecting the target positioning mode, different positioning modes are selected under the condition that the vehicle positioning deviation is different, the problem that the positioning deviation is large after the vehicle is moved under the condition that the vehicle automatic parking system is not started can be effectively solved, and the positioning accuracy of the vehicle under a shielding scene is improved.
Description
Technical Field
The disclosure relates to the technical field of vehicle control, in particular to a vehicle positioning method and device and a vehicle.
Background
An automatic parking system is a driving assistance system that helps a driver identify available parking spaces and automatically drive a vehicle into the available parking spaces. The automatic parking adopts a visual sensor or an ultrasonic radar on the vehicle to sense the surrounding environment, plans a parking method and a path in a central processing unit, and controls the vehicle to automatically run into a parking space.
In the related art, under the condition of no global navigation satellite system (Global Navigation SATELLITE SYSTEM, GNSS) and RTK (Real-TIME KINEMATIC) fusion positioning, the automatic parking system of the vehicle generally adopts a laser radar to perform SLAM (simultaneous localization AND MAPPING, instant positioning and map construction) to build a parking lot map under the condition that the positioning of the parking lot depends on a sensor carried by the vehicle, and the position is recorded according to the position when the vehicle is parked in the parking lot and is used as an initial position of the vehicle in the SLAM map before the vehicle runs after power-on. And after the vehicle is powered down in a parking mode, if the vehicle is moved under the condition that the automatic parking system is not started, the vehicle position recorded by the automatic parking system before the power down is inconsistent with the actual position of the starting vehicle, so that the vehicle positioning deviation is larger.
Disclosure of Invention
The invention aims to provide a vehicle positioning method and device and a vehicle, and aims to solve the problem that vehicle positioning deviation is large due to the fact that the vehicle is moved under the condition that an automatic parking system is not started.
In order to achieve the above object, the present disclosure provides a vehicle positioning method, the method comprising:
after the vehicle is electrified, acquiring first positioning information of the vehicle and second positioning information stored before last power-off;
Determining a target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between preset deviation thresholds;
And determining the target positioning information of the vehicle according to the target positioning mode.
Optionally, the step of determining the target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between the preset deviation threshold value includes:
and when the deviation value is smaller than the deviation threshold value, determining that the target positioning mode is a first positioning mode, wherein the first positioning mode is a mode of determining the first positioning information as the target positioning information.
Optionally, the step of determining the target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between the preset deviation threshold value includes:
And under the condition that the deviation value is larger than the deviation threshold value, determining the target positioning mode as a second positioning mode, wherein the second positioning mode is a mode for determining the target positioning information according to the surrounding image of the vehicle and the first positioning information.
Optionally, the step of determining the target positioning information of the vehicle according to the target positioning mode includes:
acquiring the environment image under the condition that the target positioning mode is determined to be the second positioning mode;
Obtaining the number information of the parking space where the vehicle is located according to the environment image;
And obtaining the target positioning information according to the number information and the first positioning information.
Optionally, the step of obtaining the target positioning information according to the number information and the first positioning information includes:
acquiring real-time point cloud information of a vehicle according to the first positioning information;
according to the number information, determining the parking space point cloud information of the parking space where the vehicle is located;
And registering the real-time point cloud information and the parking space point cloud information by adopting an ICP algorithm to obtain the target positioning information.
Optionally, registering the real-time point cloud information and the parking space point cloud information by adopting an ICP algorithm to obtain the target positioning information, including:
initializing the value of a feature matrix of the real-time point cloud information according to the vehicle-site cloud information;
acquiring a target point meeting a distance condition between the target point and the real-time point cloud information from the parking spot cloud information;
according to the target point and the distance error between the points corresponding to the target point in the real-time point cloud information, performing iterative computation on the value of the feature matrix by adopting a least square method to obtain a target feature matrix;
And obtaining the target positioning information according to the target feature matrix.
Optionally, the step of obtaining the target positioning information according to the target feature matrix includes:
Solving the target feature matrix by adopting an SVD method to obtain a target rotation matrix;
And obtaining the target positioning information according to the target rotation matrix.
Optionally, after the step of determining the target positioning information of the vehicle according to the target positioning manner, the method further includes:
updating the actual position of the vehicle in the map according to the target positioning information;
and obtaining the running path of the vehicle according to the actual position and the target position input by the user.
In order to achieve the above object, the present disclosure also provides a vehicle positioning device including:
The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring first positioning information of a vehicle and second positioning information stored before last power-down after the vehicle is powered on;
The first determining module is used for determining a target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between preset deviation thresholds;
and the second determining module is used for determining the target positioning information of the vehicle according to the target positioning mode.
In order to achieve the above object, the present disclosure also provides a vehicle including:
a processor and a memory storing machine executable instructions executable by the processor for executing the machine executable instructions to implement the vehicle locating method described above.
According to the method, compared with the method that the positioning information stored before the power-down of the vehicle is directly used as the initial position of the vehicle driving in the prior art, the method and the device for determining the positioning information of the vehicle can effectively solve the problem that the positioning deviation is large after the vehicle is moved under the condition that an automatic parking system of the vehicle is not started, and improve the positioning accuracy of the vehicle under a shielding scene.
Additional features and advantages of the present disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings are included to provide a further understanding of the disclosure, and are incorporated in and constitute a part of this specification, illustrate the disclosure and together with the description serve to explain, but do not limit the disclosure. In the drawings:
FIG. 1 is a flow chart illustrating a method of vehicle positioning according to an exemplary embodiment.
FIG. 2 is a block diagram illustrating a vehicle locating apparatus according to an exemplary embodiment.
FIG. 3 is a functional block diagram of a vehicle, according to an exemplary embodiment.
Fig. 4 is a block diagram illustrating an apparatus for a vehicle positioning method according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
In the related art, the main function of SLAM is to make a robot complete positioning (Localization), mapping (Mapping) and path planning (Navigation) in an unknown environment. SLAM technology is widely applied to fields such as robot, unmanned aerial vehicle, unmanned, AR, VR, relies on the function such as autonomous positioning, map building, path planning that the sensor can realize the machine. The sensors of the vehicle may include lidar, millimeter wave radar, ultrasonic radar, and vision sensors.
The vehicle is generally positioned based on combined navigation when the vehicle is powered on, and the combined navigation refers to a navigation system which integrates various navigation devices and is controlled by a monitor and a computer. Most integrated navigation systems are based on inertial navigation systems, mainly because inertial navigation can provide a relatively large number of navigation parameters, and can also provide full-attitude information parameters. When a vehicle parks in a shielded parking lot, the combination navigation is poor in star searching performance, so that the accurate positioning position of the vehicle during signal shielding can not be provided. Under the condition that the environment where the vehicle is located by the laser SLAM technology, the vehicle locating deviation is larger due to poor robustness of the SLAM algorithm.
In addition, after the vehicle is parked in the parking space and powered down, the driver can finish the replacement of the parking space under the condition that the parking system is not normally started, and the position of the vehicle recorded by the automatic parking system before the power down is inconsistent with the actual position of the starting vehicle, so that the vehicle positioning deviation is larger.
Based on the above-mentioned problems, the embodiments of the present disclosure provide a concept for solving the above-mentioned problems, and determine a target positioning manner from different positioning manners based on a deviation value between first positioning information acquired after power-up and second positioning information stored before power-down of a vehicle last time and a preset deviation threshold value, so as to obtain target positioning information.
Embodiments of the present disclosure are specifically described below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a flowchart illustrating a vehicle positioning method according to an exemplary embodiment, and as shown in fig. 1, the vehicle positioning method includes:
S101, after the vehicle is electrified, acquiring first positioning information of the vehicle and second positioning information stored before the last power-down.
In a specific implementation process, the first positioning information is obtained by repositioning the vehicle after power-on, the second positioning information is stored before power-off after last driving of the vehicle, and the first positioning information and the second positioning information are positioned according to sensors on the vehicle and are displayed on a vehicle-mounted entertainment control system (HUT) of the vehicle through a map constructed by SLAM. The sensors of the vehicle may include inertial measurement units (inertial measurement unit, IMU), lidar, millimeter wave radar, ultrasonic radar, and camera devices, among others.
When the vehicle is parked, the driver opens an automatic parking system of the vehicle, and after the vehicle is parked, the automatic parking system records second positioning information of the vehicle before power-down and stores the second positioning information into the whole vehicle controller so as to determine the actual positioning position of the vehicle after the vehicle is powered on.
S102, determining a target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between preset deviation thresholds.
In a specific implementation process, the deviation value is obtained based on the first positioning information and the second positioning information, and the preset deviation threshold value can be determined according to the size of the vehicle and the error of the sensor. In general, the larger the vehicle size and the larger the sensor error, the larger the deviation value, and conversely the smaller the deviation value. In the existing positioning mode, for example, the initial position of the current running is determined directly according to the positioning information of the vehicle after the current power-up and the repositioning through the sensor and the integrated navigation, and in this case, the positioning information of the vehicle before the power-down can not be stored before the power-down of the vehicle. That is, in the conventional positioning method, the initial position of the vehicle in this time is generally determined according to the stored positioning information before the vehicle is powered down last time, or the initial position of the vehicle in this time is determined according to the positioning information acquired again after the vehicle is powered up.
The target positioning mode is a positioning mode determined from different positioning modes. In general, the positioning method may include a plurality of positioning methods, for example, in the case where the vehicle sensor includes a laser radar or a camera, the target positioning information may be obtained based on a SLAM algorithm. In the case where the vehicle sensor includes integrated navigation, the target positioning information may be obtained based on a track recurrence method.
In one embodiment, vehicle positioning can be realized based on data acquired by a plurality of vehicle sensors, so that the situation that self positioning cannot be performed due to failure of a single sensor can be avoided, and the robustness of positioning results is improved.
In the embodiment of the disclosure, the positioning manner may specifically be to determine the initial position of the vehicle according to the first positioning information determined after the vehicle is powered on, or may determine the initial position of the vehicle according to the current surrounding environment image of the vehicle and the positioning information stored before the vehicle is powered off.
S103, determining target positioning information of the vehicle according to the target positioning mode.
In a specific implementation process, the target positioning information is used for determining an initial position of the vehicle after power-on, and after determining a target positioning mode, the target positioning information of the vehicle can be obtained according to the target positioning mode. Wherein, under the condition that the deviation value between the first positioning information and the second positioning information is smaller than the preset deviation threshold value, the first positioning information is directly determined as target positioning information; or under the condition that the deviation value between the first positioning information and the second positioning information is larger than a preset deviation threshold value, identifying the number information of the current parking space of the vehicle according to the vehicle environment image, and carrying out matching operation according to the number information and the first positioning information to obtain updated target positioning information.
According to the method, compared with the method that the positioning information stored before the power-down of the vehicle is directly used as the initial position of the vehicle driving in the prior art, the method and the device for determining the positioning information of the vehicle can effectively solve the problem that the positioning deviation is large after the vehicle is moved under the condition that an automatic parking system of the vehicle is not started, and improve the positioning accuracy of the vehicle under a shielding scene.
In some embodiments, the step of determining the target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between the preset deviation threshold value includes:
When the deviation value is smaller than the deviation threshold value, the target positioning mode is determined to be a first positioning mode, and the first positioning mode is a mode of determining the first positioning information as the target positioning information.
In a specific implementation process, when the deviation value is smaller than the deviation threshold value, the deviation value is in a positioning deviation range, and it is determined that the vehicle does not move after the automatic parking system is closed or the situation that the position moving distance is too large does not occur, and the first positioning information acquired by the vehicle after the power-on can be used as the target positioning information of the current vehicle.
In some embodiments, the step of determining the target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between the preset deviation threshold value includes:
And when the deviation value is larger than the deviation threshold value, determining that the target positioning mode is a second positioning mode, wherein the second positioning mode is a mode for determining target positioning information according to the surrounding image of the vehicle and the first positioning information.
In a specific implementation process, under the condition that the deviation value is larger than the deviation threshold value, it is determined that the vehicle is subjected to larger displacement after the parking system is closed or larger deviation occurs in the positioning system, and due to poor robustness of the laser SLAM algorithm, the positioning performance is poor under the influence of a shielding scene of a parking lot, and the vehicle positioning deviation is larger and needs to be repositioned by directly adopting first positioning information as target positioning information. At this time, a visual sensor of the vehicle may be used to obtain an environmental image around the vehicle, and in general, the visual sensor is an imaging device of the vehicle, and the target positioning information of the vehicle is obtained by matching according to the environmental image and the first positioning information obtained by repositioning the vehicle after power-on.
In some embodiments, the step of determining target positioning information of the vehicle according to the target positioning mode includes:
Acquiring an environment image under the condition that the target positioning mode is determined to be the second positioning mode;
obtaining the number information of the parking space where the vehicle is located according to the environment image;
and obtaining target positioning information according to the number information and the first positioning information.
In a specific implementation process, after an environment image is acquired, according to an image recognition algorithm, the number information of the parking space in the environment image can be recognized, and because the map of the parking lot is constructed according to the SLAM before the vehicle is powered down last time, the number information can be matched and positioned in the constructed map under the condition that the image pickup device recognizes the number information of the current parking space of the vehicle, so that the target positioning information is obtained.
The image recognition algorithm is not particularly limited herein, and may be, for example, an image recognition algorithm based on a deep neural network, an image recognition algorithm based on a classifier, and an image recognition algorithm of a Support Vector Machine (SVM).
In some embodiments, the step of obtaining the target positioning information according to the number information and the first positioning information includes:
Acquiring real-time point cloud information of the vehicle according to the first positioning information;
according to the number information, determining parking space point cloud information of a parking space where the vehicle is located;
And registering the real-time point cloud information and the vehicle point cloud information by adopting an ICP algorithm to obtain target positioning information.
In a specific implementation process, the real-time point cloud information is coordinates of a point set for representing the position of the vehicle, which are obtained according to the first positioning information, and the parking space point cloud information is coordinates of a point set for representing the position of the parking space where the vehicle is located. The ICP algorithm is based on a data registration method and utilizes a closest point search method, so that the algorithm based on the free form curved surface is solved.
In some embodiments, registering the real-time point cloud information and the vehicle-site cloud information by adopting an ICP algorithm to obtain the target positioning information includes:
Initializing the value of a feature matrix of real-time point cloud information according to the vehicle point cloud information;
Acquiring a target point meeting a distance condition between the target point and the real-time point cloud information from the parking space point cloud information;
According to the target point and the distance error between the real-time point cloud information and the points corresponding to the target point, carrying out iterative computation on the value of the feature matrix by adopting a least square method to obtain a target feature matrix;
And obtaining target positioning information according to the target feature matrix.
In a specific implementation process, initializing a value of a feature matrix of the real-time point cloud is based on a coordinate system where the parking space point cloud information is located, and assigning a value to each coordinate point in the real-time point cloud information. The distance condition may be that a distance between points in the vehicle-site cloud information, which are acquired to be matched with the real-time point cloud information, is smaller than a preset distance threshold. Under the condition of initializing the values of the feature matrix of the real-time point cloud information, the points in the real-time point cloud information and the vehicle-site cloud information are matched, each point in the real-time point cloud information and the vehicle-site cloud information is a vector, and according to the distance between the matched points between the real-time point cloud information and the vehicle-site cloud information, the values of the feature matrix are iteratively updated by adopting a least square method so as to minimize an error function, and finally the optimized target feature matrix is obtained.
Specifically, the ICP algorithm steps may be:
(1) The method comprises the steps of obtaining a point set P i epsilon P in real-time point cloud information P;
(2) Finding out a corresponding point set Q i epsilon Q in the vehicle-site cloud information Q, so that ||qi-pi||=min;
(3) Calculating a feature matrix, which comprises a rotation matrix R and a translation matrix t, so that an error function is minimum;
(4) Performing rotation and translation transformation on the P i by using the rotation matrix R and the translation matrix t obtained in the step (3) to obtain a new corresponding point set P i'＝{pi'＝Rpi+t,pi epsilon P;
(5) According to Calculating the average distance between p i' and the corresponding point set q i;
(6) If d is less than a given threshold or greater than a preset maximum number of iterations, the iterative calculation is stopped. Otherwise, returning to the step (2) until the convergence condition is met.
In some embodiments, the step of obtaining target positioning information according to the target feature matrix includes:
solving the target feature matrix by adopting an SVD method to obtain a target rotation matrix;
And obtaining target positioning information according to the target rotation matrix.
In a specific implementation process, a method for solving a target feature matrix generally comprises an SVD method and a nonlinear optimization method, and the method adopts an SVD algorithm for solving, and comprises the following specific steps:
① Calculating the mass centers of the matching points in the real-time point cloud information and the vehicle point cloud information to obtain a point set with the mass centers removed;
② And calculating a 3X3 matrix H, wherein H=XY T, and X and Y are characteristic matrices of real-time point cloud information and vehicle point cloud information of which the centers are removed respectively.
③ SVD decomposition of H is performed on h=uΣv T, resulting in the target rotation matrix R *＝VUT.
In some embodiments, after the step of determining the target positioning information of the vehicle according to the target positioning manner, the method further comprises:
Updating the actual position of the vehicle in the map according to the target positioning information;
and obtaining the running path of the vehicle according to the actual position and the target position input by the user.
In a specific implementation process, after the target positioning information is obtained, the actual position of the vehicle is updated in the SLAM map of the vehicle, and the whole vehicle controller can calculate the running path of the vehicle according to the actual position and the target position input by the user.
Referring to fig. 2, fig. 2 is a block diagram of a vehicle positioning apparatus according to an exemplary embodiment, and as shown in fig. 2, a vehicle positioning apparatus 500 includes:
The acquiring module 520 is configured to acquire, after the vehicle is powered on, first positioning information of the vehicle and second positioning information stored before last power off;
a first determining module 530, configured to determine a target positioning mode from different positioning modes according to a magnitude relation between a deviation value between the first positioning information and the second positioning information and a preset deviation threshold;
The second determining module 540 is configured to determine target positioning information of the vehicle according to the target positioning manner.
In some embodiments, the first determination module 530 includes:
The first determining sub-module is used for determining that the target positioning mode is a first positioning mode when the deviation value is smaller than the deviation threshold value, and the first positioning mode is a mode of determining the first positioning information as the target positioning information.
In some embodiments, the first determination module 530 includes:
The second determining sub-module is used for determining that the target positioning mode is a second positioning mode under the condition that the deviation value is larger than the deviation threshold value, and the second positioning mode is a mode for determining the target positioning information according to the surrounding image of the vehicle and the first positioning information.
In some embodiments, the second determining module 540 includes:
The acquisition sub-module is used for acquiring an environment image under the condition that the target positioning mode is determined to be the second positioning mode;
the first obtaining submodule is used for obtaining the number information of the parking space where the vehicle is located according to the environment image;
And the second obtaining submodule is used for obtaining target positioning information according to the number information and the first positioning information.
In some embodiments, the second deriving submodule is specifically configured to:
Acquiring real-time point cloud information of the vehicle according to the first positioning information;
according to the number information, determining parking space point cloud information of a parking space where the vehicle is located;
And registering the real-time point cloud information and the vehicle point cloud information by adopting an ICP algorithm to obtain target positioning information.
In some embodiments, the second deriving submodule is specifically configured to:
Initializing the value of a feature matrix of real-time point cloud information according to the vehicle point cloud information;
Acquiring a target point meeting a distance condition between the target point and the real-time point cloud information from the parking space point cloud information;
According to the target point and the distance error between the real-time point cloud information and the points corresponding to the target point, carrying out iterative computation on the value of the feature matrix by adopting a least square method to obtain a target feature matrix;
And obtaining target positioning information according to the target feature matrix.
In some embodiments, the second deriving submodule is specifically configured to:
solving the target feature matrix by adopting an SVD method to obtain a target rotation matrix;
And obtaining target positioning information according to the target rotation matrix.
In some embodiments, the vehicle locating apparatus 500 further includes:
the updating module is used for updating the actual position of the vehicle in the map according to the target positioning information;
and the obtaining module is used for obtaining the driving path of the vehicle according to the actual position and the target position input by the user.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
In addition, to achieve the above object, an embodiment of the present disclosure also provides a vehicle including:
The vehicle positioning system comprises a processor and a memory, wherein the memory stores machine executable instructions capable of being executed by the processor, and the processor is used for executing the machine executable instructions to realize the vehicle positioning method.
Referring to fig. 3, fig. 3 is a functional block diagram of a vehicle 600 according to an exemplary embodiment. For example, vehicle 600 may be a hybrid vehicle, but may also be a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other type of vehicle. The vehicle 600 may be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle.
Referring to fig. 3, a vehicle 600 may include various subsystems, such as an infotainment system 610, a perception system 620, a decision control system 630, a drive system 640, and a computing platform 650. Wherein the vehicle 600 may also include more or fewer subsystems, and each subsystem may include multiple components. In addition, interconnections between each subsystem and between each component of the vehicle 600 may be achieved by wired or wireless means.
In some embodiments, the infotainment system 610 may include a communication system, an entertainment system, a navigation system, and the like.
The perception system 620 may include several sensors for sensing information of the environment surrounding the vehicle 600. For example, the sensing system 620 may include a global positioning system (which may be a GPS system, a beidou system, or other positioning system), an inertial measurement unit (inertial measurement unit, IMU), a lidar, millimeter wave radar, an ultrasonic radar, and a camera device.
Decision control system 630 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.
The drive system 640 may include components that provide powered movement of the vehicle 600. In one embodiment, the drive system 640 may include an engine, a torque source, a driveline, and wheels. The engine may be one or a combination of an internal combustion engine, an electric motor, an air compression engine. The engine is capable of converting torque provided by the torque source into mechanical torque.
Some or all of the functions of the vehicle 600 are controlled by the computing platform 650. The computing platform 650 may include at least one processor 651 and a first memory 652, the processor 651 may execute instructions 653 stored in the first memory 652.
The processor 651 may be any conventional processor, such as a commercially available CPU. The processor may also include, for example, an image processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable GATE ARRAY, FPGA), a System On Chip (SOC), an Application SPECIFIC INTEGRATED Circuit (ASIC), or a combination thereof.
The first memory 652 may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
In addition to instructions 653, the first memory 652 may also store data such as road maps, route information, the position, direction, speed, etc. of the vehicle. The data stored by the first memory 652 may be used by the computing platform 650.
In an embodiment of the present disclosure, the processor 651 may execute instructions 653 to perform all or part of the steps of the vehicle positioning method described above.
Referring to fig. 4, fig. 4 is a block diagram illustrating an apparatus 1900 for a vehicle positioning method according to an example embodiment. For example, the apparatus 1900 may be provided as a server. Referring to fig. 4, the apparatus 1900 includes a processing component 1922 that further includes one or more processors and memory resources represented by a second memory 1932 for storing instructions, such as applications, that can be executed by the processing component 1922. The application program stored in the second memory 1932 may include one or more modules each corresponding to a set of instructions. Further, processing component 1922 is configured to execute instructions to perform the vehicle locating method described above.
The apparatus 1900 may further comprise a power component 1926 configured to perform power management of the apparatus 1900, a wired or wireless network interface 1950 configured to connect the apparatus 1900 to a network, and an input/output interface 1958. The device 1900 may operate based on an operating system stored in a second memory 1932, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, or the like.
The present disclosure also provides a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the vehicle locating method provided by the present disclosure.
In another exemplary embodiment, a computer program product is also provided, which comprises a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-mentioned vehicle localization method when being executed by the programmable apparatus.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A vehicle positioning method, the method comprising:
after the vehicle is electrified, acquiring first positioning information of the vehicle and second positioning information stored before last power-off;
Determining a target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between preset deviation thresholds;
And determining the target positioning information of the vehicle according to the target positioning mode.
2. The method of claim 1, wherein the step of determining the target positioning mode from different positioning modes according to the magnitude relation between the deviation value between the first positioning information and the second positioning information and the preset deviation threshold value comprises:
and when the deviation value is smaller than the deviation threshold value, determining that the target positioning mode is a first positioning mode, wherein the first positioning mode is a mode of determining the first positioning information as the target positioning information.
3. The method of claim 1, wherein the step of determining the target positioning mode from different positioning modes according to the magnitude relation between the deviation value between the first positioning information and the second positioning information and the preset deviation threshold value comprises:
And under the condition that the deviation value is larger than the deviation threshold value, determining the target positioning mode as a second positioning mode, wherein the second positioning mode is a mode for determining the target positioning information according to the surrounding image of the vehicle and the first positioning information.
4. A method according to claim 3, wherein the step of determining target positioning information of the vehicle according to a target positioning method comprises:
acquiring the environment image under the condition that the target positioning mode is determined to be the second positioning mode;
Obtaining the number information of the parking space where the vehicle is located according to the environment image;
And obtaining the target positioning information according to the number information and the first positioning information.
5. The method of claim 4, wherein the step of obtaining the target positioning information based on the number information and the first positioning information comprises:
acquiring real-time point cloud information of a vehicle according to the first positioning information;
according to the number information, determining the parking space point cloud information of the parking space where the vehicle is located;
And registering the real-time point cloud information and the parking space point cloud information by adopting an ICP algorithm to obtain the target positioning information.
6. The method of claim 5, wherein the step of registering the real-time point cloud information and the parking spot cloud information using an ICP algorithm to obtain the target positioning information comprises:
initializing the value of a feature matrix of the real-time point cloud information according to the vehicle-site cloud information;
acquiring a target point meeting a distance condition between the target point and the real-time point cloud information from the parking spot cloud information;
according to the target point and the distance error between the points corresponding to the target point in the real-time point cloud information, performing iterative computation on the value of the feature matrix by adopting a least square method to obtain a target feature matrix;
And obtaining the target positioning information according to the target feature matrix.
7. The method of claim 6, wherein the step of obtaining the target positioning information based on the target feature matrix comprises:
Solving the target feature matrix by adopting an SVD method to obtain a target rotation matrix;
And obtaining the target positioning information according to the target rotation matrix.
8. The method according to claim 1, wherein after the step of determining target positioning information of the vehicle according to a target positioning manner, the method further comprises:
updating the actual position of the vehicle in the map according to the target positioning information;
and obtaining the running path of the vehicle according to the actual position and the target position input by the user.
9. A vehicle positioning device, the device comprising:
The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring first positioning information of a vehicle and second positioning information stored before last power-down after the vehicle is powered on;
The first determining module is used for determining a target positioning mode from different positioning modes according to the deviation value between the first positioning information and the second positioning information and the magnitude relation between preset deviation thresholds;
and the second determining module is used for determining the target positioning information of the vehicle according to the target positioning mode.
10. A vehicle, characterized in that the vehicle comprises:
a processor and a memory storing machine executable instructions executable by the processor for executing the machine executable instructions to implement the vehicle locating method of any of claims 1-8.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211399770.9A CN118046890A (en) | 2022-11-09 | 2022-11-09 | Vehicle positioning method and device and vehicle |
| PCT/CN2022/133346 WO2024098463A1 (en) | 2022-11-09 | 2022-11-21 | Vehicle localization method and apparatus, and vehicle |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202211399770.9A CN118046890A (en) | 2022-11-09 | 2022-11-09 | Vehicle positioning method and device and vehicle |
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| WO (1) | WO2024098463A1 (en) |
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| CN109547925A (en) * | 2018-12-07 | 2019-03-29 | 纳恩博（北京）科技有限公司 | Location updating method, the display methods of position and navigation routine, vehicle and system |
| CN110723151B (en) * | 2019-09-24 | 2021-01-29 | 华为技术有限公司 | Intelligent driving system initialization method and device |
| CN112835085B (en) * | 2020-07-09 | 2022-04-12 | 北京京东乾石科技有限公司 | Method and device for determining vehicle position |
| CN114516322B (en) * | 2022-02-24 | 2024-04-26 | 重庆长安汽车股份有限公司 | System and method for parking vehicle, vehicle and computer storage medium |
| CN114839659A (en) * | 2022-04-13 | 2022-08-02 | 合众新能源汽车有限公司 | Vehicle positioning method and device |
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