Vehicle heading angle determination method, system, vehicle and storage medium

Abstract

The present invention provides a vehicle heading angle determination method, system, vehicle and storage medium, the method comprising: determining first shape point data of a first lane boundary line based on a visual sensor arranged on the vehicle, determining second shape point data of a second lane boundary line based on a high-precision positioning system and a high-precision map system arranged on the vehicle; determining a first projection point from the vehicle to the first lane boundary line and a second projection point from the vehicle to the second lane boundary line; determining a first shape point distance between each first lane boundary line shape point and the first projection point, and a second shape point distance between each second lane boundary line shape point and the second projection point; constructing a first fifth-order fitting equation, a second fifth-order fitting equation, a third fifth-order fitting equation and a fourth fifth-order fitting equation; determining the vehicle heading angle based on the first fifth-order fitting equation, the second fifth-order fitting equation, the third fifth-order fitting equation and the fourth fifth-order fitting equation. The present invention improves the accuracy of the vehicle heading angle while improving the determination efficiency.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving technology, and in particular to a vehicle heading angle determination method, system, vehicle and storage medium. Background Art

[0002] At present, vehicles with autonomous driving systems (ADS) have begun to be gradually introduced to the market, greatly promoting the development of intelligent transportation. The heading angle is an important parameter to ensure the safe and stable operation of autonomous vehicles.

[0003] The application publication number CN116295457A discloses a vehicle visual positioning method and system based on a two-dimensional semantic map, which obtains the current sensor posture data and camera image data; performs image perception on the camera image data to obtain visual semantic perception elements; obtains a two-dimensional semantic map of the current vehicle environment to obtain map elements; obtains the height of the map elements in the two-dimensional semantic map according to the visual semantic perception elements, and constructs the three-dimensional coordinates of the map element sampling points; performs mixed data association on the three-dimensional coordinates of the map element sampling points and the visual semantic perception elements; performs nonlinear optimization iteration based on the mixed data association results to obtain the optimal current posture, which includes the heading angle. However, it has the following technical problems: the accuracy of the two-dimensional semantic map is low, resulting in low matching accuracy between the map element sampling points and the visual semantic perception elements, which in turn leads to inaccurate determination of the heading angle, and the heading angle is obtained through nonlinear optimization iteration, which requires a large amount of calculation, resulting in a slow determination speed of the heading angle.

[0004] Therefore, there is an urgent need to propose a vehicle heading angle determination method, system, vehicle and storage medium to solve the above technical problems. Summary of the invention

[0005] In view of this, it is necessary to provide a vehicle heading angle determination method, system, vehicle and storage medium to solve the technical problems existing in the prior art that the determined heading angle is inaccurate and the determination efficiency is low.

[0006] In one aspect, the present invention provides a method for determining a vehicle heading angle, comprising:

[0007] Determine first shape point data of a first lane edge line based on a visual sensor disposed on the vehicle, and determine second shape point data of a second lane edge line based on a high-precision positioning system and a high-precision map system disposed on the vehicle; the first shape point data includes a first X-axis coordinate value and a first Y-axis coordinate value of each first lane edge line shape point in a target coordinate system, and the second shape point data includes a second X-axis coordinate value and a second Y-axis coordinate value of each second lane edge line shape point in the target coordinate system;

[0008] Determine a first projection point of the vehicle to the first lane edge and a second projection point of the vehicle to the second lane edge;

[0009] Determine a first shape point distance between each of the first lane edge shape points and the first projection point, and a second shape point distance between each of the second lane edge shape points and the second projection point;

[0010] Taking the first shape point distance as the independent variable, the first X-axis coordinate value and the first Y-axis coordinate value as the dependent variable, respectively constructing a first fifth-order fitting equation and a second fifth-order fitting equation, and taking the second shape point distance as the independent variable, the second X-axis coordinate value and the second Y-axis coordinate value as the dependent variable, respectively constructing a third fifth-order fitting equation and a fourth fifth-order fitting equation;

[0011] A first angle of the vehicle is determined based on the first and second fifth-order fitting equations, a second angle of the vehicle is determined based on the third and fourth fifth-order fitting equations, and a vehicle heading angle is determined based on the first and second angles.

[0012] In some possible implementations, the determining of first shape point data of a first lane edge line based on a visual sensor disposed on the vehicle includes:

[0013] Acquiring first lane boundary information of the first lane boundary based on a visual sensor disposed on the vehicle;

[0014] Taking the vehicle as the target coordinate origin, constructing the target coordinate system, and determining a plurality of first lane boundary coordinate points of the first lane boundary information in the target coordinate system;

[0015] The first shape point data is determined based on the plurality of first lane edge coordinate points.

[0016] In some possible implementations, determining the first shape point data based on the plurality of first lane edge coordinate points includes:

[0017] Fitting the plurality of first lane edge line coordinate points with a target fitting equation to obtain a lane edge line fitting equation;

[0018] The first shape point data is extracted from the lane edge fitting equation based on a preset extraction range.

[0019] In some possible implementations, the determining of the second shape point data of the second lane boundary line based on a high-precision positioning system and a high-precision map system provided on the vehicle includes:

[0020] Acquiring second lane boundary line information of the second lane boundary line based on a high-precision positioning system and a high-precision map system provided on the vehicle; the second lane boundary line information includes a plurality of initial second lane boundary line coordinate points in a preset coordinate system;

[0021] Determining a coordinate transformation matrix of the preset coordinate system and the target coordinate system based on the high-precision positioning system, and determining a plurality of second lane boundary line coordinate points based on the coordinate transformation matrix and the plurality of initial second lane boundary line coordinate points;

[0022] Downsampling is performed on the plurality of second lane edge coordinate points to obtain the second shape point data.

[0023] In some possible implementations, performing downsampling processing on the plurality of second lane edge coordinate points to obtain the second shape point data includes:

[0024] Determine the distance between each of the second lane edge coordinate points and the second projection point to be screened;

[0025] A preset shape point distance range is obtained, and the second shape point data is determined based on the shape point distance to be screened and the preset shape point distance range.

[0026] In some possible implementations, the preset shape point distance range includes a first preset distance range in which the vehicle has traveled and a second preset distance range in the direction of travel of the vehicle, and the first preset distance range is equal to the second preset distance range.

[0027] In some possible implementations, the first quintic fitting equation is:

[0028]

[0029] The second fifth order fitting equation is:

[0030]

[0031] The third fifth order fitting equation is:

[0032]

[0033] The fourth and fifth order fitting equations are:

[0034]

[0035] The vehicle heading angle is:

[0036]

[0037]

[0038] In the formula, is the first X-axis coordinate value; is the distance of the first shape point; is the first Y-axis coordinate value; is the second X-axis coordinate value; is the distance between the second shape points; is the second Y-axis coordinate value; is the vehicle heading angle; is the first angle; is the second angle; C 0 is the first parameter; C 1 is the second parameter; C 2 is the third parameter; C 3 is the fourth parameter; C 4 is the fifth parameter; C 5 is the sixth parameter; is the seventh parameter; is the eighth parameter; is the ninth parameter; is the tenth parameter; is the eleventh parameter; is the twelfth parameter; D 0 is the thirteenth parameter; D 1 is the fourteenth parameter; D 2 is the fifteenth parameter; D 3 is the sixteenth parameter; D 4 is the seventeenth parameter; D 5 is the eighteenth parameter; is the nineteenth parameter; is the twentieth parameter; is the twenty-first parameter; is the twenty-second parameter; is the twenty-third parameter; It is the twenty-fourth parameter.

[0039] On the other hand, the present invention also provides a vehicle heading angle determination system, comprising:

[0040] A shape point data determination unit, used to determine first shape point data of a first lane edge based on a visual sensor arranged on the vehicle, and to determine second shape point data of a second lane edge based on a high-precision positioning system and a high-precision map system arranged on the vehicle; the first shape point data includes a first X-axis coordinate value and a first Y-axis coordinate value of each first lane edge shape point in a target coordinate system, and the second shape point data includes a second X-axis coordinate value and a second Y-axis coordinate value of each second lane edge shape point in the target coordinate system;

[0041] A projection point determination unit, used to determine a first projection point from the vehicle to the first lane edge and a second projection point from the vehicle to the second lane edge;

[0042] a shape point distance determination unit, configured to determine a first shape point distance between each shape point of the first lane edge line and the first projection point, and a second shape point distance between each shape point of the second lane edge line and the second projection point;

[0043] a quintic fitting equation construction unit, configured to respectively construct a first quintic fitting equation and a second quintic fitting equation with the first shape point distance as an independent variable, the first X-axis coordinate value and the first Y-axis coordinate value as dependent variables, and respectively construct a third quintic fitting equation and a fourth quintic fitting equation with the second shape point distance as an independent variable, the second X-axis coordinate value and the second Y-axis coordinate value as dependent variables;

[0044] A vehicle heading angle determination unit is used to determine a first angle of the vehicle based on the first fifth-order fitting equation and the second fifth-order fitting equation, determine a second angle of the vehicle based on the third fifth-order fitting equation and the fourth fifth-order fitting equation, and determine a vehicle heading angle based on the first angle and the second angle.

[0045] In another aspect, the present invention further provides a vehicle, comprising a memory and a processor, wherein:

[0046] The memory is used to store programs;

[0047] The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the vehicle heading angle determination method described in any one of the possible implementations above.

[0048] On the other hand, the present invention also provides a computer-readable storage medium for storing computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the vehicle heading angle determination method described in any of the above possible implementations.

[0049] The beneficial effects of adopting the above-mentioned embodiment are as follows: the vehicle heading angle determination method provided by the present invention determines the second shape point data of the second lane edge line based on the high-precision positioning system and the high-precision map system arranged on the vehicle. Compared with the two-dimensional semantic map, the high-precision map in the high-precision map system has higher accuracy and stability. In addition, the present invention determines the first projection point from the vehicle to the first lane edge line and the second projection point from the vehicle to the second lane edge line, and constructs a fifth-order fitting equation respectively with the vehicle as a unified reference object, which can ensure the matching accuracy of the first shape point data and the second shape point data, thereby improving the accuracy of the determined vehicle heading angle.

[0050] Furthermore, the present invention constructs a first fifth-order fitting equation and a second fifth-order fitting equation respectively by taking the first shape point distance as the independent variable and the first X-axis coordinate value and the first Y-axis coordinate value as the dependent variables, and constructs a third fifth-order fitting equation and a fourth fifth-order fitting equation respectively by taking the second shape point distance as the independent variable and the second X-axis coordinate value and the second Y-axis coordinate value as the dependent variables. The vehicle heading angle can be determined based on the four fifth-order fitting equations without the need for nonlinear iteration, and the calculation process is simple and the amount of calculation is small, thereby improving the efficiency of determining the vehicle heading angle.

[0051] Furthermore, the present invention uses the first shape point distance as the independent variable, the first X-axis coordinate value and the first Y-axis coordinate value as the dependent variables, to respectively construct the first fifth-order fitting equation and the second fifth-order fitting equation, and uses the second shape point distance as the independent variable, the second X-axis coordinate value and the second Y-axis coordinate value as the dependent variable, to respectively construct the third fifth-order fitting equation and the fourth fifth-order fitting equation, instead of directly using the first X-axis coordinate value and the second X-axis coordinate value as the independent variables and the first Y-axis coordinate value and the second Y-axis coordinate value as the dependent variables to construct the fitting equation, thereby ensuring that the fitted curve is not distorted and reducing the error between the first lane edge line shape point and the second lane edge line shape point, so that the determination of the vehicle heading angle is stable and reliable without jumping. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0053] Figure 1 A schematic flow chart of an embodiment of a method for determining a vehicle heading angle provided by the present invention;

[0054] Figure 2 A schematic diagram of a flow chart of an embodiment of determining first shape point data provided by the present invention;

[0055] Figure 3 A schematic diagram of a flow chart of an embodiment of determining second shape point data provided by the present invention;

[0056] Figure 4 For the present invention Figure 3 A schematic flow chart of an embodiment of step S303;

[0057] Figure 5 A schematic diagram of the structure of an embodiment of a vehicle heading angle determination system provided by the present invention;

[0058] Figure 6A schematic structural diagram of an embodiment of a vehicle provided by the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0060] It should be understood that the schematic drawings are not drawn to scale. The flow chart used in the present invention shows the operations implemented according to some embodiments of the present invention. It should be understood that the operations of the flow chart can be implemented out of order, and the steps without logical context can be reversed or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flow chart under the guidance of the content of the present invention, and can also remove one or more operations from the flow chart.

[0061] Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor systems and / or microcontroller systems.

[0062] Reference to an "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0063] Embodiments of the present invention provide a method, system, vehicle and storage medium for determining a vehicle heading angle, which are described below respectively.

[0064] Figure 1 A schematic flow chart of an embodiment of a method for determining a vehicle heading angle provided by the present invention is shown in FIG. Figure 1 As shown, the vehicle heading angle determination method includes:

[0065] S101, determining first shape point data of a first lane edge based on a visual sensor disposed on the vehicle, and determining second shape point data of a second lane edge based on a high-precision positioning system and a high-precision map system disposed on the vehicle; the first shape point data includes a first X-axis coordinate value and a first Y-axis coordinate value of each first lane edge shape point in a target coordinate system, and the second shape point data includes a second X-axis coordinate value and a second Y-axis coordinate value of each second lane edge shape point in the target coordinate system;

[0066] S102, determining a first projection point from the vehicle to the first lane edge and a second projection point from the vehicle to the second lane edge;

[0067] S103, determining a first shape point distance between each first lane edge shape point and the first projection point, and a second shape point distance between each second lane edge shape point and the second projection point;

[0068] S104, taking the first shape point distance as the independent variable, the first X-axis coordinate value and the first Y-axis coordinate value as the dependent variables, respectively constructing a first fifth-order fitting equation and a second fifth-order fitting equation, and taking the second shape point distance as the independent variable, the second X-axis coordinate value and the second Y-axis coordinate value as the dependent variables, respectively constructing a third fifth-order fitting equation and a fourth fifth-order fitting equation;

[0069] S105. Determine a first angle of the vehicle based on the first fifth-order fitting equation and the second fifth-order fitting equation, determine a second angle of the vehicle based on the third fifth-order fitting equation and the fourth fifth-order fitting equation, and determine a heading angle of the vehicle based on the first angle and the second angle.

[0070] Compared with the prior art, the vehicle heading angle determination method provided by the embodiment of the present invention determines the second shape point data of the second lane edge based on the high-precision positioning system and the high-precision map system set on the vehicle. Compared with the two-dimensional semantic map, the high-precision map in the high-precision map system has higher accuracy and stability. In addition, the embodiment of the present invention determines the first projection point from the vehicle to the first lane edge and the second projection point from the vehicle to the second lane edge, and constructs a quintic fitting equation with the vehicle as a unified reference object, respectively, so as to ensure the matching accuracy of the first shape point data and the second shape point data, thereby improving the accuracy of the determined vehicle heading angle. Further, the embodiment of the present invention constructs the first quintic fitting equation and the second quintic fitting equation respectively by taking the first shape point distance as the independent variable, the first X-axis coordinate value and the first Y-axis coordinate value as the dependent variable, and constructs the third quintic fitting equation and the fourth quintic fitting equation respectively by taking the second shape point distance as the independent variable, the second X-axis coordinate value and the second Y-axis coordinate value as the dependent variable. The vehicle heading angle can be determined based on the four quintic fitting equations, without the need for nonlinear iteration, and the calculation process is simple and the amount of calculation is small, thereby improving the efficiency of determining the vehicle heading angle.

[0071] Furthermore, in the embodiment of the present invention, the first shape point distance is used as the independent variable, the first X-axis coordinate value and the first Y-axis coordinate value are used as the dependent variables, and the first fifth-order fitting equation and the second fifth-order fitting equation are constructed respectively. The second shape point distance is used as the independent variable, and the second X-axis coordinate value and the second Y-axis coordinate value are used as the dependent variables, and the third fifth-order fitting equation and the fourth fifth-order fitting equation are constructed respectively, instead of directly constructing the fitting equation with the first X-axis coordinate value and the second X-axis coordinate value as the independent variables and the first Y-axis coordinate value and the second Y-axis coordinate value as the dependent variables. This ensures that the fitted curve is not distorted, and reduces the error between the first lane edge line shape point and the second lane edge line shape point, so that the determination of the vehicle heading angle is stable and reliable, and there will be no jump.

[0072] It should be understood that the visual sensor, high-precision positioning system and high-precision map system are built-in devices on the autonomous driving vehicle. Therefore, the embodiment of the present invention does not change the hardware solution of the vehicle, that is, the purpose of accurately and quickly determining the vehicle heading angle is achieved without changing the hardware solution of the vehicle.

[0073] Among them, the visual sensor can be a forward-looking camera, a forward-looking camera and other devices.

[0074] It should be noted that the specific process of determining the second shape point data of the second lane edge line based on the high-precision positioning system and the high-precision map system is: determine the current position of the vehicle based on the high-precision positioning system, call the high-precision map corresponding to the current position from the high-precision map system based on the current position, and then determine the second shape point data based on the high-precision map.

[0075] It should also be noted that the target coordinate system in step S101 is a right-handed rectangular coordinate system constructed with the vehicle as the coordinate origin, wherein the positive direction of the X-axis is the direction of travel of the vehicle head.

[0076] In some embodiments of the present invention, Figure 2 As shown, the step S101 of determining the first shape point data of the first lane boundary line based on the visual sensor disposed on the vehicle includes:

[0077] S201, acquiring first lane boundary information of a first lane boundary based on a visual sensor disposed on a vehicle;

[0078] S202, constructing a target coordinate system with the vehicle as the target coordinate origin, and determining a plurality of first lane boundary coordinate points of the first lane boundary information in the target coordinate system;

[0079] S203: Determine first shape point data based on a plurality of first lane edge coordinate points.

[0080] The first lane edge information may be a plurality of shape points of the first lane edge obtained from a fitting curve output by a visual sensor based on a preset sampling step.

[0081] Since the visual sensor may have a distortion problem when fitting the long-distance lane edge, in order to solve this technical problem, in some embodiments of the present invention, step S203 includes:

[0082] The target fitting equation is used to fit multiple coordinate points to obtain a lane edge fitting equation; and the first shape point data is extracted from the lane edge fitting equation based on a preset extraction range.

[0083] The embodiment of the present invention extracts the first shape point data from the lane edge fitting equation through a preset extraction range, and can eliminate the coordinate points of the long-distance lane, thereby avoiding the first shape point data being distorted shape points, and further improving the accuracy of the determined vehicle heading angle. In addition, by extracting the first shape point data through a preset extraction range, the amount of calculation can also be reduced, thereby further improving the efficiency of determining the vehicle heading angle.

[0084] Among them, the target fitting equation is:

[0085]

[0086] In the formula, is the ordinate value of each coordinate point; is the horizontal coordinate value of each coordinate point; is the lateral displacement deviation between the vehicle and the first lane edge; To observe the heading angle; is the curvature of the first lane edge; is the curvature change rate of the first lane edge.

[0087] In a specific embodiment of the present invention, the preset extraction range is a range of abscissa values ​​of 0 to 5, and the abscissa difference between two adjacent shape points is 0.1, that is, the spacing step is 0.1.

[0088] After the above preset extraction range, 50 first lane edge line points will be obtained.

[0089] It should be noted that the extraction range can be adjusted and determined according to the actual application scenario and hardware computing power, which will not be elaborated here.

[0090] In some embodiments of the present invention, Figure 3 As shown, the second shape point data of the second lane boundary line is determined based on the high-precision positioning system and the high-precision map system provided on the vehicle in step S101, including:

[0091] S301, obtaining second lane boundary information of the second lane boundary based on a high-precision positioning system and a high-precision map system provided on the vehicle; the second lane boundary information includes a plurality of initial second lane boundary coordinate points in a preset coordinate system;

[0092] S302, determining a coordinate transformation matrix of a preset coordinate system and a target coordinate system based on a high-precision positioning system, and determining a plurality of second lane boundary line coordinate points based on the coordinate transformation matrix and a plurality of initial second lane boundary line coordinate points;

[0093] S303: Down-sampling the plurality of second lane edge coordinate points to obtain second shape point data.

[0094] Since the distance of the second lane edge line obtained by the high-precision positioning system and the high-precision map system is relatively long, and the embodiment of the present invention is only used to determine the vehicle heading angle, that is, it only focuses on the lane edge line points near the vehicle. Therefore, the embodiment of the present invention downsamples multiple second lane edge line coordinate points and intercepts a part of the second lane edge line points, which can greatly reduce the amount of calculation for subsequent determination of the vehicle heading angle and further improve the efficiency of determining the vehicle heading angle.

[0095] It should be noted that the preset coordinate system is a coordinate system that can represent the absolute position of the second initial lane edge coordinate point. In a specific embodiment of the present invention, the preset coordinate system is the Northeastern Universe (ENU) coordinate system.

[0096] The second lane line in step S301 is the lane line of the lane where the current vehicle is located, and the second lane edge line information is the edge line point information of the lane where the current vehicle is located.

[0097] In some embodiments of the present invention, Figure 4 As shown, step S303 includes:

[0098] S401, determining the distance between each second lane edge coordinate point and the second projection point to be screened;

[0099] S402, obtaining a preset shape point distance range, and determining second shape point data based on the shape point distance to be screened and the preset shape point distance range.

[0100] The distance between the to-be-screened points can be the sum of the distances between two adjacent points, that is, the distance between the to-be-screened points is:

[0101]

[0102] In the formula, S is the distance of the points to be screened; is the second X-axis coordinate value of the i-th second lane edge line point; is the second Y-axis coordinate value of the i-th second lane edge; is the second X-axis coordinate value of the i-1th second lane edge line point; It is the second Y-axis coordinate value of the i-1 second lane edge line.

[0103] It should be noted that: is the coordinate of the second projection point, and S=0 at the second projection point.

[0104] Since the vehicle heading angle refers to the heading angle at the vehicle position, that is, S=0, in order to ensure the accuracy of the fitting parameters at the S=0 position, in some embodiments of the present invention, the preset shape point distance range includes a first preset distance range that the vehicle has traveled and a second preset distance range in the direction of vehicle travel, and the first preset distance range and the second preset distance range are equal.

[0105] The embodiment of the present invention ensures the accuracy of the fitting parameters at the S=0 position by setting the preset shape point distance range to include a first preset distance range that the vehicle has traveled and a second preset distance range in the vehicle's traveling direction, thereby improving the accuracy of the vehicle's heading angle.

[0106] In a specific embodiment of the present invention, the first preset distance range and the second preset distance range are both 5m.

[0107] Since the positive direction of the shape point distance is the direction of the vehicle's forward movement, the negative sign is used to represent the distance range that the vehicle has traveled, and the positive sign is used to represent the distance range in the vehicle's forward movement direction. The shape point distance range is -5~5.

[0108] In some embodiments of the present invention, the first fifth-order fitting equation is:

[0109]

[0110] The second fifth order fitting equation is:

[0111]

[0112] The third and fifth order fitting equations are:

[0113]

[0114] The fourth and fifth fitting equations are:

[0115]

[0116] The vehicle heading angle is:

[0117]

[0118]

[0119] In the formula, is the first X-axis coordinate value; is the distance of the first shape point; is the first Y-axis coordinate value; is the second X-axis coordinate value; is the distance between the second shape points; is the second Y-axis coordinate value; is the vehicle heading angle; is the first angle; is the second angle; C 0 is the first parameter; C 1 is the second parameter; C 2 is the third parameter; C 3 is the fourth parameter; C 4 is the fifth parameter; C 5 is the sixth parameter; is the seventh parameter; is the eighth parameter; is the ninth parameter; is the tenth parameter; is the eleventh parameter; is the twelfth parameter; D 0 is the thirteenth parameter; D 1 is the fourteenth parameter; D 2 is the fifteenth parameter; D 3 is the sixteenth parameter; D 4 is the seventeenth parameter; D 5 is the eighteenth parameter; is the nineteenth parameter; is the twentieth parameter; is the twenty-first parameter; is the twenty-second parameter; is the twenty-third parameter; It is the twenty-fourth parameter.

[0120] The first angle is the absolute heading angle at the origin of the high-precision map ENU coordinate system where the vehicle is located, that is, the absolute heading angle with the east direction as 0 and the counterclockwise direction as the positive direction. The second angle is the angle between the vehicle and the sideline of the second lane.

[0121] In order to better implement the vehicle heading angle determination method in the embodiment of the present invention, based on the vehicle heading angle determination method, the embodiment of the present invention also provides a vehicle heading angle determination system, such as Figure 5 As shown, the vehicle heading angle determination system 500 includes:

[0122] A shape point data determining unit 501 is used to determine first shape point data of a first lane edge based on a visual sensor disposed on the vehicle, and to determine second shape point data of a second lane edge based on a high-precision positioning system and a high-precision map system disposed on the vehicle; the first shape point data includes a first X-axis coordinate value and a first Y-axis coordinate value of each shape point of the first lane edge in a target coordinate system, and the second shape point data includes a second X-axis coordinate value and a second Y-axis coordinate value of each shape point of the second lane edge in the target coordinate system;

[0123] A projection point determination unit 502, used to determine a first projection point from the vehicle to the first lane edge and a second projection point from the vehicle to the second lane edge;

[0124] A shape point distance determination unit 503, used to determine a first shape point distance between each first lane edge shape point and the first projection point, and a second shape point distance between each second lane edge shape point and the second projection point;

[0125] A quintic fitting equation construction unit 504 is used to respectively construct a first quintic fitting equation and a second quintic fitting equation with the first shape point distance as an independent variable, the first X-axis coordinate value and the first Y-axis coordinate value as dependent variables, and respectively construct a third quintic fitting equation and a fourth quintic fitting equation with the second shape point distance as an independent variable, the second X-axis coordinate value and the second Y-axis coordinate value as dependent variables;

[0126] The vehicle heading angle determination unit 505 is used to determine the first angle of the vehicle based on the first fifth-order fitting equation and the second fifth-order fitting equation, determine the second angle of the vehicle based on the third fifth-order fitting equation and the fourth fifth-order fitting equation, and determine the vehicle heading angle based on the first angle and the second angle.

[0127] The vehicle heading angle determination system 500 provided in the above embodiment can implement the technical solution described in the above vehicle heading angle determination method embodiment. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above vehicle heading angle determination method embodiment, which will not be repeated here.

[0128] like Figure 6 As shown, the present invention also provides a vehicle 600. The vehicle 600 includes a processor 601, a memory 602 and a display 603. Figure 6 Only some of the components of vehicle 600 are shown, but it should be understood that implementation of all of the components shown is not a requirement, and more or fewer components may alternatively be implemented.

[0129] In some embodiments, the processor 601 may be a central processing unit (CPU), a microprocessor or other data processing chip, which is used to run the program code or process data stored in the memory 602, such as the vehicle heading angle determination method of the present invention.

[0130] In some embodiments, the processor 601 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, the processor 601 may be local or remote. In some embodiments, the processor 601 may be implemented in a cloud platform. In one embodiment, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-cloud, etc., or any combination thereof.

[0131] In some embodiments, the memory 602 may be an internal storage unit of the vehicle 600, such as a hard disk or memory of the vehicle 600. In other embodiments, the memory 602 may also be an external storage device of the vehicle 600, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the vehicle 600.

[0132] Furthermore, the memory 602 may include both an internal storage unit of the vehicle 600 and an external storage device. The memory 602 is used to store application software installed in the vehicle 600 and various data.

[0133] In some embodiments, the display 603 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 603 is used to display information on the vehicle 600 and to display a visual user interface. The components 601-603 of the vehicle 600 communicate with each other via a system bus.

[0134] In some embodiments of the present invention, when the processor 601 executes the vehicle heading angle determination program in the memory 602, the following steps may be implemented:

[0135] Determine first shape point data of a first lane edge line based on a visual sensor disposed on the vehicle, and determine second shape point data of a second lane edge line based on a high-precision positioning system and a high-precision map system disposed on the vehicle; the first shape point data includes a first X-axis coordinate value and a first Y-axis coordinate value of each first lane edge line shape point in a target coordinate system, and the second shape point data includes a second X-axis coordinate value and a second Y-axis coordinate value of each second lane edge line shape point in the target coordinate system;

[0136] Determine a first projection point of the vehicle to the first lane edge and a second projection point of the vehicle to the second lane edge;

[0137] Determine a first shape point distance between each first lane edge shape point and the first projection point, and a second shape point distance between each second lane edge shape point and the second projection point;

[0138] Taking the first shape point distance as the independent variable, the first X-axis coordinate value and the first Y-axis coordinate value as the dependent variables, the first fifth-order fitting equation and the second fifth-order fitting equation are constructed respectively, and taking the second shape point distance as the independent variable, the second X-axis coordinate value and the second Y-axis coordinate value as the dependent variables, the third fifth-order fitting equation and the fourth fifth-order fitting equation are constructed respectively;

[0139] A first angle of the vehicle is determined based on the first fifth-order fitting equation and the second fifth-order fitting equation, a second angle of the vehicle is determined based on the third fifth-order fitting equation and the fourth fifth-order fitting equation, and a vehicle heading angle is determined based on the second angle and the second angle.

[0140] It should be understood that: when the processor 601 executes the vehicle heading angle determination program in the memory 602, in addition to the above functions, other functions can also be implemented. For details, please refer to the description of the corresponding method embodiment above.

[0141] Accordingly, an embodiment of the present application also provides a computer-readable storage medium, which is used to store computer-readable programs or instructions. When the program or instructions are executed by a processor, the steps or functions in the vehicle heading angle determination method provided in the above-mentioned method embodiments can be implemented.

[0142] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the computer program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0143] The above is a detailed introduction to a vehicle heading angle determination method, system, vehicle and storage medium provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for determining a vehicle heading angle, characterized in that: include: Determine first shape point data of a first lane edge line based on a visual sensor disposed on the vehicle, and determine second shape point data of a second lane edge line based on a high-precision positioning system and a high-precision map system disposed on the vehicle; the first shape point data includes a first X-axis coordinate value and a first Y-axis coordinate value of each first lane edge line shape point in a target coordinate system, and the second shape point data includes a second X-axis coordinate value and a second Y-axis coordinate value of each second lane edge line shape point in the target coordinate system; Determine a first projection point of the vehicle to the first lane edge and a second projection point of the vehicle to the second lane edge; Determine a first shape point distance between each of the first lane edge shape points and the first projection point, and a second shape point distance between each of the second lane edge shape points and the second projection point; Taking the first shape point distance as the independent variable, the first X-axis coordinate value and the first Y-axis coordinate value as the dependent variable, respectively constructing a first fifth-order fitting equation and a second fifth-order fitting equation, and taking the second shape point distance as the independent variable, the second X-axis coordinate value and the second Y-axis coordinate value as the dependent variable, respectively constructing a third fifth-order fitting equation and a fourth fifth-order fitting equation; A first angle of the vehicle is determined based on the first and second fifth-order fitting equations, a second angle of the vehicle is determined based on the third and fourth fifth-order fitting equations, and a vehicle heading angle is determined based on the first and second angles.

2. The method for determining a vehicle heading angle according to claim 1, characterized in that: The method of determining the first shape point data of the first lane boundary line based on a visual sensor disposed on the vehicle comprises: Acquiring first lane boundary information of the first lane boundary based on a visual sensor disposed on the vehicle; Taking the vehicle as the target coordinate origin, constructing the target coordinate system, and determining a plurality of first lane boundary coordinate points of the first lane boundary information in the target coordinate system; The first shape point data is determined based on the plurality of first lane edge coordinate points.

3. The method for determining a vehicle heading angle according to claim 2, characterized in that: The determining the first shape point data based on the plurality of first lane edge coordinate points comprises: Fitting the plurality of first lane edge line coordinate points with a target fitting equation to obtain a lane edge line fitting equation; The first shape point data is extracted from the lane edge fitting equation based on a preset extraction range.

4. The method for determining a vehicle heading angle according to claim 1, characterized in that: The method of determining the second shape point data of the second lane boundary line based on the high-precision positioning system and the high-precision map system provided on the vehicle includes: Acquiring second lane boundary line information of the second lane boundary line based on a high-precision positioning system and a high-precision map system provided on the vehicle; the second lane boundary line information includes a plurality of initial second lane boundary line coordinate points in a preset coordinate system; Determining a coordinate transformation matrix of the preset coordinate system and the target coordinate system based on the high-precision positioning system, and determining a plurality of second lane boundary line coordinate points based on the coordinate transformation matrix and the plurality of initial second lane boundary line coordinate points; Downsampling is performed on the plurality of second lane edge coordinate points to obtain the second shape point data.

5. The method for determining a vehicle heading angle according to claim 4, characterized in that: The downsampling process is performed on the plurality of second lane edge coordinate points to obtain the second shape point data, including: Determine the distance between each of the second lane edge coordinate points and the second projection point to be screened; A preset shape point distance range is obtained, and the second shape point data is determined based on the shape point distance to be screened and the preset shape point distance range.

6. The method for determining a vehicle heading angle according to claim 5, characterized in that: The preset shape point distance range includes a first preset distance range in which the vehicle has traveled and a second preset distance range in the vehicle's traveling direction, and the first preset distance range is equal to the second preset distance range.

7. The method for determining a vehicle heading angle according to claim 1, characterized in that: The first quintic fitting equation is: The second fifth order fitting equation is: The third fifth order fitting equation is: The fourth and fifth order fitting equations are: The vehicle heading angle is: In the formula, is the first X-axis coordinate value; is the distance of the first shape point; is the first Y-axis coordinate value; is the second X-axis coordinate value; is the distance between the second shape points; is the second Y-axis coordinate value; is the vehicle heading angle; is the first angle; is the second angle; C 0 is the first parameter; C 1 is the second parameter; C 2 is the third parameter; C 3 is the fourth parameter; C 4 is the fifth parameter; C 5 is the sixth parameter; is the seventh parameter; is the eighth parameter; is the ninth parameter; is the tenth parameter; is the eleventh parameter; is the twelfth parameter; D 0 is the thirteenth parameter; D 1 is the fourteenth parameter; D 2 is the fifteenth parameter; D 3 is the sixteenth parameter; D 4 is the seventeenth parameter; D 5 is the eighteenth parameter; is the nineteenth parameter; is the twentieth parameter; is the twenty-first parameter; is the twenty-second parameter; is the twenty-third parameter; It is the twenty-fourth parameter.

8. A vehicle heading angle determination system, characterized in that: include: A shape point data determination unit, used to determine first shape point data of a first lane edge based on a visual sensor arranged on the vehicle, and to determine second shape point data of a second lane edge based on a high-precision positioning system and a high-precision map system arranged on the vehicle; the first shape point data includes a first X-axis coordinate value and a first Y-axis coordinate value of each first lane edge shape point in a target coordinate system, and the second shape point data includes a second X-axis coordinate value and a second Y-axis coordinate value of each second lane edge shape point in the target coordinate system; A projection point determination unit, used to determine a first projection point from the vehicle to the first lane edge and a second projection point from the vehicle to the second lane edge; a shape point distance determination unit, configured to determine a first shape point distance between each shape point of the first lane edge line and the first projection point, and a second shape point distance between each shape point of the second lane edge line and the second projection point; a quintic fitting equation construction unit, configured to respectively construct a first quintic fitting equation and a second quintic fitting equation with the first shape point distance as an independent variable, the first X-axis coordinate value and the first Y-axis coordinate value as dependent variables, and respectively construct a third quintic fitting equation and a fourth quintic fitting equation with the second shape point distance as an independent variable, the second X-axis coordinate value and the second Y-axis coordinate value as dependent variables; A vehicle heading angle determination unit is used to determine a first angle of the vehicle based on the first fifth-order fitting equation and the second fifth-order fitting equation, determine a second angle of the vehicle based on the third fifth-order fitting equation and the fourth fifth-order fitting equation, and determine a vehicle heading angle based on the first angle and the second angle.

9. A vehicle, characterized in that: comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the vehicle heading angle determination method described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the vehicle heading angle determination method described in any one of claims 1 to 7.

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