Vehicle positioning calibration method, device, computer equipment, and storage medium

Abstract

The present application relates to a vehicle positioning calibration method, device, computer equipment, storage medium and computer program product. The method comprises: obtaining first positioning information and second positioning information obtained through multiple vehicle-mounted electronic devices of a target vehicle; obtaining the cumulative error of the first positioning information, and adjusting the confidence parameter according to the cumulative error; calculating the speed error of the target vehicle according to the second positioning information, and adjusting the weight parameter according to the speed error; if the confidence parameter satisfies the first preset condition, and the weight parameter satisfies the second preset condition, obtaining calibration positioning information according to the first positioning information and the second positioning information. The method can be used to calculate the error size of different types of positioning information, adjust the confidence or weight corresponding to each positioning information, and determine the effective positioning information in combination with the confidence and weight, and obtain the calibration positioning information according to the effective positioning information, so as to improve the accuracy of vehicle positioning.

Description

Technical Field

[0001] The present application relates to the field of vehicle networking technology, and in particular to a vehicle positioning and calibration method, device, computer equipment, storage medium and computer program product. Background Art

[0002] When a vehicle is traveling in a place without satellite positioning signals, such as an indoor parking lot, remote mountainous area, or a road scene with weak positioning signals, such as areas with a lot of shade from trees, many tall buildings, many obstacles, overpasses, etc., it is impossible to obtain accurate vehicle location information, which makes it impossible to use positioning-related applications on the vehicle or prone to errors. Moreover, if the vehicle travels in an area with poor navigation signals for a long time, the position calculated by the GNSS+ inertial navigation positioning system currently commonly used on vehicles will gradually deviate from the actual position, and navigation errors and other problems are likely to occur.

[0003] The current vehicle positioning is affected by different road scenes and the positioning accuracy is not high. Summary of the invention

[0004] Based on this, it is necessary to provide a vehicle positioning calibration method, device, computer equipment, computer readable storage medium and computer program product that can improve the vehicle positioning accuracy in response to the above technical problems.

[0005] In a first aspect, the present application provides a vehicle positioning calibration method. The method comprises:

[0006] Acquire first positioning information and second positioning information obtained by a plurality of on-board electronic devices of a target vehicle;

[0007] Obtaining a cumulative error of the first positioning information, and adjusting a confidence parameter according to the cumulative error;

[0008] Calculating a speed error of the target vehicle according to the second positioning information, and adjusting a weight parameter according to the speed error;

[0009] If the confidence parameter satisfies the first preset condition and the weight parameter satisfies the second preset condition, calibration positioning information is acquired according to the first positioning information and the second positioning information.

[0010] In one embodiment, the plurality of vehicle-mounted electronic devices at least include a satellite signal receiving device, an inertial measurement device, and a network access device, and obtaining first positioning information and second positioning information obtained by the plurality of vehicle-mounted electronic devices of the target vehicle includes:

[0011] Acquire original positioning data of the target vehicle obtained through a satellite signal receiving device, and six-axis data of the target vehicle obtained through an inertial measurement device;

[0012] The original three-dimensional position information of the target vehicle is calculated based on the six-axis data;

[0013] Obtaining first positioning information according to the original three-dimensional position information and the original positioning data;

[0014] The second positioning information of the target vehicle is obtained from the real-time dynamic measurement system through the network access device.

[0015] In one embodiment, obtaining the accumulated error of the first positioning information and adjusting the confidence parameter according to the accumulated error includes:

[0016] If the cumulative error is greater than or equal to the error threshold, reduce the confidence parameter.

[0017] In one embodiment, calculating the speed error of the target vehicle according to the second positioning information, and adjusting the weight parameter according to the speed error, includes:

[0018] According to the second positioning information, obtaining the positioning of the target vehicle at multiple consecutive moments at preset time intervals;

[0019] The measured speed of the target vehicle at the current continuous moment is calculated based on the positioning at the current continuous moment, the positioning at the previous continuous moment and the preset time interval;

[0020] If the measured speed of the target vehicle at the current continuous moment is not within the standard speed threshold range, the measured speed of the target vehicle at the current continuous moment is determined to be an abnormal speed;

[0021] If the number of consecutive abnormal speed determinations exceeds the number threshold, the weight parameter is reduced.

[0022] In one embodiment, obtaining calibration positioning information according to the first positioning information and the second positioning information includes:

[0023] Acquire first three-dimensional position information from the first positioning information, where the first three-dimensional position information includes a first longitude, a first latitude, and a first altitude;

[0024] Acquire second three-dimensional positioning information from the second positioning information, where the second three-dimensional position information includes a second longitude, a second latitude, and a second altitude;

[0025] The first longitude and the second longitude are filtered by a federal Kalman filter to obtain a fused longitude, the first latitude and the second latitude are filtered to obtain a fused latitude, and the first altitude and the second altitude are filtered to obtain a fused altitude;

[0026] The fused longitude, fused latitude and fused altitude are used as fused three-dimensional position information, and the fused three-dimensional position information replaces the first three-dimensional position information in the first positioning information to obtain calibrated positioning information.

[0027] In one embodiment, the method further comprises:

[0028] The third positioning information of at least three roadside devices corresponding to the target vehicle is obtained.

[0029] In one embodiment, the method further comprises:

[0030] If the confidence parameter satisfies the first preset condition and the weight parameter does not satisfy the second preset condition, calibration positioning information is acquired according to the first positioning information and the third positioning information.

[0031] In one embodiment, the method further comprises:

[0032] If the confidence parameter does not satisfy the first preset condition and the weight parameter satisfies the second preset condition, calibration positioning information is obtained according to the second positioning information and the third positioning information.

[0033] In one embodiment, the method further comprises:

[0034] If the confidence parameter does not meet the first preset condition and the weight parameter does not meet the second preset condition, the third positioning information is used as the calibration positioning information.

[0035] In a second aspect, the present application also provides a vehicle positioning calibration device. The device comprises:

[0036] A positioning acquisition module, used to acquire first positioning information and second positioning information obtained through a plurality of vehicle-mounted electronic devices of a target vehicle;

[0037] A first adjustment module, used to obtain a cumulative error of the first positioning information and adjust a confidence parameter according to the cumulative error;

[0038] A second adjustment module, used to calculate a speed error of the target vehicle according to the second positioning information, and adjust a weight parameter according to the speed error;

[0039] The positioning calibration module is used to obtain calibration positioning information according to the first positioning information and the second positioning information if the confidence parameter meets the first preset condition and the weight parameter meets the second preset condition.

[0040] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0041] Acquire first positioning information and second positioning information obtained by a plurality of on-board electronic devices of a target vehicle;

[0042] Obtaining a cumulative error of the first positioning information, and adjusting a confidence parameter according to the cumulative error;

[0043] Calculating a speed error of the target vehicle according to the second positioning information, and adjusting a weight parameter according to the speed error;

[0044] If the confidence parameter satisfies the first preset condition and the weight parameter satisfies the second preset condition, calibration positioning information is acquired according to the first positioning information and the second positioning information.

[0045] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0046] Acquire first positioning information and second positioning information obtained by a plurality of on-board electronic devices of a target vehicle;

[0047] Obtaining a cumulative error of the first positioning information, and adjusting a confidence parameter according to the cumulative error;

[0048] Calculating a speed error of the target vehicle according to the second positioning information, and adjusting a weight parameter according to the speed error;

[0049] If the confidence parameter satisfies the first preset condition and the weight parameter satisfies the second preset condition, calibration positioning information is acquired according to the first positioning information and the second positioning information.

[0050] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0051] Acquire first positioning information and second positioning information obtained by a plurality of on-board electronic devices of a target vehicle;

[0052] Obtaining a cumulative error of the first positioning information, and adjusting a confidence parameter according to the cumulative error;

[0053] Calculating a speed error of the target vehicle according to the second positioning information, and adjusting a weight parameter according to the speed error;

[0054] If the confidence parameter satisfies the first preset condition and the weight parameter satisfies the second preset condition, calibration positioning information is acquired according to the first positioning information and the second positioning information.

[0055] The above-mentioned vehicle positioning calibration method, device, computer equipment, storage medium and computer program product obtain the first positioning information and the second positioning information obtained by multiple vehicle-mounted electronic devices of the target vehicle; obtain the cumulative error of the first positioning information, and adjust the confidence parameter according to the cumulative error; calculate the speed error of the target vehicle according to the second positioning information, and adjust the weight parameter according to the speed error; if the confidence parameter meets the first preset condition and the weight parameter meets the second preset condition, obtain the calibration positioning information according to the first positioning information and the second positioning information. By calculating the error size of different types of positioning information, adjusting the confidence or weight corresponding to each positioning information, and determining the effective positioning information in combination with the confidence and weight, and obtaining the calibration positioning information according to the effective positioning information, the accuracy of vehicle positioning can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A diagram showing an application environment of a vehicle positioning calibration method in an embodiment;

[0057] Figure 2 A schematic diagram of a process flow of a vehicle positioning calibration method in one embodiment;

[0058] Figure 3 A logical schematic diagram of vehicle positioning calibration in one embodiment;

[0059] Figure 4 is a structural block diagram of a vehicle positioning and calibration device in one embodiment;

[0060] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0062] The vehicle positioning calibration method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the application processor is a component in a vehicle. It can be understood that the vehicle can be a vehicle, a robot device with a driving function, etc., and the vehicle can be a truck, an off-road vehicle, a dump truck, a tractor, a special-purpose vehicle, a bus, a car, a semi-trailer, etc. The satellite signal receiving device (GNSS receiving device), the inertial measurement unit (IMU, InertialMeasurement Unit), the network access device (NAD, Network Access Device), the communication device and the application processor are connected and communicated. The application processor can communicate with the real-time dynamic measurement system (RTK system) through the network access device, and the application processor can also communicate wirelessly with multiple roadside devices through the communication device.

[0063] In one embodiment, Figure 2 As shown, a vehicle positioning calibration method is provided, which is applied to Figure 1 The application processor in FIG. 1 is taken as an example to illustrate the process, which includes the following steps:

[0064] Step 202: Acquire first positioning information and second positioning information obtained through a plurality of vehicle-mounted electronic devices of the target vehicle.

[0065] Among them, the first positioning information can be vehicle dead reckoning positioning information, also known as DR (Dead Reckoning) positioning information; the second positioning information can be real-time dynamic measurement positioning information, also known as RTK (Real Time Kinematic) positioning information.

[0066] Optionally, the application processor is installed on the target vehicle and communicates with the GNSS receiver and IMU on the target vehicle. The IMU mainly includes sensors such as gravity, geomagnetism, gyroscope, accelerometer, and electronic compass. The application processor uses the six-axis data of the IMU to correct the original positioning data received by the GNSS receiver, thereby obtaining the DR positioning information of the target vehicle, and obtains the RTK positioning information of the target vehicle by communicating with the NAD on the target vehicle. Both the DR positioning information and the RTK positioning information contain three-dimensional position information composed of longitude, latitude, and altitude.

[0067] Step 204: Obtain the accumulated error of the first positioning information, and adjust the confidence parameter according to the accumulated error.

[0068] Optionally, the application processor continuously detects the cumulative error of the DR positioning information (first positioning information). When the cumulative error reaches a certain level, it is determined that the error of the DR positioning information is large, and the confidence parameter is reduced.

[0069] Step 206, calculating the speed error of the target vehicle according to the second positioning information, and adjusting the weight parameter according to the speed error.

[0070] Optionally, the application processor determines multiple continuous positioning positions according to the preset sampling frequency based on the RTK positioning information, calculates the displacement of the preset sampling frequency based on the two consecutive positioning positions, and further calculates the average speed of the preset sampling frequency, compares the average speed with the standard speed threshold, obtains the speed error, and adjusts the weight parameter according to the size of the speed error. For example, if the speed error is too large, it means that the average speed of the preset sampling frequency calculated currently is inaccurate, which may be due to inaccurate RTK positioning information, and the weight parameter is reduced.

[0071] Step 208: If the confidence parameter satisfies the first preset condition and the weight parameter satisfies the second preset condition, calibrated positioning information is obtained according to the first positioning information and the second positioning information.

[0072] Among them, the first preset condition may be that the confidence parameter is not less than 50%, and the second preset condition may be that the weight parameter is not less than 0.6.

[0073] Optionally, the application processor continuously detects the confidence parameters of the DR positioning information and the weight parameters of the RTK positioning information. When the confidence parameters meet the first preset condition and the weight parameters meet the second preset condition, it is determined that the current DR positioning information and RTK positioning information are both valid positioning information. Then, the calibration positioning information is obtained based on the longitude, latitude, and altitude in the DR positioning information and the RTK positioning information.

[0074] In the above vehicle positioning calibration method, the first positioning information and the second positioning information obtained by multiple on-board electronic devices of the target vehicle are obtained; the cumulative error of the first positioning information is obtained, and the confidence parameter is adjusted according to the cumulative error; the speed error of the target vehicle is calculated according to the second positioning information, and the weight parameter is adjusted according to the speed error; if the confidence parameter meets the first preset condition and the weight parameter meets the second preset condition, the calibration positioning information is obtained according to the first positioning information and the second positioning information. By calculating the error size of different types of positioning information, adjusting the confidence or weight corresponding to each positioning information, and determining the effective positioning information in combination with the confidence and weight, and obtaining the calibration positioning information according to the effective positioning information, the accuracy of vehicle positioning can be improved.

[0075] In one embodiment, multiple vehicle-mounted electronic devices include at least a satellite signal receiving device, an inertial measurement device, and a network access device, and first positioning information and second positioning information obtained by multiple vehicle-mounted electronic devices of a target vehicle are obtained, including: obtaining original positioning data of the target vehicle obtained by the satellite signal receiving device, and six-axis data of the target vehicle obtained by the inertial measurement device; calculating the original three-dimensional position information of the target vehicle based on the six-axis data; obtaining the first positioning information based on the original three-dimensional position information and the original positioning data; and obtaining the second positioning information of the target vehicle obtained from a real-time dynamic measurement system through the network access device.

[0076] Optionally, the GNSS receiving device receives in real time original NMEA (National Marine Electronics Association, a standard format developed by marine electronic equipment) data that is unified by standard GNSS navigation equipment and sent by the GNSS (Global Navigation Satellite System) satellite constellation as original positioning data. In scenarios where there is signal obstruction, the original positioning data will have low data accuracy, invalid positioning data, and a large positioning point error range. After the application processor obtains the original NMEA data, it obtains the six-axis data of the target vehicle from the IMU, and uses a three-dimensional recursive algorithm to perform precision correction on the original NMEA data to obtain the first positioning information (i.e., DR positioning information).

[0077] Specifically, when the vehicle is stationary, the application processor records the six-axis data from the IMU and converts it into Euler angles through the Mahony complementary filter algorithm. The Euler angles are converted together with the acceleration information output by the accelerometer to the computer reference coordinate system. After an integral operation, three velocity components, i.e., three-dimensional velocity information, are obtained. Then, through a second integral operation, three position components (longitude, latitude, and altitude) are obtained, thereby obtaining the original three-dimensional position information. The original positioning data is corrected by the original three-dimensional position information to obtain the first positioning information.

[0078] Furthermore, the medical processor accesses the RTK system server of the positioning service provider through NAD to obtain the second positioning information (i.e., RTK positioning information) calculated by the RTK system for the current target vehicle. The RTK positioning information is the NMEA data obtained by the RTK system through the inter-satellite double difference model by differentially processing the original NMEA data sent by the GNSS satellite group, which is equivalent to the NMEA data corrected by RTK.

[0079] In this embodiment, the original positioning data of the target vehicle obtained by the satellite signal receiving device and the six-axis data of the target vehicle obtained by the inertial measurement device are obtained; the original three-dimensional position information of the target vehicle is calculated based on the six-axis data; the first positioning information is obtained based on the original three-dimensional position information and the original positioning data; and the second positioning information of the target vehicle obtained from the real-time dynamic measurement system through the network access device is obtained. The two different types of positioning information can be obtained, which is convenient for improving the accuracy of vehicle positioning.

[0080] In one embodiment, the accumulated error of the first positioning information is obtained, and the confidence parameter is adjusted according to the accumulated error, including: if the accumulated error is greater than or equal to an error threshold, the confidence parameter is lowered.

[0081] Optionally, the application processor continuously detects the cumulative error of the DR positioning information. When the cumulative errors detected for multiple consecutive times are greater than or equal to the error threshold, the confidence parameter is lowered, thereby reducing the impact of the DR positioning information with large errors on the final positioning. For example, the application processor continuously detects the cumulative error of the DR positioning information according to a preset detection period. When the cumulative error detected for 10 consecutive times is greater than or equal to the error threshold, the confidence parameter is lowered. This is because the gyroscope zero bias in the IMU drifts over time, so it is necessary to correct the GNSS raw data based on the cumulative error in the gyroscope. However, when the GNSS receiving device cannot receive the GNSS signal (original NMEA data), it is impossible to correct the IMU cumulative error, resulting in the error of the DR positioning information accumulating over time, and there will also be cumulative errors.

[0082] Specifically, the confidence of DR positioning information is calculated, and the frequency of GNSS signal is 10hz. The IMU update frequency is the standard frequency of 30khz, and the ratio is 1:3000, that is, after the IMU outputs 3k times, the GNSS signal will be calibrated once. In the three-dimensional trajectory calculation of DR positioning information, it is necessary to continuously correct the initial heading angle in the recursive formula when the GNSS outputs, so as to update t to 0 and reduce the accumulation of noise errors caused by time. According to this method, if the IMU outputs 3k data for 1 second continuously, the GNSS data (10 times) is in an invalid state and the accumulated error cannot be corrected. After the accumulated error exceeds the preset error threshold, the confidence default value 1 will decrease by 0.01.

[0083] In a feasible implementation, the application processor continuously detects the cumulative error of the DR positioning information. When the cumulative error detected continuously for multiple times is smaller than the error threshold, the confidence parameter is increased and the confidence parameter reaches a maximum value.

[0084] In this embodiment, if the accumulated error is greater than or equal to the error threshold, the confidence parameter is reduced, which can reduce the impact of the first positioning information with a large error on the final positioning and improve the accuracy of vehicle positioning.

[0085] In one embodiment, the speed error of the target vehicle is calculated according to the second positioning information, and the weight parameter is adjusted according to the speed error, including: according to the second positioning information, obtaining the positioning of the target vehicle at multiple continuous moments at a preset time interval; calculating the measured speed of the target vehicle at the current continuous moment according to the positioning at the current continuous moment, the positioning at the previous continuous moment and the preset time interval; if the measured speed of the target vehicle at the current continuous moment is not within the standard speed threshold range, determining that the measured speed of the target vehicle at the current continuous moment is an abnormal speed; if the number of consecutive abnormal speed determinations exceeds the number threshold, reducing the weight parameter.

[0086] The standard speed threshold range is used to represent a reasonable speed range for normal vehicle driving.

[0087] Optionally, the application processor continuously obtains the position in the RTK positioning information and uses the RTK positioning to calculate the vehicle speed at the current moment. The formula is as follows:

[0088] v=||P k，GNSS -P k-1 || / Δt,

[0089] Among them, P k,GNSS and P k-1 They are the GNSS positioning at time k and the filtered positioning result at time k-1. The speeds of the two are compared. If v exceeds the standard speed threshold range (actual speed ± redundant value), it is considered that the RTK positioning error of this epoch is too large. After the above process is abnormal for 5 consecutive times, the weight parameter of the RTK positioning information is downgraded by 0.1.

[0090] In a feasible implementation, if the number of consecutive abnormal speed determinations does not exceed the number threshold, the weight parameter is increased, and the weight parameter has a maximum value. For example, if the current vehicle speed is calculated using RTK positioning for 5 consecutive times, and there is one time when the speed is within the standard speed threshold, the weight parameter of the RTK positioning information is weighted and increased by 0.1.

[0091] In this embodiment, according to the second positioning information, the positioning of the target vehicle at multiple continuous moments is obtained according to the preset time interval; according to the positioning at the current continuous moment, the positioning at the previous continuous moment and the preset time interval, the measured speed of the target vehicle at the current continuous moment is calculated; if the measured speed of the target vehicle at the current continuous moment is not within the standard speed threshold range, the measured speed of the target vehicle at the current continuous moment is determined to be an abnormal speed; if the number of consecutive abnormal speed determinations exceeds the number threshold, the weight parameter is reduced. The influence of the second positioning information with a large error on the final positioning can be reduced, and the accuracy of vehicle positioning is improved.

[0092] In one embodiment, calibration positioning information is obtained based on the first positioning information and the second positioning information, including: obtaining first three-dimensional positioning information from the first positioning information, the first three-dimensional positioning information including a first longitude, a first latitude and a first altitude; obtaining second three-dimensional positioning information from the second positioning information, the second three-dimensional positioning information including a second longitude, a second latitude and a second altitude; filtering the first longitude and the second longitude through a federal Kalman filter to obtain a fused longitude, filtering the first latitude and the second latitude to obtain a fused latitude, and filtering the first altitude and the second altitude to obtain a fused altitude; using the fused longitude, the fused latitude and the fused altitude as fused three-dimensional positioning information, and replacing the first three-dimensional positioning information in the first positioning information with the fused three-dimensional positioning information, to obtain calibration positioning information.

[0093] Optionally, the application processor obtains the first three-dimensional position information (first longitude, first latitude, and first altitude) in the DR positioning information and the second three-dimensional position information (second longitude, second latitude, and second altitude) in the RTK positioning information, and performs a federal Kalman filter on the longitude, latitude, and altitude respectively, that is, performs three federal Kalman filters.

[0094] The federated Kalman filter vector state is: δNk, δEk, δSk, are the north and east position errors, step length estimation error and heading estimation error respectively. Assuming that the step length and heading conform to the first-order Markov process, according to the DR principle, the system state equation is x k =Ax k-1 +Fω k .in, x k-1 is the state of the previous moment; F and ω k are the system noise matrix and system process noise respectively; is the heading angle at the current moment; ΔT is the sampling interval; T S , For the relevant time.

[0095] The system observation is the position difference between DR and RTK: Observation vector z k =[z n z e ]T,z n and z e They are the differences between the DR and RTK north and east positions, respectively.

[0096] The system observation equation is z k =Hx k +v k Where v k is the observation noise.

[0097] After three federated Kalman filters, the filtered fused longitude, fused latitude and fused altitude are output respectively to form the fused three-dimensional position information after the federated Kalman filter. Finally, the first three-dimensional position information in the DR positioning information is replaced with the fused three-dimensional position information feedback. The final fused positioning result is output as the final three-dimensional position positioning.

[0098] In this embodiment, the first three-dimensional position information is obtained from the first positioning information, and the first three-dimensional position information includes the first longitude, the first latitude and the first altitude; the second three-dimensional position information is obtained from the second positioning information, and the second three-dimensional position information includes the second longitude, the second latitude and the second altitude; the first longitude and the second longitude are filtered by the federal Kalman filter to obtain the fused longitude, the first latitude and the second latitude are filtered to obtain the fused latitude, and the first altitude and the second altitude are filtered to obtain the fused altitude; the fused longitude, the fused latitude and the fused altitude are used as the fused three-dimensional position information, and the fused three-dimensional position information replaces the first three-dimensional position information in the first positioning information to obtain the calibrated positioning information. The three-dimensional position information in the effective positioning information can be Kalman filtered to obtain the filtered three-dimensional position information, and the filtered three-dimensional position information is used to obtain the calibrated positioning information, thereby improving the accuracy of vehicle positioning.

[0099] In one embodiment, the method further includes: acquiring third positioning information of at least three roadside devices corresponding to the target vehicle.

[0100] Among them, roadside equipment refers to the roadside unit (RSU), which is a device installed on the roadside in V2X (vehicle to everything, that is, vehicle-to-external information exchange), using cellular vehicle-to-everything (C-V2X) technology to communicate with the on-board unit (OBU) to achieve vehicle identity recognition. Roadside equipment can be a vehicle or an electronic device installed on the roadside.

[0101] Optionally, the application processor obtains the roadside positioning information of three roadside devices corresponding to the target vehicle respectively through the communication device, and calculates the third positioning information of the target vehicle based on the three roadside positioning information.

[0102] Specifically, the communication device can be a PC5 communication chip (V2X communication chip). The application processor communicates through PC5 (ProSe5 proximity communication is a form of radio communication) to receive high-precision positioning (latitude and longitude, altitude, 3-axis acceleration, confidence, etc.) in the basic safety information of BSM (Basic Safety Message) sent by other roadside equipment (stationary V2X terminal vehicles or V2X roadside facilities). According to the principle of geometry, N+1 points are selected to determine the N-dimensional space, so the 3D position information needs to be determined. In addition to the positioning vehicle, the roadside three-dimensional position information of at least 3 additional V2X devices is required. Each roadside three-dimensional position information includes longitude, latitude and altitude.

[0103] The target vehicle position is determined by calculating the distance between the target vehicle and the three RSUs. The specific formula is as follows:

[0104] Where, X a , Y a , Z a is the longitude, latitude and altitude coordinates (three-dimensional position information) of the target vehicle, X1, Y1, Z1, X2, Y2, Z2 and X3, Y3, Z3 are the three-dimensional position information of the three roadside devices. The distances d1, d2 and d3 between the three roadside devices and the target vehicle are obtained. The application processor calculates X a , Y a , Z a , which is the third positioning information.

[0105] In the V2X system, the application processor can obtain the real-time antenna signal RSSI value, antenna RF gain value, and V2X system real-time frequency through the network access layer interface API provided by the chip manufacturer, and use the theoretical model to calculate the speed and distance. It can also use the TDOA (Time Difference Of Arrival) measurement method to measure the signal arrival time, and then use the above formula for ranging.

[0106] In this embodiment, the third positioning information of at least three roadside devices corresponding to the target vehicle is obtained. The positioning information of the target vehicle can be obtained based on the V2X system, which is convenient for obtaining the positioning of the target vehicle in the scenario where the NAD cannot access the network and the GNSS has no signal, thereby improving the accuracy of vehicle positioning.

[0107] In one embodiment, the method further includes: if the confidence parameter satisfies a first preset condition and the weight parameter does not satisfy a second preset condition, acquiring calibration positioning information according to the first positioning information and the third positioning information.

[0108] If the confidence parameter does not meet the first preset condition and the weight parameter meets the second preset condition, the calibration positioning information is obtained according to the second positioning information and the third positioning information. If the confidence parameter does not meet the first preset condition and the weight parameter does not meet the second preset condition, the third positioning information is used as the calibration positioning information.

[0109] Optionally, if the confidence parameter meets the first preset condition, and the weight parameter does not meet the second preset condition, it means that the current road environment has a situation where the NAD cannot access the network and cannot receive the RTK system positioning. At this time, the accuracy of the RTK positioning information is low, so the RTK positioning information cannot be used as valid positioning information, and the DR positioning information and the third positioning information are used as valid positioning information, and the calibration positioning information is obtained based on the first positioning information and the third positioning information. If the confidence parameter does not meet the first preset condition, and the weight parameter meets the second preset condition, it means that the current road environment has a situation where the GNSS has no signal and the IMU cumulative error is large. At this time, the accuracy of the DR positioning information is low, so the DR positioning information cannot be used as valid positioning information, and the RTK positioning information and the third positioning information are used as valid positioning information, and the calibration positioning information is obtained based on the second positioning information and the third positioning information. If the confidence parameter does not meet the first preset condition, and the weight parameter does not meet the second preset condition, it means that the current road environment is such that NAD cannot access the network and GNSS has no signal, and it is impossible to receive RTK system positioning, and the IMU cumulative error is also large. At this time, the accuracy of DR positioning information and RTK positioning information are both low. Therefore, neither DR positioning information nor RTK positioning information can be used as valid positioning information. Only the third positioning information is used as valid positioning information, and the third positioning information is directly output as calibration positioning information.

[0110] In this embodiment, by calculating the error size of different types of positioning information, adjusting the confidence or weight corresponding to each type of positioning information, and determining the effective positioning information in combination with the confidence and weight, and obtaining the calibrated positioning information based on the effective positioning information, the accuracy of vehicle positioning can be improved.

[0111] In one embodiment, Figure 3 As shown, a vehicle positioning calibration method includes:

[0112] Obtain the original positioning data of the target vehicle obtained by the satellite signal receiving device and the six-axis data of the target vehicle obtained by the inertial measurement device; calculate the original three-dimensional position information of the target vehicle based on the six-axis data; obtain the first positioning information based on the original three-dimensional position information and the original positioning data; obtain the second positioning information of the target vehicle obtained from the real-time dynamic measurement system through the network access device. Obtain the third positioning information of at least three roadside devices corresponding to the target vehicle.

[0113] The accumulated error of the first positioning information is obtained, and if the accumulated error is greater than or equal to the error threshold, the confidence parameter is reduced.

[0114] According to the second positioning information, the positioning of the target vehicle at multiple continuous moments is obtained according to a preset time interval; according to the positioning at the current continuous moment, the positioning at the previous continuous moment and the preset time interval, the measured speed of the target vehicle at the current continuous moment is calculated; if the measured speed of the target vehicle at the current continuous moment is not within the standard speed threshold range, the measured speed of the target vehicle at the current continuous moment is determined to be an abnormal speed; if the number of consecutive abnormal speed determinations exceeds the number threshold, the weight parameter is reduced.

[0115] If the confidence parameter meets the first preset condition and the weight parameter meets the second preset condition, the first three-dimensional position information is obtained from the first positioning information, and the first three-dimensional position information includes the first longitude, the first latitude and the first altitude; the second three-dimensional position information is obtained from the second positioning information, and the second three-dimensional position information includes the second longitude, the second latitude and the second altitude; the first longitude and the second longitude are filtered by a federal Kalman filter to obtain a fused longitude, the first latitude and the second latitude are filtered to obtain a fused latitude, and the first altitude and the second altitude are filtered to obtain a fused altitude; the fused longitude, the fused latitude and the fused altitude are used as the fused three-dimensional position information, and the fused three-dimensional position information replaces the first three-dimensional position information in the first positioning information to obtain the calibrated positioning information.

[0116] If the confidence parameter satisfies the first preset condition and the weight parameter does not meet the second preset condition, the first three-dimensional position information is obtained from the first positioning information, and the first three-dimensional position information includes the first longitude, the first latitude and the first altitude; the third three-dimensional position information is obtained from the third positioning information, and the third three-dimensional position information includes the third longitude, the third latitude and the third altitude; the first longitude and the third longitude are filtered by a federal Kalman filter to obtain a fused longitude, the first latitude and the third latitude are filtered to obtain a fused latitude, and the first altitude and the third altitude are filtered to obtain a fused altitude; the fused longitude, the fused latitude and the fused altitude are used as the fused three-dimensional position information, and the fused three-dimensional position information replaces the first three-dimensional position information in the first positioning information to obtain the calibrated positioning information.

[0117] If the confidence parameter does not meet the first preset condition and the weight parameter meets the second preset condition, obtain third three-dimensional position information from the third positioning information, the third three-dimensional position information including the third longitude, the third latitude and the third altitude; obtain second three-dimensional positioning information from the second positioning information, the second three-dimensional position information including the second longitude, the second latitude and the second altitude; filter the third longitude and the second longitude through a federal Kalman filter to obtain a fused longitude, filter the third latitude and the second latitude to obtain a fused latitude, and filter the third altitude and the second altitude to obtain a fused altitude; use the fused longitude, the fused latitude and the fused altitude as the fused three-dimensional position information, and replace the first three-dimensional position information in the first positioning information with the fused three-dimensional position information to obtain the calibrated positioning information.

[0118] If the confidence parameter does not meet the first preset condition and the weight parameter does not meet the second preset condition, the third positioning information is used as the calibration positioning information.

[0119] In road scenarios where different positioning data sources fail, different calculation methods can be used to calculate effective positioning data, calibrate the vehicle's positioning, and ensure the accuracy of the vehicle's positioning in different road scenarios.

[0120] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0121] Based on the same inventive concept, the embodiment of the present application also provides a vehicle positioning calibration device for implementing the vehicle positioning calibration method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more vehicle positioning calibration device embodiments provided below can refer to the limitations of the vehicle positioning calibration method above, and will not be repeated here.

[0122] In one embodiment, Figure 4 As shown, a vehicle positioning calibration device 400 is provided, comprising: a positioning acquisition module 401, a first adjustment module 402, a second adjustment module 403 and a positioning calibration module 404, wherein:

[0123] A positioning acquisition module 401 is used to acquire first positioning information and second positioning information obtained by a plurality of vehicle-mounted electronic devices of a target vehicle;

[0124] A first adjustment module 402, configured to obtain a cumulative error of the first positioning information and adjust a confidence parameter according to the cumulative error;

[0125] A second adjustment module 403 is used to calculate a speed error of the target vehicle according to the second positioning information, and adjust a weight parameter according to the speed error;

[0126] The positioning calibration module 404 is used to obtain calibration positioning information according to the first positioning information and the second positioning information if the confidence parameter meets the first preset condition and the weight parameter meets the second preset condition.

[0127] In one embodiment, the plurality of vehicle-mounted electronic devices include at least a satellite signal receiving device, an inertial measurement device, and a network access device. The positioning acquisition module 401 is also used to obtain the original positioning data of the target vehicle obtained by the satellite signal receiving device, and the six-axis data of the target vehicle obtained by the inertial measurement device; calculate the original three-dimensional position information of the target vehicle based on the six-axis data; obtain the first positioning information based on the original three-dimensional position information and the original positioning data; and obtain the second positioning information of the target vehicle obtained from the real-time dynamic measurement system through the network access device.

[0128] In one embodiment, the first adjustment module 402 is further configured to reduce the confidence parameter if the accumulated error is greater than or equal to the error threshold.

[0129] In one embodiment, the second adjustment module 403 is also used to obtain the positioning of the target vehicle at multiple continuous moments according to the second positioning information at a preset time interval; calculate the measured speed of the target vehicle at the current continuous moment according to the positioning at the current continuous moment, the positioning at the previous continuous moment and the preset time interval; if the measured speed of the target vehicle at the current continuous moment is not within the standard speed threshold range, determine that the measured speed of the target vehicle at the current continuous moment is an abnormal speed; if the number of consecutive abnormal speed determinations exceeds the number threshold, reduce the weight parameter.

[0130] In one embodiment, the positioning calibration module 404 is also used to obtain first three-dimensional position information from the first positioning information, the first three-dimensional position information including a first longitude, a first latitude and a first altitude; obtain second three-dimensional positioning information from the second positioning information, the second three-dimensional position information including a second longitude, a second latitude and a second altitude; filter the first longitude and the second longitude by a federal Kalman filter to obtain a fused longitude, filter the first latitude and the second latitude to obtain a fused latitude, and filter the first altitude and the second altitude to obtain a fused altitude; use the fused longitude, the fused latitude and the fused altitude as fused three-dimensional position information, and replace the first three-dimensional position information in the first positioning information with the fused three-dimensional position information to obtain calibrated positioning information.

[0131] In one embodiment, the positioning acquisition module 401 is further used to acquire third positioning information of at least three roadside devices corresponding to the target vehicle.

[0132] In one embodiment, the positioning calibration module 404 is further configured to obtain calibration positioning information according to the first positioning information and the third positioning information if the confidence parameter satisfies a first preset condition and the weight parameter does not satisfy a second preset condition.

[0133] In one embodiment, the positioning calibration module 404 is further configured to obtain calibration positioning information according to the second positioning information and the third positioning information if the confidence parameter does not satisfy the first preset condition and the weight parameter satisfies the second preset condition.

[0134] In one embodiment, the positioning calibration module 404 is further configured to use the third positioning information as calibration positioning information if the confidence parameter does not satisfy the first preset condition and the weight parameter does not satisfy the second preset condition.

[0135] Each module in the above vehicle positioning and calibration device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each module.

[0136] In one embodiment, a computer device is provided. The computer device may be a vehicle-mounted T-BOX (Telematics BOX) or a vehicle-mounted terminal device with a network function and a V2X function. The internal structure diagram thereof may be as follows: Figure 5As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store positioning data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a vehicle positioning calibration method is implemented.

[0137] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0138] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: obtaining first positioning information and second positioning information obtained by multiple vehicle-mounted electronic devices of a target vehicle; obtaining a cumulative error of the first positioning information, and adjusting a confidence parameter according to the cumulative error; calculating a speed error of the target vehicle according to the second positioning information, and adjusting a weight parameter according to the speed error; if the confidence parameter meets a first preset condition and the weight parameter meets a second preset condition, obtaining calibration positioning information according to the first positioning information and the second positioning information.

[0139] In one embodiment, multiple vehicle-mounted electronic devices include at least a satellite signal receiving device, an inertial measurement device and a network access device. When the processor executes the computer program, the following steps are also implemented: obtaining original positioning data of the target vehicle obtained through the satellite signal receiving device, and six-axis data of the target vehicle obtained through the inertial measurement device; calculating the original three-dimensional position information of the target vehicle based on the six-axis data; obtaining first positioning information based on the original three-dimensional position information and the original positioning data; and obtaining second positioning information of the target vehicle obtained from the real-time dynamic measurement system through the network access device.

[0140] In one embodiment, when the processor executes the computer program, the following steps are further implemented: if the accumulated error is greater than or equal to the error threshold, the confidence parameter is reduced.

[0141] In one embodiment, the processor further implements the following steps when executing the computer program: obtaining the positioning of the target vehicle at multiple continuous moments according to a preset time interval based on the second positioning information; calculating the measured speed of the target vehicle at the current continuous moment based on the positioning at the current continuous moment, the positioning at the previous continuous moment and the preset time interval; if the measured speed of the target vehicle at the current continuous moment is not within the standard speed threshold range, determining that the measured speed of the target vehicle at the current continuous moment is an abnormal speed; if the number of consecutive abnormal speed determinations exceeds the number threshold, reducing the weight parameter.

[0142] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining first three-dimensional position information from the first positioning information, the first three-dimensional position information including a first longitude, a first latitude and a first altitude; obtaining second three-dimensional position information from the second positioning information, the second three-dimensional position information including a second longitude, a second latitude and a second altitude; filtering the first longitude and the second longitude through a federal Kalman filter to obtain a fused longitude, filtering the first latitude and the second latitude to obtain a fused latitude, and filtering the first altitude and the second altitude to obtain a fused altitude; using the fused longitude, the fused latitude and the fused altitude as fused three-dimensional position information, and replacing the first three-dimensional position information in the first positioning information with the fused three-dimensional position information to obtain calibrated positioning information.

[0143] In one embodiment, when the processor executes the computer program, the following steps are further implemented: obtaining third positioning information of at least three roadside devices corresponding to the target vehicle.

[0144] In one embodiment, when the processor executes the computer program, the following steps are also implemented: if the confidence parameter meets the first preset condition and the weight parameter does not meet the second preset condition, calibration positioning information is obtained according to the first positioning information and the third positioning information.

[0145] In one embodiment, when the processor executes the computer program, the following steps are also implemented: if the confidence parameter does not meet the first preset condition and the weight parameter meets the second preset condition, calibration positioning information is obtained according to the second positioning information and the third positioning information.

[0146] In one embodiment, when the processor executes the computer program, the following steps are also implemented: if the confidence parameter does not meet the first preset condition and the weight parameter does not meet the second preset condition, the third positioning information is used as the calibration positioning information.

[0147] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented: obtaining first positioning information and second positioning information obtained by multiple on-board electronic devices of a target vehicle; obtaining a cumulative error of the first positioning information, and adjusting a confidence parameter according to the cumulative error; calculating a speed error of the target vehicle according to the second positioning information, and adjusting a weight parameter according to the speed error; if the confidence parameter meets a first preset condition and the weight parameter meets a second preset condition, obtaining calibration positioning information according to the first positioning information and the second positioning information.

[0148] In one embodiment, multiple vehicle-mounted electronic devices include at least a satellite signal receiving device, an inertial measurement device and a network access device. When the computer program is executed by the processor, the following steps are also implemented: obtaining original positioning data of the target vehicle obtained through the satellite signal receiving device, and six-axis data of the target vehicle obtained through the inertial measurement device; calculating the original three-dimensional position information of the target vehicle based on the six-axis data; obtaining first positioning information based on the original three-dimensional position information and the original positioning data; and obtaining second positioning information of the target vehicle obtained from the real-time dynamic measurement system through the network access device.

[0149] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: if the accumulated error is greater than or equal to the error threshold, the confidence parameter is reduced.

[0150] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: according to the second positioning information, the positioning of the target vehicle at multiple continuous moments is obtained according to a preset time interval; according to the positioning at the current continuous moment, the positioning at the previous continuous moment and the preset time interval, the measured speed of the target vehicle at the current continuous moment is calculated; if the measured speed of the target vehicle at the current continuous moment is not within the standard speed threshold range, the measured speed of the target vehicle at the current continuous moment is determined to be an abnormal speed; if the number of consecutive abnormal speed determinations exceeds the number threshold, the weight parameter is reduced.

[0151] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining first three-dimensional position information from the first positioning information, the first three-dimensional position information including a first longitude, a first latitude and a first altitude; obtaining second three-dimensional position information from the second positioning information, the second three-dimensional position information including a second longitude, a second latitude and a second altitude; filtering the first longitude and the second longitude by a federal Kalman filter to obtain a fused longitude, filtering the first latitude and the second latitude to obtain a fused latitude, and filtering the first altitude and the second altitude to obtain a fused altitude; using the fused longitude, the fused latitude and the fused altitude as fused three-dimensional position information, and replacing the first three-dimensional position information in the first positioning information with the fused three-dimensional position information to obtain calibrated positioning information.

[0152] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining third positioning information of at least three roadside devices corresponding to the target vehicle.

[0153] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the confidence parameter meets the first preset condition and the weight parameter does not meet the second preset condition, calibrated positioning information is obtained according to the first positioning information and the third positioning information.

[0154] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the confidence parameter does not meet the first preset condition and the weight parameter meets the second preset condition, calibration positioning information is obtained according to the second positioning information and the third positioning information.

[0155] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the confidence parameter does not meet the first preset condition and the weight parameter does not meet the second preset condition, the third positioning information is used as the calibration positioning information.

[0156] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps: obtaining first positioning information and second positioning information obtained by multiple on-board electronic devices of a target vehicle; obtaining a cumulative error of the first positioning information, and adjusting a confidence parameter according to the cumulative error; calculating a speed error of the target vehicle according to the second positioning information, and adjusting a weight parameter according to the speed error; if the confidence parameter satisfies a first preset condition and the weight parameter satisfies a second preset condition, obtaining calibration positioning information according to the first positioning information and the second positioning information.

[0157] In one embodiment, multiple vehicle-mounted electronic devices include at least a satellite signal receiving device, an inertial measurement device and a network access device. When the computer program is executed by the processor, the following steps are also implemented: obtaining original positioning data of the target vehicle obtained through the satellite signal receiving device, and six-axis data of the target vehicle obtained through the inertial measurement device; calculating the original three-dimensional position information of the target vehicle based on the six-axis data; obtaining first positioning information based on the original three-dimensional position information and the original positioning data; and obtaining second positioning information of the target vehicle obtained from the real-time dynamic measurement system through the network access device.

[0158] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: if the accumulated error is greater than or equal to the error threshold, the confidence parameter is reduced.

[0159] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: according to the second positioning information, the positioning of the target vehicle at multiple continuous moments is obtained according to a preset time interval; according to the positioning at the current continuous moment, the positioning at the previous continuous moment and the preset time interval, the measured speed of the target vehicle at the current continuous moment is calculated; if the measured speed of the target vehicle at the current continuous moment is not within the standard speed threshold range, the measured speed of the target vehicle at the current continuous moment is determined to be an abnormal speed; if the number of consecutive abnormal speed determinations exceeds the number threshold, the weight parameter is reduced.

[0160] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining first three-dimensional position information from the first positioning information, the first three-dimensional position information including a first longitude, a first latitude and a first altitude; obtaining second three-dimensional position information from the second positioning information, the second three-dimensional position information including a second longitude, a second latitude and a second altitude; filtering the first longitude and the second longitude by a federal Kalman filter to obtain a fused longitude, filtering the first latitude and the second latitude to obtain a fused latitude, and filtering the first altitude and the second altitude to obtain a fused altitude; using the fused longitude, the fused latitude and the fused altitude as fused three-dimensional position information, and replacing the first three-dimensional position information in the first positioning information with the fused three-dimensional position information to obtain calibrated positioning information.

[0161] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining third positioning information of at least three roadside devices corresponding to the target vehicle.

[0162] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the confidence parameter meets the first preset condition and the weight parameter does not meet the second preset condition, calibrated positioning information is obtained according to the first positioning information and the third positioning information.

[0163] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the confidence parameter does not meet the first preset condition and the weight parameter meets the second preset condition, calibration positioning information is obtained according to the second positioning information and the third positioning information.

[0164] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: if the confidence parameter does not meet the first preset condition and the weight parameter does not meet the second preset condition, the third positioning information is used as the calibration positioning information.

[0165] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0166] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0167] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0168] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle positioning calibration method, characterized in that: The method comprises: Acquire first positioning information and second positioning information obtained by a plurality of on-board electronic devices of a target vehicle; the first positioning information is vehicle dead reckoning positioning information, and the second positioning information is real-time dynamic measurement positioning information; Acquire a cumulative error of the first positioning information, and adjust a confidence parameter according to the cumulative error; Calculating a speed error of the target vehicle according to the second positioning information, and adjusting a weight parameter according to the speed error; If the confidence parameter satisfies a first preset condition and the weight parameter satisfies a second preset condition, obtaining calibration positioning information according to the first positioning information and the second positioning information; Acquire roadside positioning information of at least three roadside devices corresponding to the target vehicle, and calculate the third positioning information of the target vehicle according to the three roadside positioning information; If the confidence parameter satisfies a first preset condition and the weight parameter does not satisfy a second preset condition, calibration positioning information is acquired according to the first positioning information and the third positioning information.

2. The method according to claim 1, characterized in that The plurality of vehicle-mounted electronic devices at least include a satellite signal receiving device, an inertial measurement device, and a network access device, and the step of acquiring the first positioning information and the second positioning information obtained by the plurality of vehicle-mounted electronic devices of the target vehicle includes: Acquire the original positioning data of the target vehicle obtained by the satellite signal receiving device, and the six-axis data of the target vehicle obtained by the inertial measurement device; Calculating the original three-dimensional position information of the target vehicle according to the six-axis data; Obtaining the first positioning information according to the original three-dimensional position information and the original positioning data; Acquire the second positioning information of the target vehicle obtained from the real-time dynamic measurement system through the network access device.

3. The method according to claim 1, characterized in that The obtaining the accumulated error of the first positioning information and adjusting the confidence parameter according to the accumulated error includes: If the accumulated error is greater than or equal to an error threshold, the confidence parameter is reduced.

4. The method according to claim 1, characterized in that: The calculating the speed error of the target vehicle according to the second positioning information, and adjusting the weight parameter according to the speed error, comprises: According to the second positioning information, obtaining the positioning of the target vehicle at multiple consecutive moments at preset time intervals; Calculate the measured speed of the target vehicle at the current continuous moment according to the positioning at the current continuous moment, the positioning at the previous continuous moment and the preset time interval; If the measured speed of the target vehicle at the current continuous moment is not within the standard speed threshold range, determining that the measured speed of the target vehicle at the current continuous moment is an abnormal speed; If the number of consecutive abnormal speed determinations exceeds a number threshold, the weight parameter is reduced.

5. The method according to claim 1, characterized in that The acquiring calibration positioning information according to the first positioning information and the second positioning information includes: Acquire first three-dimensional position information from the first positioning information, where the first three-dimensional position information includes a first longitude, a first latitude, and a first altitude; Acquire second three-dimensional position information from the second positioning information, where the second three-dimensional position information includes a second longitude, a second latitude, and a second altitude; filtering the first longitude and the second longitude by a federal Kalman filter to obtain a fused longitude, filtering the first latitude and the second latitude to obtain a fused latitude, and filtering the first altitude and the second altitude to obtain a fused altitude; The fused longitude, fused latitude and fused altitude are used as fused three-dimensional position information, and the fused three-dimensional position information replaces the first three-dimensional position information in the first positioning information to obtain the calibrated positioning information.

6. The method according to claim 1, characterized in that The method further comprises: If the confidence parameter does not satisfy the first preset condition and the weight parameter satisfies the second preset condition, calibration positioning information is acquired according to the second positioning information and the third positioning information.

7. The method according to claim 1, characterized in that The method further comprises: If the confidence parameter does not meet the first preset condition and the weight parameter does not meet the second preset condition, the third positioning information is used as calibration positioning information.

8. A vehicle positioning and calibration device, characterized in that: The device comprises: A positioning acquisition module, used to acquire first positioning information and second positioning information obtained by multiple on-board electronic devices of the target vehicle; the first positioning information is vehicle dead reckoning positioning information, and the second positioning information is real-time dynamic measurement positioning information; A first adjustment module, configured to obtain a cumulative error of the first positioning information and adjust a confidence parameter according to the cumulative error; A second adjustment module, used for calculating a speed error of the target vehicle according to the second positioning information, and adjusting a weight parameter according to the speed error; A positioning calibration module is used to obtain calibration positioning information based on the first positioning information and the second positioning information if the confidence parameter meets the first preset condition and the weight parameter meets the second preset condition; obtain roadside positioning information of at least three roadside devices corresponding to the target vehicle, and calculate the third positioning information of the target vehicle based on the three roadside positioning information; if the confidence parameter meets the first preset condition and the weight parameter does not meet the second preset condition, obtain calibration positioning information based on the first positioning information and the third positioning information.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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