Vehicle positioning method, device, electronic device and computer-readable storage medium

Abstract

The present application relates to a vehicle positioning method, device, electronic device and computer-readable storage medium. The method includes: when the signal strength of the on-board navigation device does not meet the positioning conditions, performing track deduction on the vehicle; when the track deduction meets the deduction conditions and the signal of the on-board navigation device has not yet recovered, obtaining the position information and chassis information of the vehicle in the track deduction, and determining the virtual observation position of the vehicle; combining with a preset filtering algorithm, calculating the real-time position of the vehicle. The embodiment of the present application performs track deduction on the driving trajectory of the vehicle when the signal strength of the on-board navigation device does not meet the positioning conditions, and records the process of track deduction. By setting restriction conditions for the track deduction and combining the position information of the track deduction and the chassis information of the vehicle with a filtering algorithm to calculate the real-time position of the vehicle, it can effectively reduce the error accumulation caused by the long track deduction time and prevent large distance jumps in vehicle positioning.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a vehicle positioning method, device, electronic device, and computer-readable storage medium. Background Art

[0002] With the advancement of technology, autonomous driving has gradually entered people's lives. In the near future, autonomous driving vehicles will become another mode of transportation for people.

[0003] In relevant technical solutions, for autonomous driving vehicles, when the vehicle needs to be positioned, a combined navigation module that integrates the global positioning navigation system and the inertial measurement unit is generally used to position the vehicle. When the signal of the global positioning navigation system is interfered with, resulting in the inability of the global positioning navigation system to accurately locate the vehicle, the inertial measurement unit will be used to deduce the vehicle's track. However, there are errors in the track deduction. When the track deduction time is too long, the accumulated error will become larger and larger. When the signal of the global positioning navigation system returns to normal, it will cause a large distance jump in the position display, affecting the navigation effect. Summary of the Invention

[0004] In order to solve or partially solve the problems existing in the related art, the present application provides a vehicle positioning method, device, electronic device and computer-readable storage medium, which can fuse the position information of the track deduction and the chassis information of the vehicle when the signal of the vehicle's global positioning navigation system is interfered with, calculate the position of the vehicle, ensure the accuracy of the vehicle positioning, and when the global positioning navigation signal returns to normal, ensure that the vehicle positioning will not jump over a large distance.

[0005] A first aspect of the present application provides a vehicle positioning method, comprising:

[0006] When the signal strength of the vehicle navigation device does not meet the preset positioning conditions, the vehicle's driving trajectory is deduced;

[0007] Acquiring position information and chassis information of the vehicle during track deduction, and determining a virtual observation position of the vehicle based on the position information and chassis information when the track deduction satisfies a preset deduction condition and the signal of the on-board navigation device has not yet been restored;

[0008] Based on the virtual observation position and in combination with a preset filtering algorithm, the real-time position of the vehicle is calculated.

[0009] As a possible implementation of the present application, in this implementation,

[0010] The performing trajectory deduction on the vehicle's driving trajectory includes:

[0011] Obtaining vehicle inertial measurement values based on an onboard inertial measurement unit;

[0012] Calculating the acceleration and angular velocity of the vehicle and the geomagnetism of the location of the vehicle based on the inertial measurement value;

[0013] The track information of the vehicle is calculated by combining the acceleration and angular velocity of the vehicle and the geomagnetism of the location of the vehicle, wherein the track information of the vehicle includes the speed information and virtual observation position information of the vehicle.

[0014] As an embodiment of the present application, in this embodiment,

[0015] The preset deduction conditions include one or more of the following:

[0016] The deduction duration of the track deduction reaches a first preset duration threshold;

[0017] The travel distance of the vehicle reaches a preset distance threshold.

[0018] As an embodiment of the present application, in this embodiment, obtaining chassis information of the vehicle includes:

[0019] The chassis speed and the vehicle yaw rate of the vehicle are obtained through the vehicle controller local area network. As an embodiment of the present application, in this embodiment,

[0020] The preset filtering algorithm is a Kalman filtering algorithm, and determining the virtual observation position of the vehicle based on the position information and the chassis information includes:

[0021] Acquiring inertial measurement values of the vehicle based on an on-board inertial measurement unit, wherein the inertial measurement values include acceleration and angular velocity of the vehicle and geomagnetism at a location of the vehicle;

[0022] constructing a state vector of the vehicle based on the angular velocity and the geomagnetic field of the location of the vehicle, and updating the state vector using the Kalman filter algorithm to determine the Euler angle of the vehicle;

[0023] determining a real-time speed of the vehicle based on the acceleration;

[0024] The virtual observation position of the vehicle is calculated based on the Euler angle and real-time speed of the vehicle and the duration of the track deduction.

[0025] As an embodiment of the present application, in this embodiment,

[0026] Based on the virtual observation position, combined with a preset filtering algorithm, the real-time position of the vehicle is calculated, including:

[0027] Calculating an error coefficient of the chassis velocity of the vehicle and an error coefficient of the yaw rate of the vehicle based on the velocity information and Euler angles obtained by the vehicle-mounted inertial measurement unit within the deduction conditions;

[0028] Calculating a velocity observation value obtained through trajectory extrapolation based on an error coefficient of the chassis velocity, calculating an angular velocity observation value obtained through trajectory extrapolation based on an error coefficient of the vehicle yaw angular velocity, and calculating a virtual observation value of the vehicle position by combining the velocity observation value and the angular velocity observation value;

[0029] The filter updates the observation of the vehicle position based on the virtual observation value to determine the real-time position of the vehicle.

[0030] As an embodiment of the present application, in this embodiment,

[0031] After the vehicle trajectory is deduced, the method further includes:

[0032] When the signal of the vehicle navigation device passes the card square detection within a preset time period, the track deduction of the vehicle's driving trajectory is stopped and the vehicle navigation device is used to navigate the vehicle;

[0033] When the signal of the vehicle navigation device does not pass the card square detection within the preset time period, the card square detection of the signal of the vehicle navigation device is stopped until it is determined that the signal of the vehicle navigation device meets the preset positioning conditions, and the vehicle navigation device is used to navigate the vehicle.

[0034] A second aspect of the present application provides a vehicle positioning device, the vehicle positioning device comprising:

[0035] A track deduction module is used to perform track deduction on the vehicle's driving trajectory when the signal strength of the vehicle navigation device does not meet the preset positioning conditions;

[0036] an information acquisition module, configured to acquire position information and chassis information of the vehicle during track deduction, and determine a virtual observation position of the vehicle based on the position information and chassis information when the track deduction satisfies a preset deduction condition and the signal of the on-board navigation device has not yet been restored;

[0037] A real-time positioning module is used to calculate the real-time position of the vehicle based on the virtual observation position in combination with a preset filtering algorithm.

[0038] A third aspect of the present application provides an electronic device, including:

[0039] processor; and

[0040] The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is caused to execute the vehicle positioning method as described above.

[0041] A fourth aspect of the present application provides a computer-readable storage medium having executable code stored thereon. When the executable code is executed by a processor of an electronic device, the processor is caused to execute the vehicle positioning method as described above.

[0042] The technical solution provided by the present application may include the following beneficial effects: the embodiment of the present application performs track deduction on the vehicle's driving trajectory and records the process of track deduction when the signal strength of the on-board navigation device does not meet the positioning conditions. When the track deduction reaches a preset restriction condition, the position information of the track deduction and the chassis information of the vehicle are obtained, and the real-time position of the vehicle is calculated using a filtering algorithm based on the position information and chassis information. By setting restriction conditions for the track deduction and using a filtering algorithm to calculate the real-time position of the vehicle in combination with the position information of the track deduction and the chassis information of the vehicle, the error accumulation caused by the long track deduction time can be effectively prevented, the accuracy of the vehicle positioning can be determined, and large-distance jumps in the vehicle positioning can be prevented.

[0043] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The above and other objects, features and advantages of the present application will become more apparent by describing in more detail exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0045] Figure 1 This is a flow chart of a vehicle positioning method shown in an embodiment of the present application;

[0046] Figure 2 1 is a flow chart of a track deduction method shown in an embodiment of the present application;

[0047] Figure 3 1 is a flow chart of a method for determining a virtual observation value shown in an embodiment of the present application;

[0048] Figure 4 1 is a flow chart of a method for determining a real-time position according to an embodiment of the present application;

[0049] Figure 5 This is a flow chart of a method for restoring vehicle navigation according to an embodiment of the present application;

[0050] Figure 61 is a schematic structural diagram of a vehicle positioning device according to an embodiment of the present application;

[0051] Figure 7 It is a structural diagram of an electronic device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0052] The following describes embodiments of the present application in more detail with reference to the accompanying drawings. Although the accompanying drawings illustrate embodiments of the present application, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. Rather, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0053] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. As used in this application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0054] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0055] In relevant technical solutions, for autonomous driving vehicles, when the vehicle needs to be positioned, a combined navigation module that integrates the global positioning navigation system and the inertial measurement unit is generally used to position the vehicle. When the signal of the global positioning navigation system is interfered with, resulting in the inability of the global positioning navigation system to accurately locate the vehicle, the inertial measurement unit will be used to deduce the vehicle's track. However, there are errors in the track deduction. When the track deduction time is too long, the accumulated error will become larger and larger. When the signal of the global positioning navigation system returns to normal, it will cause a large distance jump in the position display, affecting the navigation effect.

[0056] To address the above-mentioned issues, an embodiment of the present application provides a vehicle positioning method that can fuse the position information derived from the track and the chassis information of the vehicle when the signal of the vehicle's global positioning navigation system is interfered with, calculate the position of the vehicle, and ensure the accuracy of the vehicle positioning. When the global positioning navigation signal returns to normal, it can ensure that the vehicle positioning will not jump over large distances.

[0057] The technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0058] Figure 1 It is a flow chart of the vehicle positioning method shown in an embodiment of the present application.

[0059] See also Figure 1 The vehicle positioning method provided in the embodiment of the present application includes:

[0060] Step S101: When the signal strength of the vehicle-mounted navigation device does not meet the preset positioning condition, the vehicle's driving trajectory is deduced.

[0061] In an embodiment of the present application, a combined navigation module is installed on the autonomous driving vehicle, which includes a GNSS (Global Navigation Satellite System) and a track deduction module. Due to certain special geographical environments or network environments, the GNSS signal may be interfered with. When the combined navigation module determines that the degree of interference with the GNSS signal causes the strength of the GNSS signal to be unable to meet the strength of positioning navigation, the track deduction module is activated to perform track deduction on the driving trajectory of the autonomous driving vehicle.

[0062] Step S102, obtaining the position information and chassis information of the vehicle during track deduction, and when the track deduction satisfies a preset deduction condition and the signal of the vehicle navigation device has not yet recovered, determining the virtual observation position of the vehicle based on the position information and the chassis information.

[0063] In an embodiment of the present application, a trajectory deduction module is used to deduce the driving trajectory of an autonomous vehicle. Deduction conditions are preset. When the trajectory deduction module meets the preset conditions and the signal from the onboard navigation device has not yet been restored, the vehicle's position information and chassis information during the trajectory deduction process are obtained. As a possible implementation of the present application, the preset deduction conditions may include the duration of the trajectory deduction reaching a preset duration threshold, the distance traveled by the autonomous vehicle under trajectory deduction reaching a preset distance threshold, etc. The present application does not limit the specific deduction conditions.

[0064] As a possible implementation method of the present application, when the combined navigation module of the autonomous driving vehicle determines that the GNSS signal does not meet the navigation requirements, the track deduction module starts to deduce the vehicle's driving trajectory. During the track deduction process, the driving data of the autonomous driving vehicle obtained by the track deduction is continuously obtained, including but not limited to the speed, acceleration, track deduction time and the distance traveled by the autonomous driving vehicle under the track deduction. When any of the aforementioned preset deduction conditions is met, such as the deduction time reaches five minutes, or the driving distance of the autonomous driving vehicle under the track deduction reaches two kilometers, the vehicle's position information and the vehicle's current chassis information under the track deduction are determined in combination with the vehicle's driving data.

[0065] Step S103 : Calculate the real-time position of the vehicle based on the virtual observation position and in combination with a preset filtering algorithm.

[0066] In an embodiment of the present application, when the trajectory extrapolation meets a preset condition, a preset filtering algorithm is used to calculate the vehicle's real-time position based on the acquired vehicle position information and chassis information. The preset filtering algorithm may be a Kalman filter algorithm, which combines the autonomous vehicle's position information obtained from the trajectory extrapolation with the vehicle's real-time chassis information to determine the vehicle's real-time position.

[0067] The embodiment of the present application performs track deduction on the vehicle's driving trajectory and records the track deduction process when the signal strength of the on-board navigation device does not meet the positioning conditions. When the track deduction reaches a preset restriction condition, the position information of the track deduction and the chassis information of the vehicle are obtained, and the real-time position of the vehicle is calculated using a filtering algorithm based on the position information and the chassis speed. By setting restriction conditions for the track deduction and using a filtering algorithm to calculate the real-time position of the vehicle in combination with the position information of the track deduction and the chassis information of the vehicle, the accumulation of errors caused by excessively long track deduction time can be effectively prevented, the accuracy of the vehicle positioning can be determined, and large-distance jumps in the vehicle positioning can be prevented.

[0068] As a possible implementation of the present application, in this implementation, if Figure 2 As shown, the vehicle trajectory deduction includes:

[0069] Step S201 : obtaining an inertial measurement value of the vehicle based on the vehicle-mounted inertial measurement unit.

[0070] In an embodiment of the present application, the track deduction module on the autonomous vehicle includes an on-board inertial measurement unit. When performing track deduction on the autonomous vehicle, the vehicle's inertial measurement value is obtained through the on-board inertial vehicle unit. Optionally, the on-board inertial measurement unit includes an on-board accelerometer, an on-board magnetometer, and an on-board gyroscope. The inertial measurement value can be a value measured by the accelerometer, the geomagnetism of the vehicle area measured by the on-board magnetometer, and a measurement value measured by the gyroscope, etc.

[0071] Step S202 : Calculate the acceleration and angular velocity of the vehicle and the geomagnetism of the location of the vehicle based on the inertial measurement value.

[0072] In an embodiment of the present application, the vehicle's driving information is calculated using inertial measurement values obtained by measuring an on-board inertial measurement unit, wherein the driving information includes the vehicle's acceleration, angular velocity, and geomagnetism at the location of the vehicle.

[0073] Step S203 , calculating the vehicle's track information based on the vehicle's acceleration, angular velocity, and geomagnetism at the vehicle's location, wherein the vehicle's track information includes the vehicle's speed information and position information.

[0074] In an embodiment of the present application, after calculating the acceleration angular velocity of the autonomous driving vehicle and the geomagnetic field at the location of the vehicle, the vehicle's track information is deduced in combination with the duration of the track deduction. For example, the vehicle's speed can be calculated through the relationship between acceleration and time; the vehicle's heading angular velocity is used to infer whether the vehicle is in a turning state, as well as information such as the vehicle's turning radius, and then the vehicle's speed information is combined to calculate the vehicle's driving trajectory, wherein the driving trajectory includes the vehicle's turning trajectory, and then the measured driving distance is calculated to determine the vehicle's position information.

[0075] In the embodiment of the present application, an on-board inertial unit is used to obtain the vehicle's inertial measurement value, and based on the vehicle's inertial measurement value, the vehicle's driving information, such as acceleration, angular velocity, and the geomagnetic field at the location of the vehicle, is calculated. The vehicle's position and speed information are determined by combining this driving information with the duration of the track deduction to ensure the accuracy of the measurement and positioning.

[0076] As a possible implementation of the present application, in this implementation, the preset deduction conditions include one and / or more of the following:

[0077] The deduction duration of the track deduction reaches a first preset duration threshold;

[0078] The travel distance of the vehicle reaches a preset distance threshold;

[0079] In an embodiment of the present application, as described in the aforementioned embodiment, the preset deduction condition may be that the duration of the track deduction reaches a preset duration threshold, or the driving distance of the autonomous driving vehicle under track deduction reaches a preset distance threshold. When the autonomous driving vehicle is driving in the track deduction mode, when any of the above conditions is met, it indicates that the track deduction has reached the threshold for effective deduction, and it is necessary to integrate the speed, angle, and position information provided by the vehicle body information as virtual observation information to update the filter and thereby obtain a more accurate real-time position of the vehicle.

[0080] As a possible implementation of the present application, when the deduction duration of the track deduction reaches a first preset duration threshold, the position information of the vehicle in the track deduction and the chassis speed of the vehicle are obtained. For example, the first preset duration threshold is five minutes. When the vehicle has been driving for five minutes in the track deduction mode, it means that the track deduction has reached the effective threshold. At this time, it is necessary to integrate the speed, angle, and position information provided by the vehicle body information, update the filter, and then obtain a more accurate real-time position of the vehicle. For another example, the preset distance threshold is two kilometers. When the autonomous driving vehicle has traveled two kilometers in the track deduction mode, it means that the track deduction has reached the effective threshold. At this time, it is necessary to integrate the speed, angle, and position information provided by the vehicle body information, update the filter, and then obtain a more accurate real-time position of the vehicle.

[0081] The embodiment of the present application passes several possible track deduction conditions. When the track deduction satisfies any one of the conditions, it means that the track deduction reaches the effective threshold. At this time, it is necessary to integrate the speed, angle, and position information provided by the vehicle body information to update the filter, thereby obtaining a more accurate real-time position of the vehicle, ensuring the accuracy of vehicle positioning, and preventing the vehicle position displayed in the navigation device from changing suddenly.

[0082] As a possible implementation of the present application, in this implementation, obtaining the chassis speed of the vehicle includes:

[0083] The chassis speed and the vehicle yaw angular velocity of the vehicle are obtained through the vehicle controller local area network.

[0084] In the embodiments of this application, chassis speed refers to the speed of the vehicle chassis. This chassis speed can be obtained via the vehicle's CAN (Controller Area Network) bus or calculated using other methods, such as measuring wheel speed using sensors on the vehicle and then calculating the chassis speed based on the circumference of the vehicle's tires. The vehicle's yaw rate can be obtained using a Yaw-G sensor.

[0085] As a possible implementation of the present application, in this implementation, if Figure 3As shown, the preset filtering algorithm is a Kalman filtering algorithm, and the virtual observation position of the vehicle is determined based on the position information and the chassis information, including:

[0086] Step S301 : Acquire inertial measurement values of the vehicle based on a vehicle-mounted inertial measurement unit, wherein the inertial measurement values include acceleration and angular velocity of the vehicle and geomagnetism at the location of the vehicle.

[0087] In an embodiment of the present application, the track deduction module on the autonomous vehicle includes an on-board inertial measurement unit. When performing track deduction on the autonomous vehicle, the vehicle's inertial measurement value is obtained through the on-board inertial vehicle unit. Optionally, the on-board inertial measurement unit includes an on-board accelerometer, an on-board magnetometer, and an on-board gyroscope. The inertial measurement value includes the vehicle's acceleration, steering angle, and geomagnetism at the vehicle's location.

[0088] Step S302 : constructing a state vector of the vehicle based on the angular velocity and the geomagnetic field of the location of the vehicle, updating the state vector using the Kalman filter algorithm, and determining the Euler angle of the vehicle.

[0089] In an embodiment of the present application, a state vector is constructed based on a quaternion differential equation by adding the bias of the gyroscope, and the state vector is updated using a Kalman filter algorithm to obtain the Euler angle of the vehicle.

[0090] Step S303: determining the real-time speed of the vehicle based on the acceleration; and calculating the virtual observation position of the vehicle based on the track deduction duration in combination with the Euler angle and the real-time speed of the vehicle.

[0091] In an embodiment of the present application, after obtaining the vehicle's acceleration via an accelerometer, the vehicle's real-time speed is determined based on the acceleration and the vehicle's real-time chassis speed. In an embodiment of the present application, the vehicle's real-time speed can be determined based on an acceleration formula, the duration of the track deduction, and the vehicle's acceleration. In an embodiment of the present application, after determining the vehicle's Euler angles and real-time speed, the vehicle's distance traveled is calculated based on the duration of the track deduction and the vehicle's real-time speed. Then, based on the vehicle's Euler angles, the vehicle's steering, uphill and downhill movements during travel are determined, thereby determining the vehicle's virtual observation position.

[0092] The embodiment of the present application uses a Kalman filter algorithm to combine the vehicle's position information and chassis speed information to determine the vehicle's real-time position, thereby ensuring the accuracy of vehicle positioning.

[0093] As a possible implementation of the present application, in this implementation, if Figure 4 As shown, the real-time position of the vehicle is calculated based on the virtual observation position in combination with a preset filtering algorithm, including:

[0094] Step S401 : calculating an error coefficient of the chassis velocity and an error coefficient of the vehicle yaw rate based on the velocity information and Euler angles obtained by the vehicle-mounted inertial measurement unit within the deduction conditions.

[0095] In this embodiment of the present application, when the trajectory extrapolation meets preset extrapolation conditions, the vehicle's speed information and Euler angle information obtained through the trajectory extrapolation are obtained to determine the error coefficient of the vehicle's chassis speed and the error coefficient of the vehicle's yaw rate. In this embodiment of the present application, this can be determined using a pre-set error adjustment model.

[0096] Step S402, calculating the speed observation value obtained through track deduction based on the error coefficient of the chassis speed, calculating the angular velocity observation value obtained through track deduction based on the error coefficient of the vehicle yaw angular velocity, and combining the speed observation value and the angular velocity observation value to calculate the virtual observation value of the vehicle's position.

[0097] In an embodiment of the present application, after determining the error coefficient of the vehicle chassis speed and the error coefficient of the vehicle yaw angular velocity, the vehicle speed observation value and the angular velocity observation value are determined based on the vehicle speed information and the vehicle angular velocity information obtained by track deduction, wherein the vehicle speed observation value and the angular velocity observation value refer to the vehicle speed and the vehicle angular velocity used for filter fusion.

[0098] Step S403: Update the observation of the vehicle position by a filter based on the virtual observation value to determine the real-time position of the vehicle.

[0099] In an embodiment of the present application, the virtual observation values of the vehicle position are fused through a filter, wherein the fused information also includes signals received by other sensors, such as visual sensors, high-precision maps and other information. The virtual observation values of the vehicle position obtained by track deduction are fused with the above information to obtain more accurate vehicle position information.

[0100] As a possible implementation of the present application, in this implementation, if Figure 5 As shown, after performing track deduction on the vehicle's driving trajectory, the method further includes:

[0101] Step S501 : within a preset time period, when the signal of the vehicle navigation device passes the card-square detection, the track deduction of the vehicle's driving trajectory is stopped, and the vehicle navigation device is used to navigate the vehicle.

[0102] In an embodiment of the present application, the real-time position of the vehicle obtained by the track deduction module is used as the true value, and the real-time position of the vehicle obtained by positioning the on-board navigation device is used as the detection value for chi-square detection. When the signal strength of the on-board navigation device passes the chi-square detection, it indicates that the signal strength of the on-board navigation device can navigate the vehicle, and the vehicle position information determined by the on-board navigation device is determined as the real-time position of the vehicle.

[0103] Step S502: When the signal of the vehicle navigation device does not pass the card square detection within the preset time period, stop the card square detection of the signal of the vehicle navigation device until it is determined that the signal of the vehicle navigation device meets the preset positioning condition, and use the vehicle navigation device to navigate the vehicle.

[0104] In the embodiments of the present application, there are two situations in which the signal strength of the vehicle navigation device does not meet the positioning conditions. One is that the signal of the vehicle navigation device mentioned in the previous embodiment is interfered with for a long time, making it impossible to accurately locate the vehicle. The other is that when the positioning information of the vehicle navigation device is affected, the change is only short-term, and the signal strength of the vehicle navigation device does not meet the positioning conditions continuously and briefly, such as when the signal of the vehicle navigation device experiences one or more frame jumps due to occlusion or other reasons. When the signal strength of the vehicle navigation device experiences short-term jumps, the signal of the vehicle navigation device cannot pass the card-square detection, and the filter rejects the signal update.

[0105] In the embodiment of the present application, when the signal strength of the vehicle-mounted navigation device changes for a short time, a card-square test is performed on the signal of the vehicle-mounted navigation device. When the signal strength of the vehicle-mounted navigation device meets the card-square test, the vehicle-mounted navigation device is used to locate and navigate the vehicle, thereby preventing the time for independent practical track deduction and navigation from being too long and improving the accuracy of vehicle navigation.

[0106] The technical solution provided by the present application may include the following beneficial effects: the embodiment of the present application performs track deduction on the vehicle's driving trajectory and records the process of track deduction when the signal strength of the on-board navigation device does not meet the positioning conditions. When the track deduction reaches a preset restriction condition, the position information of the track deduction and the chassis speed of the vehicle are obtained, and the real-time position of the vehicle is calculated using a filtering algorithm based on the position information and chassis speed. By setting restriction conditions for the track deduction and using a filtering algorithm to calculate the real-time position of the vehicle in combination with the position information of the track deduction and the chassis speed information of the vehicle, the error accumulation caused by the long track deduction time can be effectively prevented, the accuracy of the vehicle positioning can be determined, and large-distance jumps in the vehicle positioning can be prevented.

[0107] Corresponding to the aforementioned application function implementation method embodiment, the present application also provides a vehicle positioning device, an electronic device and corresponding embodiments.

[0108] Figure 6 It is a structural schematic diagram of a vehicle positioning device shown in an embodiment of the present application.

[0109] See also Figure 6 The vehicle positioning device 60 provided in the embodiment of the present application includes a track deduction module 610, an information acquisition module 620, and a real-time positioning module 630, wherein:

[0110] The track deduction module 610 is used to perform track deduction on the vehicle's driving trajectory when the signal strength of the vehicle navigation device does not meet the preset positioning conditions;

[0111] An information acquisition module 620 is configured to acquire the vehicle's position information and chassis information during track derivation, and determine a virtual observation position of the vehicle based on the position information and chassis information when the track derivation satisfies a preset derivation condition and the signal from the vehicle navigation device has not yet been restored.

[0112] The real-time positioning module 630 is used to calculate the real-time position of the vehicle based on the virtual observation position in combination with a preset filtering algorithm.

[0113] As a possible implementation of the present application, in this implementation, when the trajectory deduction module 610 performs trajectory deduction on the vehicle's driving trajectory, it can be used to:

[0114] Obtaining vehicle inertial measurement values based on an onboard inertial measurement unit;

[0115] Calculating the acceleration and angular velocity of the vehicle and the geomagnetism of the location of the vehicle based on the inertial measurement value;

[0116] The vehicle's track information is calculated based on the vehicle's acceleration, angular velocity, and geomagnetism at the vehicle's location, wherein the vehicle's track information includes the vehicle's speed information and position information.

[0117] As a possible implementation of the present application, in this implementation, when the track extrapolation meets the preset extrapolation conditions, the information acquisition module 620 acquires the position information and chassis information of the vehicle in the track extrapolation, which can be used to:

[0118] When the duration of the trajectory deduction reaches a first preset duration threshold, obtaining position information of the vehicle and chassis information of the vehicle in the trajectory deduction;

[0119] When the vehicle's travel distance reaches a preset distance threshold, the vehicle's position information and chassis information in the trajectory deduction are obtained;

[0120] As a possible implementation of the present application, in this implementation, when acquiring chassis information of a vehicle, the information acquisition module 620 may be used to:

[0121] The chassis speed and the vehicle yaw angular velocity of the vehicle are obtained through the vehicle controller local area network.

[0122] As a possible implementation of the present application, in this implementation, the preset filtering algorithm is a Kalman filtering algorithm. When the real-time positioning module 630 calculates the real-time position of the vehicle based on the position information and the chassis speed using the preset filtering algorithm, it can be used to:

[0123] Acquiring inertial measurement values of the vehicle based on an on-board inertial measurement unit, wherein the inertial measurement values include acceleration and angular velocity of the vehicle and geomagnetism at a location of the vehicle;

[0124] constructing a state vector of the vehicle based on the angular velocity and the geomagnetic field of the location of the vehicle, and updating the state vector using the Kalman filter algorithm to determine the Euler angle of the vehicle;

[0125] The real-time speed of the vehicle is determined based on the acceleration, and the virtual observation position of the vehicle is calculated based on the track deduction duration in combination with the Euler angle of the vehicle. As a possible implementation of the present application, in this implementation, the real-time positioning module 630

[0126] Based on the virtual observation position, combined with a preset filtering algorithm, the real-time position of the vehicle is calculated, including:

[0127] Calculating an error coefficient of the chassis velocity of the vehicle and an error coefficient of the yaw rate of the vehicle based on the velocity information and Euler angles obtained by the vehicle-mounted inertial measurement unit within the deduction conditions;

[0128] Calculating a velocity observation value obtained through trajectory extrapolation based on an error coefficient of the chassis velocity, calculating an angular velocity observation value obtained through trajectory extrapolation based on an error coefficient of the vehicle yaw angular velocity, and calculating a virtual observation value of the vehicle position by combining the velocity observation value and the angular velocity observation value;

[0129] The filter updates the observation of the vehicle position based on the virtual observation value to determine the real-time position of the vehicle.

[0130] As a possible implementation of the present application, in this implementation, when the signal strength of the vehicle-mounted navigation device does not meet the preset positioning conditions, the device may also be used to:

[0131] When the signal of the vehicle navigation device passes the card square detection within a preset time period, the track deduction of the vehicle's driving trajectory is stopped and the vehicle navigation device is used to navigate the vehicle;

[0132] When the signal of the vehicle navigation device does not pass the card square detection within the preset time period, the card square detection of the signal of the vehicle navigation device is stopped until it is determined that the signal of the vehicle navigation device meets the preset positioning conditions, and the vehicle navigation device is used to navigate the vehicle.

[0133] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated again here.

[0134] The technical solution provided by the present application may include the following beneficial effects: the embodiment of the present application performs track deduction on the vehicle's driving trajectory and records the process of track deduction when the signal strength of the on-board navigation device does not meet the positioning conditions. When the track deduction reaches a preset restriction condition, the position information of the track deduction and the chassis speed of the vehicle are obtained, and the real-time position of the vehicle is calculated using a filtering algorithm based on the position information and chassis speed. By setting restriction conditions for the track deduction and combining the position information of the track deduction and the chassis speed information of the vehicle with a filtering algorithm to calculate the real-time position of the vehicle, it is possible to effectively prevent the accumulation of errors caused by excessively long track deduction time, determine the accuracy of the vehicle positioning, and prevent the vehicle positioning from jumping.

[0135] Figure 7 It is a structural diagram of an electronic device shown in an embodiment of the present application.

[0136] See also Figure 7 , the electronic device 1000 includes a memory 1010 and a processor 1020.

[0137] The processor 1020 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0138] Memory 1010 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage. ROM may store static data or instructions required by processor 1020 or other computer modules. Permanent storage may be a readable and writable storage device. Permanent storage may be a non-volatile storage device that retains stored instructions and data even when the computer is powered off. In some embodiments, the permanent storage device utilizes a mass storage device (e.g., a magnetic or optical disk, flash memory). In other embodiments, the permanent storage device may be a removable storage device (e.g., a floppy disk, optical drive). System memory may be a readable and writable storage device or a volatile readable and writable storage device, such as dynamic random access memory (DRAM). System memory may store some or all instructions and data required by the processor during operation. Furthermore, memory 1010 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (e.g., DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), as well as magnetic disks and / or optical disks. In some embodiments, the memory 1010 may include a readable and / or writable removable storage device, such as a compact disc (CD), a read-only digital versatile disc (e.g., DVD-ROM, double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (e.g., SD card, mini SD card, Micro-SD card, etc.), a magnetic floppy disk, etc. Computer-readable storage media do not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0139] The memory 1010 stores executable codes. When the executable codes are processed by the processor 1020 , the processor 1020 may execute part or all of the above-mentioned methods.

[0140] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0141] Alternatively, the present application can also be implemented as a computer-readable storage medium (or non-transitory machine-readable storage medium or machine-readable storage medium) on which executable code (or computer program or computer instruction code) is stored. When the executable code (or computer program or computer instruction code) is executed by a processor of an electronic device (or server, etc.), the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0142] The embodiments of the present application have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or improvements to the technology in the market, or to enable other persons skilled in the art to understand the embodiments disclosed herein.

Claims

1. A vehicle positioning method, characterized in that: The method comprises: When the signal strength of the vehicle navigation device does not meet the preset positioning conditions, the vehicle's driving trajectory is deduced; Obtaining the position information and chassis information of the vehicle during track deduction, and when the track deduction satisfies a preset deduction condition and the signal of the on-board navigation device has not yet been restored, determining the virtual observation position of the vehicle based on the position information and the chassis information; wherein, determining the virtual observation position of the vehicle based on the position information and the chassis information includes: obtaining inertial measurement values of the vehicle based on an on-board inertial measurement unit, wherein the inertial measurement values include acceleration, angular velocity, and geomagnetism of the location of the vehicle; constructing a state vector of the vehicle based on the angular velocity and geomagnetism of the location of the vehicle, updating the state vector using a Kalman filter algorithm, and determining the Euler angle of the vehicle; determining the real-time speed of the vehicle based on the acceleration, and calculating the virtual observation position of the vehicle based on the track deduction duration in combination with the Euler angle and real-time speed of the vehicle; wherein, the preset deduction condition includes one or more of the following: the deduction duration of the track deduction reaches a first preset duration threshold; the driving distance of the vehicle reaches a preset distance threshold; Based on the virtual observation position, combined with a preset filtering algorithm, the real-time position of the vehicle is calculated; the preset filtering algorithm is a Kalman filtering algorithm; which includes: calculating the error coefficient of the chassis speed of the vehicle and the error coefficient of the vehicle yaw angular velocity based on the speed information and Euler angles obtained by the on-board inertial measurement unit within the deduction conditions; calculating the speed observation value obtained by track deduction based on the error coefficient of the chassis speed, calculating the angular velocity observation value obtained by track deduction based on the error coefficient of the vehicle yaw angular velocity, and calculating the virtual observation value of the vehicle's position by combining the speed observation value and the angular velocity observation value; performing a filter observation update on the vehicle position based on the virtual observation value to determine the real-time position of the vehicle.

2. The vehicle positioning method according to claim 1, characterized in that: The performing trajectory deduction on the vehicle's driving trajectory includes: Obtaining inertial measurement values of the vehicle based on an onboard inertial measurement unit; Calculating the acceleration and angular velocity of the vehicle and the geomagnetism of the location of the vehicle based on the inertial measurement value; The vehicle's track information is calculated based on the vehicle's acceleration, angular velocity, and geomagnetism at the vehicle's location, wherein the vehicle's track information includes the vehicle's speed information, angle information, and position information.

3. The vehicle positioning method according to claim 1, characterized in that: The obtaining of chassis information of the vehicle includes: The chassis speed and the vehicle yaw angular velocity of the vehicle are obtained through the vehicle controller local area network.

4. The vehicle positioning method according to claim 1, characterized in that: After the vehicle trajectory is deduced, the method further includes: When the signal of the vehicle navigation device passes the card square detection within a preset time period, the track deduction of the vehicle's driving trajectory is stopped and the vehicle navigation device is used to navigate the vehicle; When the signal of the vehicle navigation device does not pass the card square detection within the preset time period, the card square detection of the signal of the vehicle navigation device is stopped until it is determined that the signal of the vehicle navigation device meets the preset positioning conditions, and the vehicle navigation device is used to navigate the vehicle.

5. A vehicle positioning device, characterized in that: The vehicle positioning device comprises: A track deduction module is used to perform track deduction on the vehicle's driving trajectory when the signal strength of the vehicle navigation device does not meet the preset positioning conditions; An information acquisition module is configured to acquire position information and chassis information of a vehicle during track deduction, and when the track deduction satisfies a preset deduction condition and the signal of the on-board navigation device has not yet been restored, determine the virtual observation position of the vehicle based on the position information and the chassis information; wherein, determining the virtual observation position of the vehicle based on the position information and the chassis information comprises: acquiring inertial measurement values of the vehicle based on an on-board inertial measurement unit, wherein the inertial measurement values include acceleration, angular velocity, and geomagnetism of the vehicle's location; constructing a state vector of the vehicle based on the angular velocity and geomagnetism of the vehicle's location, updating the state vector using a Kalman filter algorithm, and determining the Euler angle of the vehicle; determining the real-time speed of the vehicle based on the acceleration, and calculating the virtual observation position of the vehicle based on the track deduction duration in combination with the Euler angle and real-time speed of the vehicle; wherein, the preset deduction condition comprises one or more of the following: the deduction duration of the track deduction reaches a first preset duration threshold; the travel distance of the vehicle reaches a preset distance threshold; A real-time positioning module is used to calculate the real-time position of the vehicle based on the virtual observation position in combination with a preset filtering algorithm; the preset filtering algorithm is a Kalman filtering algorithm; wherein, it includes: calculating the error coefficient of the chassis speed and the error coefficient of the vehicle's yaw angular velocity based on the speed information and Euler angles obtained by the on-board inertial measurement unit within the deduction conditions; calculating the speed observation value obtained by track deduction based on the error coefficient of the chassis speed, calculating the angular velocity observation value obtained by track deduction based on the error coefficient of the vehicle yaw angular velocity, and calculating the virtual observation value of the vehicle's position by combining the speed observation value and the angular velocity observation value; and performing a filter update on the vehicle position observation based on the virtual observation value to determine the real-time position of the vehicle.

6. An electronic device, characterized in that: include: processor; as well as A memory having executable codes stored thereon, which, when executed by the processor, causes the processor to execute the vehicle positioning method according to any one of claims 1 to 4.

7. A computer-readable storage medium having executable code stored thereon, wherein when the executable code is executed by a processor of an electronic device, the processor is caused to execute the vehicle positioning method according to any one of claims 1 to 4.

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