Method, device, electronic equipment, and computer program product for calibrating heading angle of autonomous driving vehicle

Abstract

The present application discloses a heading angle calibration method, device, electronic device, and computer program product for an autonomous driving vehicle, the method comprising: obtaining the current positioning information sent by the RTK positioning device of the autonomous driving vehicle, the current positioning information including a first heading angle and a current position; converting the current position to a predefined coordinate system, the predefined coordinate system being a local coordinate system constructed with the first frame of positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin; calculating the second heading angle according to the current position and the historical position in the predefined coordinate system; determining the heading angle calibration result according to the heading angle deviation between the first heading angle and the second heading angle. The present application converts the calibration information to a local coordinate system constructed with the first frame of positioning data collected by the autonomous driving vehicle at the starting point as the origin, so that the calibration result is not subject to geographical restrictions, does not require recalibration across cities, improves the heading angle calibration efficiency, and reduces the calibration cost.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a heading angle calibration method, device, electronic equipment, and computer program product for an autonomous driving vehicle. Background Art

[0002] In the field of autonomous driving, it is crucial to accurately obtain the vehicle's real-time heading angle. This parameter is directly related to the accuracy of the perception system, the rationality of path planning, and the stability of vehicle control, which in turn profoundly affects the overall safety and reliability of autonomous driving. Therefore, efficient and accurate calibration of the vehicle's heading angle has become an indispensable part of ensuring autonomous driving performance.

[0003] The traditional heading angle calibration scheme relies on the UTM (Universal Transverse Mercator) coordinate system. This scheme usually converts geographic coordinates (latitude, longitude, elevation, or LLH) directly into UTM coordinates. However, an inherent characteristic of the UTM coordinate system is that it is based on a zone design, and each zone is set with a specific center point, which means that the accuracy of the calibration is highly dependent on the position of the vehicle relative to the center point. The closer the vehicle is to the center point, the higher the accuracy of the calibration result. However, due to the different geographical locations of different cities and regions, the corresponding UTM zone center points also change accordingly, which leads to significant geographical limitations in the heading angle calibration results performed under the UTM coordinate system.

[0004] Specifically, when an autonomous driving vehicle needs to operate across multiple cities, the heading angle parameters originally calibrated in a certain city may not be directly applicable to other cities due to the different UTM center points corresponding to each city. This requires the autonomous driving system to recalibrate the heading angle when switching operations between different cities. This not only increases the complexity and time cost of the calibration work, but may also introduce additional error risks due to frequent adjustments, posing a potential threat to the continuity and safety of autonomous driving. Therefore, exploring a new method that can cross city boundaries and achieve high-precision and unified calibration of heading angles has become a key issue that needs to be urgently addressed in the field of autonomous driving technology. Summary of the invention

[0005] The embodiments of the present application provide a method, device, electronic device, and computer program product for calibrating the heading angle of an autonomous driving vehicle to improve the calibration efficiency of the heading angle of the autonomous driving vehicle and solve the problem of recalibration across cities.

[0006] The present application embodiment adopts the following technical solutions:

[0007] In a first aspect, an embodiment of the present application provides a heading angle calibration method for an autonomous driving vehicle, wherein the heading angle calibration method for an autonomous driving vehicle includes:

[0008] Acquire current positioning information sent by an RTK positioning device of the autonomous driving vehicle, wherein the current positioning information includes a first heading angle and a current position;

[0009] Convert the current position to a predefined coordinate system to obtain the current position in the predefined coordinate system, where the predefined coordinate system is a local coordinate system constructed with the first frame positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin;

[0010] Calculating a second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system;

[0011] A heading angle calibration result of the automatic driving vehicle is determined based on a heading angle deviation between the first heading angle and the second heading angle.

[0012] Optionally, the acquiring current positioning information sent by an RTK positioning device of the autonomous driving vehicle includes:

[0013] Get the current speed of the autonomous vehicle and the current positioning status of the RTK positioning device;

[0014] Determining whether the autonomous driving vehicle meets a preset calibration condition according to the current speed and the current positioning state;

[0015] When the preset calibration conditions are met, the current positioning information sent by the RTK positioning device of the autonomous driving vehicle is obtained.

[0016] Optionally, the calculating the second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system includes:

[0017] Calculate the relative distance based on the current position in the predefined coordinate system and the historical position in the predefined coordinate system;

[0018] Determining whether a preset distance constraint condition is met according to the relative distance and a preset distance threshold;

[0019] When a preset distance constraint condition is met, a second heading angle is calculated according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system.

[0020] Optionally, determining a heading angle calibration result of the autonomous driving vehicle according to a heading angle deviation between the first heading angle and the second heading angle includes:

[0021] Calculate a heading angle deviation between the first heading angle and the second heading angle of multiple frames;

[0022] Performing sliding filtering processing on the heading angle deviation between the first heading angle and the second heading angle of multiple frames to obtain the heading angle deviation after sliding filtering;

[0023] The final heading angle calibration result of the automatic driving vehicle is determined according to the heading angle deviation after the sliding filter.

[0024] Optionally, determining a final heading angle calibration result of the automatic driving vehicle according to the heading angle deviation after the sliding filter includes:

[0025] Counting the second heading angle, and calculating the angle difference between the heading angle deviation after the sliding filter and the historical heading angle calibration result;

[0026] When the count of the second heading angle meets the preset counting threshold and the angle difference between the heading angle deviation after the sliding filter and the historical heading angle calibration result is not greater than the preset angle difference threshold, counting the heading angle deviation after the sliding filter;

[0027] Updating a heading angle calibration result of the automatic driving vehicle according to the heading angle deviation after sliding filtering and the count of the heading angle deviation after sliding filtering;

[0028] When the calibration end condition is met, the updated heading angle calibration result of the autonomous driving vehicle is used as the final heading angle calibration result.

[0029] Optionally, the heading angle calibration result is a heading angle calibration result in a predefined coordinate system, and the heading angle calibration method of the autonomous driving vehicle further includes:

[0030] Convert the heading angle calibration result in the predefined coordinate system to the UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system;

[0031] The heading angle calibration result in the UTM coordinate system is sent to the downstream module.

[0032] Optionally, converting the heading angle calibration result in the predefined coordinate system to a UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system includes:

[0033] Determine a current location of the autonomous driving vehicle, and determine the UTM zone center longitude of the current location based on the current location of the autonomous driving vehicle;

[0034] According to the UTM zone center longitude of the current location, the heading angle calibration result in the predefined coordinate system is converted to the UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system.

[0035] In a second aspect, an embodiment of the present application further provides a heading angle calibration device for an autonomous driving vehicle, wherein the heading angle calibration device for an autonomous driving vehicle comprises:

[0036] An acquisition unit, configured to acquire current positioning information sent by an RTK positioning device of the autonomous driving vehicle, wherein the current positioning information includes a first heading angle and a current position;

[0037] A first conversion unit is used to convert the current position into a predefined coordinate system to obtain the current position in the predefined coordinate system, where the predefined coordinate system is a local coordinate system constructed with the first frame positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin;

[0038] a calculation unit, configured to calculate a second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system;

[0039] A determination unit is used to determine a heading angle calibration result of the automatic driving vehicle according to a heading angle deviation between the first heading angle and the second heading angle.

[0040] In a third aspect, an embodiment of the present application further provides an electronic device, including:

[0041] A processor; and a memory arranged to store computer executable instructions, which, when executed, cause the processor to perform any of the aforementioned methods for calibrating the heading angle of the autonomous driving vehicle.

[0042] In a fourth aspect, an embodiment of the present application further provides a computer program product, comprising a computer program or instructions, which, when executed by a processor, implements any of the aforementioned methods for calibrating the heading angle of an autonomous driving vehicle.

[0043] At least one of the above-mentioned technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects: the heading angle calibration method of the autonomous driving vehicle in the embodiments of the present application first obtains the current positioning information sent by the RTK positioning device of the autonomous driving vehicle, and the current positioning information includes a first heading angle and a current position; then the current position is converted to a predefined coordinate system to obtain the current position in the predefined coordinate system, and the predefined coordinate system is a local coordinate system constructed with the first frame positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin; then the second heading angle is calculated according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system; finally, the heading angle calibration result of the autonomous driving vehicle is determined according to the heading angle deviation between the first heading angle and the second heading angle. During the heading angle calibration process of the autonomous driving vehicle in the embodiment of the present application, the calibration information used for calibration is converted into a local coordinate system constructed with the first frame positioning data collected by the autonomous driving vehicle at the starting point as the origin, so that the calibration result is not subject to geographical restrictions and can be applied to various cities and regions. There is no need to re-calibrate across cities, which improves the efficiency of heading angle calibration and reduces the calibration cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0045] Figure 1 A schematic diagram of a flow chart of a method for calibrating a heading angle of an autonomous driving vehicle in an embodiment of the present application;

[0046] Figure 2 This is a schematic diagram of the structure of a heading angle calibration device for an autonomous driving vehicle in an embodiment of the present application;

[0047] Figure 3 This is a schematic diagram of the structure of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0049] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0050] The present application embodiment provides a method for calibrating the heading angle of an autonomous driving vehicle, such as Figure 1 As shown, a flow chart of a method for calibrating a heading angle of an autonomous driving vehicle in an embodiment of the present application is provided. The method for calibrating a heading angle of an autonomous driving vehicle at least includes the following steps S110 to S140:

[0051] Step S110, obtaining current positioning information sent by the RTK positioning device of the autonomous driving vehicle, wherein the current positioning information includes a first heading angle and a current position.

[0052] When calibrating the heading angle of an autonomous vehicle, it is necessary to first obtain the current positioning information sent by the RTK positioning device of the autonomous vehicle. The current positioning information mainly includes the original heading angle and position information output by the RTK positioning device in real time. The heading angle originally output by the RTK positioning device may have deviations, so the embodiment of the present application needs to calibrate the size of this deviation. The RTK (Real-Time Kinematic) positioning device is a real-time dynamic positioning device based on carrier phase observations. It can provide three-dimensional positioning results of the measuring station in a specified coordinate system in real time, and achieve high accuracy at the centimeter level or even the millimeter level. Therefore, the embodiment of the present application calibrates the heading angle of the autonomous vehicle based on the positioning information collected by the RTK positioning device.

[0053] Step S120, converting the current position to a predefined coordinate system to obtain the current position in the predefined coordinate system, wherein the predefined coordinate system is a local coordinate system constructed with the first frame positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin.

[0054] The positioning information output by the RTK positioning device is generally the latitude, longitude and elevation information in the ENU coordinate system. The ENU coordinate system is a three-dimensional rectangular coordinate system, in which the X axis points to the east, the Y axis points to the north, and the Z axis points to the zenith (or the top, vertical direction). The ENU coordinate system in the autonomous driving scenario uses the current location of the autonomous driving vehicle as the coordinate origin, so it is also called the station center coordinate system or geographic coordinate system.

[0055] In traditional calibration schemes, the latitude, longitude and elevation information output by the RTK positioning device is generally converted to the UTM coordinate system and then the heading angle is calibrated. This is mainly to meet the usage requirements of downstream modules, but this method introduces the problem of recalibrating the heading angle in cross-city scenarios.

[0056] Based on this, the embodiment of the present application defines a new coordinate system, that is, the first frame of positioning data collected by the RTK positioning device of the autonomous driving vehicle at the starting point is used as the origin of the coordinate system to construct a local coordinate system, convert the current position collected in real time to the predefined coordinate system, and then perform calibration calculation of the heading angle. Since the origin of the coordinate system is always the position of the first frame of positioning data, it is not affected by changes in location during cross-city operations.

[0057] Step S130, calculating a second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system.

[0058] Furthermore, the embodiment of the present application also needs to obtain the historical position in a predefined coordinate system, where the historical position is, for example, the position of the previous frame, and then calculate the second heading angle based on the current position and the historical position in the predefined coordinate system. The second heading angle can be regarded as a heading angle calculated based on the position output by the RTK positioning device, which is different from the heading angle originally output by the above-mentioned RTK positioning device.

[0059] Step S140: Determine a heading angle calibration result of the automatic driving vehicle according to the heading angle deviation between the first heading angle and the second heading angle.

[0060] The deviation between the heading angle originally output by the RTK positioning device obtained according to the above steps and the heading angle obtained based on the position calculation can be calculated. By calculating and processing multiple frames of continuous data, the relatively stable deviation of the heading angle originally output by the RTK positioning device can be obtained as the final heading angle calibration result of the autonomous driving vehicle for downstream use.

[0061] During the heading angle calibration process of the autonomous driving vehicle in the embodiment of the present application, the calibration information used for calibration is converted into a local coordinate system constructed with the first frame positioning data collected by the autonomous driving vehicle at the starting point as the origin, so that the calibration result is not subject to geographical restrictions and can be applied to various cities and regions. There is no need to re-calibrate across cities, which improves the efficiency of heading angle calibration and reduces the calibration cost.

[0062] To facilitate understanding of the above embodiments, in some embodiments of the present application, the predefined coordinate system may adopt the North East Earth (NED) coordinate system, convert the longitude, latitude and altitude information into the North East Earth coordinate system and then perform subsequent heading angle calibration, which may be specifically implemented in the following manner:

[0063] if(abs(llh(0))>M_PI / 2.0f||abs(llh(1))>M_PI)

[0064] {

[0065] / / error("Latitude is limited to[pi / 2,-pi / 2](90,-90),longitude is limited to[pi,-pi]");

[0066] ecef->setZero();

[0067] return false;

[0068] }

[0069] / / llh:latitude,longitude,Hieght

[0070] T Lat = llh(0); / / Latitude

[0071] T Lon = llh(1); / / Longitude

[0072] T Alt = llh(2); / / Altitude

[0073] / / WGS84 model config

[0074] / / e=sqrt(WGS84_FLAT*(2-WGS84_FLAT));

[0075] / / e2=e^2;

[0076] T e2 = WGS84_FLAT*(2-WGS84_FLAT);

[0077] T v = WGS84_RAD / sqrt(1-e2*pow(sin(Lat),2));

[0078] (*ecef)(0) = (Alt+v)*cos(Lat)*cos(Lon);

[0079] (*ecef)(1) = (Alt+v)*cos(Lat)*sin(Lon);

[0080] (*ecef)(2) = (Alt+v*(1.0f-e2))*sin(Lat).

[0081] In some embodiments of the present application, obtaining the current positioning information sent by the RTK positioning device of the autonomous driving vehicle includes: obtaining the current speed of the autonomous driving vehicle and the current positioning status of the RTK positioning device; determining whether the autonomous driving vehicle meets preset calibration conditions based on the current speed and the current positioning status; and obtaining the current positioning information sent by the RTK positioning device of the autonomous driving vehicle when the preset calibration conditions are met.

[0082] Before calibrating the autonomous driving vehicle, the embodiment of the present application can also first determine whether the autonomous driving vehicle currently meets the calibration conditions. The judgment can be mainly based on the current speed of the autonomous driving vehicle and the current positioning status of the RTK positioning device. The size of the speed and the quality of the current positioning status will affect the accuracy and reliability of the calibration results.

[0083] Specifically, the current speed of the autonomous driving vehicle and the current positioning state of the RTK positioning device can be obtained first. If the current speed of the autonomous driving vehicle is greater than the preset speed threshold, and the current positioning state of the RTK positioning device is a differential state, then it can be considered that the autonomous driving vehicle currently meets the calibration requirements and the subsequent calibration process can be carried out. If the current speed of the autonomous driving vehicle is less than the preset speed threshold, such as 1m / s, direct calibration will result in a large calibration error due to the low speed, or if the current positioning state of the RTK positioning device is a non-differential state, it means that the current position collected by the RTK positioning device is inaccurate, and the result obtained by calibration based on this is also inaccurate. Therefore, the accuracy of heading angle calibration can be improved by constraining the calibration conditions.

[0084] Of course, the specific calibration conditions can be flexibly set by those skilled in the art according to actual needs, and no specific limitation is made here.

[0085] In some embodiments of the present application, calculating the second heading angle based on the current position in the predefined coordinate system and the historical position in the predefined coordinate system includes: calculating the relative distance based on the current position in the predefined coordinate system and the historical position in the predefined coordinate system; determining whether a preset distance constraint is met based on the relative distance and a preset distance threshold; and if the preset distance constraint is met, calculating the second heading angle based on the current position in the predefined coordinate system and the historical position in the predefined coordinate system.

[0086] In the embodiment of the present application, when calculating the second heading angle according to the current position and the historical position in the predefined coordinate system, the distance between the two position points can be first calculated according to the two position points, which can be specifically expressed as follows:

[0087] dp=|(sqrt((p1x-px_last)*(p1x-px_last)+(p1y-p1y_last)*(p1y-p1y_last)))|,

[0088] Wherein, dp is the distance between the current position and the historical position, sqrt represents the square root, p1x and p1y are the horizontal position and the vertical position in the current position p1, respectively, and px_last and p1y_last are the horizontal position and the vertical position in the previous frame position p_last. It should be added here that the embodiment of the present application can count the positioning information sent by RTK msg_cnt_pos, which is initially 0. If msg_cnt_pos=0, then p_last=p1.

[0089] The above distance difference dp reflects the moving distance of the autonomous driving vehicle between the two frames of position data. Since the calibration calculation of the heading angle is also based on the two frames of position data, if the distance is too large or too small, the calibration error will increase. Therefore, the embodiment of the present application can constrain the distance difference between the two frames of position data used to calculate the heading angle within a reasonable range, for example, it can be set to 3m-30m. If the distance difference is within this range, the second heading angle pos_yaw can be calculated as follows:

[0090] pos_yaw=-atan2(px-px_last,py-py_last)*Rad_To_Deg+90 (the degree can be adaptively adjusted according to the coordinate system);

[0091] pos_yaw=pos_yaw+360, msg_cnt_pos_cnt++.

[0092] If the distance difference exceeds the constraint range, it is considered that the current data cannot be used for subsequent heading angle calculation. Of course, how to set this range specifically can be flexibly set by those skilled in the art according to actual needs, and no specific limitation is made here.

[0093] In some special scenarios, when the autonomous driving vehicle is traveling at a constant speed, the distance difference between two adjacent frames of position data is always the same, which will reduce the reliability and accuracy of the subsequently calculated heading angle. Therefore, the last frame position p_last in the embodiment of the present application is not updated in real time, and can be updated when the update condition is triggered, for example, expressed as follows:

[0094] if(msg_cnt_pos_cnt>3)

[0095] {

[0096] msg_cnt_pos_cnt = 0;

[0097] } Update P_last every three frames

[0098] In some embodiments of the present application, determining the heading angle calibration result of the autonomous driving vehicle based on the heading angle deviation between the first heading angle and the second heading angle includes: calculating the heading angle deviation between the first heading angle and the second heading angle for multiple frames; performing sliding filtering on the heading angle deviation between the first heading angle and the second heading angle for multiple frames to obtain the heading angle deviation after sliding filtering; and determining the final heading angle calibration result of the autonomous driving vehicle based on the heading angle deviation after sliding filtering.

[0099] In the calibration phase, the calculation of the heading angle in the embodiment of the present application is a multi-frame continuous process. For the obtained second heading angle pos_yaw, the heading angle deviation yaw_diff_pos between it and the first heading angle yaw can be calculated. For ease of understanding, the heading angle deviation can be further constrained to a range of -180 to 180, which can be specifically expressed as follows:

[0100] yaw_diff_pos=pos_yaw-yaw;

[0101] if(yaw_diff_pos>180) yaw_diff_pos-=360;

[0102] if(yaw_diff_pos<-180) yaw_diff_pos+=360.

[0103] Afterwards, based on the calculated heading angle deviation of each frame, sliding filtering can be performed in the following way to improve the stability of the heading angle calibration result:

[0104] ave_yaw_diff_pos=(ave_yaw_diff_pos*msg_cnt_pos_cnt+yaw_diff_pos) / (msg_cnt_pos_cnt+1).

[0105] Among them, ave_yaw_diff_pos represents the heading angle deviation after each sliding filter.

[0106] In some embodiments of the present application, determining the final heading angle calibration result of the autonomous driving vehicle based on the heading angle deviation after sliding filtering includes: counting the second heading angle and calculating the angle difference between the heading angle deviation after sliding filtering and the historical heading angle calibration result; counting the heading angle deviation after sliding filtering when the count of the second heading angle meets a preset counting threshold and the angle difference between the heading angle deviation after sliding filtering and the historical heading angle calibration result is not greater than the preset angle difference threshold; updating the heading angle calibration result of the autonomous driving vehicle according to the heading angle deviation after sliding filtering and the count of the heading angle deviation after sliding filtering; and using the updated heading angle calibration result of the autonomous driving vehicle as the final heading angle calibration result when the calibration end condition is met.

[0107] In order to further improve the accuracy of the calibration results, during the sliding filter processing, the last heading angle calibration result yaw0 can be further obtained from the calibration configuration file as an additional constraint. The specific method can be as follows:

[0108] When msg_cnt_pos_cnt = preset count threshold, and ||ave_yaw_diff_pos|-|yaw0||<=preset angle difference threshold, calculate the new heading angle deviation:

[0109] sum_yaw_diff_cnt++;

[0110] sum_yaw_diff=sum_yaw_diff+ave_yaw_diff_pos;

[0111] yaw_diff_new=double(sum_yaw_diff / sum_yaw_diff_cnt).

[0112] The above constraints are mainly to constrain that the deviation between the heading angle deviation ave_yaw_diff_pos after sliding filtering and the heading angle calibrated in the last history should not be too large. If the current ave_yaw_diff_pos meets this condition, ave_yaw_diff_pos sum count sum_yaw_diff_cnt++ is performed, and finally the final calibrated heading angle deviation is calculated by summing and averaging.

[0113] Here you can set the conditions for the end of calibration. For example, when the sum_yaw_diff_cnt count exceeds a certain count threshold or the driving distance is greater than a certain distance threshold, the calibration is considered completed and the new yaw_diff_new is written to the calibration configuration file. Otherwise, repeat the above steps.

[0114] In some embodiments of the present application, the heading angle calibration result is a heading angle calibration result in a predefined coordinate system, and the heading angle calibration method of the autonomous driving vehicle also includes: converting the heading angle calibration result in the predefined coordinate system to the UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system; and sending the heading angle calibration result in the UTM coordinate system to a downstream module.

[0115] The heading angle calibration result obtained in the above-mentioned embodiment can be used by downstream modules such as perception module, fusion positioning module, planning and control module, etc. Since the downstream modules are generally processed in the UTM coordinate system, considering the actual use requirements of the downstream modules, the embodiment of the present application can further convert the heading angle calibration result in the predefined coordinate system obtained in the above-mentioned embodiment to the UTM coordinate system, thereby obtaining the heading angle calibration result in the UTM coordinate system, and finally sending the heading angle calibration result in the UTM coordinate system to the downstream module. The above-mentioned conversion process is implemented inside the calibration module, and there is no need for the downstream module to cooperate in the modification, thereby reducing the access cost.

[0116] In some embodiments of the present application, converting the heading angle calibration result in the predefined coordinate system to the UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system includes: determining the current location of the autonomous driving vehicle, and determining the UTM zone center longitude of the current location based on the current location of the autonomous driving vehicle; converting the heading angle calibration result in the predefined coordinate system to the UTM coordinate system based on the UTM zone center longitude of the current location to obtain the heading angle calibration result in the UTM coordinate system.

[0117] Although the aforementioned embodiment will eventually convert the heading angle calibration result in the predefined coordinate system to the UTM coordinate system, the core difference compared with the existing solution of directly calibrating the heading angle in the UTM coordinate system is that the heading angle calibration result in the predefined coordinate system obtained in the present application can be applied to different cities and regions, and no recalibration is required across cities. The final conversion to the heading angle calibration result in the UTM coordinate system is only to meet the usage requirements of downstream modules, and is not equivalent to the existing result obtained by directly calibrating in the UTM coordinate system.

[0118] Specifically, the heading angle calibration result in the predefined coordinate system can be converted to the UTM coordinate system in the following way:

[0119] y=-sin(current_latitude)x;

[0120] x=current_longtitude-middle_utm_zone_longtitude

[0121] Among them, y represents the deviation value between the heading angle calibration result in the UTM coordinate system and the heading angle calibration result in the predefined coordinate system, current_latitude and current_longtitude are the latitude and longitude of the current location respectively, middle_utm_zone_longtitude is the center longitude of the current UTM zone, and the center longitude of the current UTM zone can be determined based on the known correspondence between UTM zone-longitude range-center longitude.

[0122] After calculating the deviation between the heading angle calibration result in the UTM coordinate system and the heading angle calibration result in the predefined coordinate system, the heading angle calibration result in the predefined coordinate system is added with the deviation value to obtain the corresponding heading angle calibration result in the UTM coordinate system.

[0123] The present application also provides a heading angle calibration device 200 for an autonomous driving vehicle. Figure 2 As shown, a schematic diagram of the structure of a heading angle calibration device for an autonomous driving vehicle in an embodiment of the present application is provided. The heading angle calibration device 200 for the autonomous driving vehicle at least includes:

[0124] An acquisition unit 210 is used to acquire current positioning information sent by an RTK positioning device of the autonomous driving vehicle, wherein the current positioning information includes a first heading angle and a current position;

[0125] A first conversion unit 220 is used to convert the current position into a predefined coordinate system to obtain the current position in the predefined coordinate system, where the predefined coordinate system is a local coordinate system constructed with the first frame positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin;

[0126] A calculation unit 230, configured to calculate a second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system;

[0127] The determination unit 240 is used to determine a heading angle calibration result of the automatic driving vehicle according to the heading angle deviation between the first heading angle and the second heading angle.

[0128] In some embodiments of the present application, the acquisition unit 210 is specifically used to: obtain the current speed of the autonomous driving vehicle and the current positioning status of the RTK positioning device; determine whether the autonomous driving vehicle meets preset calibration conditions based on the current speed and the current positioning status; and when the preset calibration conditions are met, obtain the current positioning information sent by the RTK positioning device of the autonomous driving vehicle.

[0129] In some embodiments of the present application, the calculation unit 230 is specifically used to: calculate the relative distance based on the current position in the predefined coordinate system and the historical position in the predefined coordinate system; determine whether the preset distance constraint is met based on the relative distance and the preset distance threshold; if the preset distance constraint is met, calculate the second heading angle based on the current position in the predefined coordinate system and the historical position in the predefined coordinate system.

[0130] In some embodiments of the present application, the determination unit 240 is specifically used to: calculate the heading angle deviation between the first heading angle and the second heading angle of multiple frames; perform sliding filtering on the heading angle deviation between the first heading angle and the second heading angle of multiple frames to obtain the heading angle deviation after sliding filtering; and determine the final heading angle calibration result of the autonomous driving vehicle based on the heading angle deviation after sliding filtering.

[0131] In some embodiments of the present application, the determination unit 240 is specifically used to: count the second heading angle and calculate the angle difference between the heading angle deviation after sliding filtering and the historical heading angle calibration result; count the heading angle deviation after sliding filtering when the count of the second heading angle meets the preset counting threshold and the angle difference between the heading angle deviation after sliding filtering and the historical heading angle calibration result is not greater than the preset angle difference threshold; update the heading angle calibration result of the autonomous driving vehicle according to the heading angle deviation after sliding filtering and the count of the heading angle deviation after sliding filtering; and when the calibration end condition is met, use the updated heading angle calibration result of the autonomous driving vehicle as the final heading angle calibration result.

[0132] In some embodiments of the present application, the heading angle calibration result is a heading angle calibration result in a predefined coordinate system, and the heading angle calibration device 200 of the autonomous driving vehicle also includes: a second conversion unit, used to convert the heading angle calibration result in the predefined coordinate system to the UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system; a sending unit, used to send the heading angle calibration result in the UTM coordinate system to a downstream module.

[0133] In some embodiments of the present application, the second conversion unit is specifically used to: determine the current location of the autonomous driving vehicle, and determine the UTM zone center longitude of the current location based on the current location of the autonomous driving vehicle; according to the UTM zone center longitude of the current location, convert the heading angle calibration result in the predefined coordinate system to the UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system.

[0134] It can be understood that the heading angle calibration device of the above-mentioned autonomous driving vehicle can implement the various steps of the heading angle calibration method of the autonomous driving vehicle provided in the aforementioned embodiment, and the relevant explanations about the heading angle calibration method of the autonomous driving vehicle are all applicable to the heading angle calibration device of the autonomous driving vehicle, which will not be repeated here.

[0135] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. Figure 3 At the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and a memory. The memory may include a memory, such as a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. Of course, the electronic device may also include hardware required for other services.

[0136] The processor, network interface and memory can be interconnected through an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0137] The memory is used to store the program. Specifically, the program may include a program code, and the program code includes a computer operation instruction. The memory may include a memory and a non-volatile memory, and provides instructions and data to the processor.

[0138] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming a heading angle calibration device for the autonomous driving vehicle at the logical level. The processor executes the program stored in the memory and is specifically used to perform the following operations:

[0139] Acquire current positioning information sent by an RTK positioning device of the autonomous driving vehicle, wherein the current positioning information includes a first heading angle and a current position;

[0140] Convert the current position to a predefined coordinate system to obtain the current position in the predefined coordinate system, where the predefined coordinate system is a local coordinate system constructed with the first frame positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin;

[0141] Calculating a second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system;

[0142] A heading angle calibration result of the automatic driving vehicle is determined based on a heading angle deviation between the first heading angle and the second heading angle.

[0143] The above application Figure 1 The method performed by the heading angle calibration device of the autonomous driving vehicle disclosed in the illustrated embodiment can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or instructions in the form of software. The above processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0144] The present application also provides a computer program product, which stores one or more programs, wherein the one or more programs include instructions, which, when executed by an electronic device including multiple application programs, enable the electronic device to execute Figure 1The method performed by the heading angle calibration device of the autonomous driving vehicle in the illustrated embodiment is specifically used to perform:

[0145] Acquire current positioning information sent by an RTK positioning device of the autonomous driving vehicle, wherein the current positioning information includes a first heading angle and a current position;

[0146] Convert the current position to a predefined coordinate system to obtain the current position in the predefined coordinate system, where the predefined coordinate system is a local coordinate system constructed with the first frame positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin;

[0147] Calculating a second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system;

[0148] A heading angle calibration result of the automatic driving vehicle is determined based on a heading angle deviation between the first heading angle and the second heading angle.

[0149] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0150] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0151] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0152] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0153] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0154] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0155] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0156] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0157] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0158] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for calibrating the heading angle of an autonomous driving vehicle, wherein: The heading angle calibration method of the autonomous driving vehicle comprises: Acquire current positioning information sent by an RTK positioning device of the autonomous driving vehicle, wherein the current positioning information includes a first heading angle and a current position; Convert the current position to a predefined coordinate system to obtain the current position in the predefined coordinate system, where the predefined coordinate system is a local coordinate system constructed with the first frame positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin; Calculating a second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system; A heading angle calibration result of the automatic driving vehicle is determined based on a heading angle deviation between the first heading angle and the second heading angle.

2. The method for calibrating the heading angle of an autonomous driving vehicle according to claim 1, wherein: The obtaining of the current positioning information sent by the RTK positioning device of the autonomous driving vehicle includes: Get the current speed of the autonomous vehicle and the current positioning status of the RTK positioning device; Determining whether the autonomous driving vehicle meets a preset calibration condition according to the current speed and the current positioning state; When the preset calibration conditions are met, the current positioning information sent by the RTK positioning device of the autonomous driving vehicle is obtained.

3. The heading angle calibration method for an autonomous driving vehicle according to claim 1, wherein: Calculating the second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system comprises: Calculate the relative distance based on the current position in the predefined coordinate system and the historical position in the predefined coordinate system; Determining whether a preset distance constraint condition is met according to the relative distance and a preset distance threshold; When a preset distance constraint condition is met, a second heading angle is calculated according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system.

4. The heading angle calibration method for an autonomous driving vehicle according to claim 1, wherein: Determining a heading angle calibration result of the automatic driving vehicle according to a heading angle deviation between the first heading angle and the second heading angle includes: Calculate a heading angle deviation between the first heading angle and the second heading angle of multiple frames; Performing sliding filtering processing on the heading angle deviation between the first heading angle and the second heading angle of multiple frames to obtain the heading angle deviation after sliding filtering; The final heading angle calibration result of the automatic driving vehicle is determined according to the heading angle deviation after the sliding filter.

5. The heading angle calibration method for an autonomous driving vehicle as claimed in claim 4, wherein: Determining the final heading angle calibration result of the automatic driving vehicle according to the heading angle deviation after the sliding filter includes: Counting the second heading angle, and calculating the angle difference between the heading angle deviation after the sliding filter and the historical heading angle calibration result; When the count of the second heading angle meets the preset counting threshold and the angle difference between the heading angle deviation after the sliding filter and the historical heading angle calibration result is not greater than the preset angle difference threshold, counting the heading angle deviation after the sliding filter; Updating a heading angle calibration result of the automatic driving vehicle according to the heading angle deviation after sliding filtering and the count of the heading angle deviation after sliding filtering; When the calibration end condition is met, the updated heading angle calibration result of the autonomous driving vehicle is used as the final heading angle calibration result.

6. The heading angle calibration method for an autonomous driving vehicle according to claim 1, wherein: The heading angle calibration result is a heading angle calibration result in a predefined coordinate system, and the heading angle calibration method of the autonomous driving vehicle further includes: Convert the heading angle calibration result in the predefined coordinate system to the UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system; The heading angle calibration result in the UTM coordinate system is sent to the downstream module.

7. The method for calibrating the heading angle of an autonomous driving vehicle according to claim 6, wherein: The converting the heading angle calibration result in the predefined coordinate system to the UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system includes: Determine a current location of the autonomous driving vehicle, and determine the UTM zone center longitude of the current location based on the current location of the autonomous driving vehicle; According to the UTM zone center longitude of the current location, the heading angle calibration result in the predefined coordinate system is converted to the UTM coordinate system to obtain the heading angle calibration result in the UTM coordinate system.

8. A heading angle calibration device for an autonomous driving vehicle, wherein: The heading angle calibration device of the automatic driving vehicle comprises: An acquisition unit, configured to acquire current positioning information sent by an RTK positioning device of the autonomous driving vehicle, wherein the current positioning information includes a first heading angle and a current position; A first conversion unit is used to convert the current position into a predefined coordinate system to obtain the current position in the predefined coordinate system, where the predefined coordinate system is a local coordinate system constructed with the first frame positioning information collected by the RTK positioning device at the starting point of the autonomous driving vehicle as the origin; a calculation unit, configured to calculate a second heading angle according to the current position in the predefined coordinate system and the historical position in the predefined coordinate system; A determination unit is used to determine a heading angle calibration result of the automatic driving vehicle according to a heading angle deviation between the first heading angle and the second heading angle.

9. An electronic device, comprising: processor; And a memory arranged to store computer executable instructions, which, when executed, cause the processor to execute the heading angle calibration method for the autonomous driving vehicle of any one of claims 1 to 7.

10. A computer program product, comprising a computer program or instructions, which, when executed by a processor, implements the heading angle calibration method of any one of claims 1 to 7 of the autonomous driving vehicle.

Images