High-precision map lane line optimization method and device, electronic equipment and storage medium

Abstract

The application discloses a high-precision map lane line optimization method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a height parameter value of a vehicle relative to any position on a road surface according to a feature parameter; constructing a grid-based geodetic surface model according to the height parameter value of the vehicle relative to any position on the road surface, wherein the geodetic surface model comprises position points of a plurality of height parameter values; obtaining position information of a target ground element according to the geodetic surface model, and determining the spatial position of the high-precision map lane line calculated by the image acquisition device in the vehicle after optimization. The beneficial effect is that the accuracy of the spatial position of the lane line is improved.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and in particular to a method, device, electronic device, and storage medium for optimizing lane lines in a high-precision map. Background Art

[0002] High-precision maps are typically machine-oriented maps for vehicle use. They not only have highly accurate coordinates but also accurate road shapes and detailed information for each lane. Monocular image acquisition devices on vehicles capture images from the front of the vehicle.

[0003] Conventional technologies typically assume the road surface is completely flat when calculating the spatial position of lane markings using monocular image acquisition devices. However, since the Earth is a curved surface, the actual road surface is also curved; some roads are also curved or non-planar. These factors can lead to significant errors in the spatial position of lane markings in HD maps, especially for elements within lanes that are far from the camera. Summary of the Invention

[0004] The embodiments of the present application provide a method, device, electronic device, and storage medium for optimizing lane lines in high-precision maps to accurately calculate the spatial position of lane lines, thereby achieving self-improvement of lane lines in high-precision maps.

[0005] The embodiments of this application adopt the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a method for optimizing high-precision map lane lines, wherein at least an RTK positioning module is included on the vehicle, and the RTK positioning module is used to obtain the current position longitude and latitude information of the vehicle and the characteristic parameters corresponding to the current position longitude and latitude information, and the characteristic parameters are used to characterize the height parameter value. The method includes: determining the height parameter value of the vehicle relative to any position on the road surface based on the characteristic parameters; constructing a grid-based earth surface model based on the height parameter value of the vehicle relative to any position on the road surface, wherein the earth surface model includes position points of multiple height parameter values; obtaining the position information of the target ground element based on the earth surface model, and calculating the spatial position of the optimized high-precision map lane line based on the image acquisition device in the vehicle.

[0007] In a second aspect, the embodiments of the present application also provide a high-precision map lane line optimization device, wherein at least an RTK positioning module is included on a vehicle, the current position latitude and longitude information of the vehicle and feature parameters corresponding to the current position latitude and longitude information are obtained by the RTK positioning module, the feature parameters are used to represent height parameter values, the device comprises: a feature determination module, configured to determine the height parameter values of the vehicle relative to any position on the road surface according to the feature parameters; a construction module, configured to construct a grid-based geodetic surface model according to the height parameter values of the vehicle relative to any position on the road surface, wherein the geodetic surface model comprises a plurality of position points of height parameter values; and a position determination module, configured to obtain the position information of a target ground element according to the geodetic surface model, and calculate the spatial position of the optimized high-precision map lane line based on an image acquisition device in the vehicle.

[0008] In a third aspect, the embodiments of the present application also provide an electronic device, comprising: a processor; and a memory arranged to store computer executable instructions, which, when executed, cause the processor to perform any of the preceding methods.

[0009] In a fourth aspect, the embodiments of the present application also provide a computer readable storage medium storing one or more programs, which, when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform any of the preceding methods.

[0010] The above at least one technical scheme adopted by the embodiments of the present application can achieve the following beneficial effects:

[0011] The current position latitude and longitude information of the vehicle and the feature parameters corresponding to the current position latitude and longitude information are obtained by the RTK positioning module, and the geodetic surface model is constructed by the data obtained during the driving of the vehicle, so that the position of the lane line in space is calculated more accurately. BRIEF DESCRIPTION OF DRAWINGS

[0012] The accompanying drawings, which are included to provide a further understanding of the present application, constitute a part of the present application, the illustrative embodiments of the present application and the description thereof serve to explain the present application, and do not constitute an improper limitation on the present application. In the drawings:

[0013] Figure 1 It is a hardware structure schematic diagram of the high-precision map lane line optimization method in the embodiments of the present application;

[0014] Figure 2 It is a high-precision map lane line optimization method flowchart schematic diagram in the embodiments of the present application;

[0015] Figure 3A schematic diagram of a device structure for optimizing a lane line of a high-definition map in an embodiment of the present application

[0016] Figure 4 A schematic diagram of a collected image in front of a vehicle in a method for optimizing a lane line of a high-definition map in an embodiment of the present application

[0017] Figure 5 A schematic diagram of an interpolation processing method in an embodiment of the present application

[0018] Figure 6 A schematic diagram of a structure of an electronic device in an embodiment of the present application DETAILED DESCRIPTION

[0019] To make the objectives, technical solutions, and advantages of the present application clearer, the following will clearly and completely describe the technical solutions of the present application in conjunction with specific embodiments of the present application and corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0020] The following will describe the technical solutions provided by the embodiments of the present application in detail in conjunction with the drawings.

[0021] As shown in Figure 1 , a schematic diagram of a hardware structure in a method for optimizing a lane line of a high-definition map in an embodiment of the present application is provided, mainly including a vehicle 200, an RTK positioning module 100, and a road 300. The RTK positioning module 100 usually has a coordinate position of XYZ axes, and can be installed on the vehicle 200 according to the coordinate position in the RTK positioning module 100. The vehicle 200 travels on different lanes of the road 300, and collects images in front of the vehicle during the travel through an image acquisition device on the vehicle. In addition, the vehicle can also be a collection vehicle, which is not specifically limited in the present application. The vehicle 200 can pre-load a high-definition map, and the lane line in the high-definition map can be self-improved to obtain more accurate position information.

[0022] It can be understood that the vehicle can be an autonomous vehicle or a vehicle without autonomous driving function. In the embodiments of the present application, an autonomous vehicle is taken as an example for detailed description.

[0023] In an actual business scenario, when the vehicle collects road data through the image acquisition device, it usually travels on different lanes for multiple times. As shown in Figure 4 , during the travel of the vehicle on the lane, the RTK positioning module collects height parameters and the like in the lateral and longitudinal directions.

[0024] The embodiment one of the application provides a high-precision map lane line optimization method, wherein at least an RTK positioning module is included on a vehicle, current position latitude and longitude information of the vehicle and feature parameters corresponding to the current position latitude and longitude information are acquired through the RTK positioning module, and the feature parameters are used to represent a height parameter value, such as Figure 2 As shown in the figure, the method comprises the following steps S210 to S230:

[0025] Step S210, according to the feature parameters, determining the height parameter value of the vehicle relative to any position on the road surface;

[0026] Step S220, according to the height parameter value of the vehicle relative to any position on the road surface, constructing a grid-based geodetic surface model, wherein the geodetic surface model comprises a plurality of position points of height parameter values;

[0027] Step S230, according to the geodetic surface model, obtaining position information of a target ground element, and based on an image acquisition device in the vehicle, calculating a spatial position of an optimized high-precision map lane line.

[0028] Through the above steps, the current position latitude and longitude information of the vehicle and the feature parameters corresponding to the current position latitude and longitude information are acquired through the RTK positioning module, and a geodetic surface model is constructed through the data acquired during the driving of the vehicle, so that a more accurate spatial position of the lane line is calculated.

[0029] Before the above step S210 is executed, at least an RTK positioning module is included on the vehicle, and the current position latitude and longitude information of the vehicle and the feature parameters corresponding to the current position latitude and longitude information are acquired through the RTK positioning module, and the feature parameters are used to represent the height parameter value. When the RTK positioning module passes through the road, an accurate position, i.e. latitude and longitude information, is obtained. Further, through the RTK positioning module (device), the real-time current position latitude and longitude information, the height parameter value and the like of the vehicle can be obtained.

[0030] In the above step S210, according to the feature parameters, i.e. the height parameter value, the height parameter value of the vehicle relative to any position on the road surface is determined.

[0031] In the above step S220, according to the height parameter value of the vehicle relative to any position on the road surface (usually the vehicle is driven in this way, although there are offset cases), a grid-based geodetic surface model is constructed. For the height value of each position, after a certain uniformization processing, a grid-shaped geodetic surface model composed of a plurality of height parameter values is formed.

[0032] In step S230, the position information of the target ground element is obtained according to the geodesic surface model, and the spatial position of the optimized high-definition map lane line calculated based on the image acquisition device in the vehicle is determined.

[0033] It can be understood that, after the position information of the target ground element is obtained according to the geodesic surface model, the spatial position of the optimized high-definition map lane line calculated based on the image acquisition device in the vehicle is determined, that is, the optimized lane line realizes a self-improvement process, thereby determining a more accurate position.

[0034] In a specific embodiment, the position information of the target ground element is obtained according to the geodesic surface model, and the spatial position of the optimized high-definition map lane line calculated based on the image acquisition device in the vehicle is determined, including: based on the pixel coordinates P uv of any spatial point on the image and the position information of the target ground element obtained from the geodesic surface model, wherein P is the spatial coordinates of the spatial point in the vehicle coordinate system, CamRCar is the rotation transformation relationship between the image acquisition device coordinate system and the vehicle coordinate system, d is the depth value of the spatial point in the image acquisition device coordinate system, K is the intrinsic matrix of the image acquisition device, the position information of the target ground element is (x, y, z), and the geodesic surface model is y=f(x, z); the spatial position of the optimized high-definition map lane line calculated based on the image acquisition device in the vehicle is determined according to the position information of the target ground element.

[0035] In the formula P uv =K×CamRCar×P / d, the CamRCar is the rotation transformation relationship between the image acquisition device coordinate system and the vehicle coordinate system, which can be obtained by the extrinsic parameters of the image acquisition device, and the d is the depth value of the spatial point in the image acquisition device coordinate system, which is known. The K is the intrinsic matrix of the image acquisition device. The P is the spatial coordinates (x, y, z) of the spatial point in the vehicle coordinate system, which is the parameter to be solved.

[0036] In the previous scheme, by assuming that the road surface is a plane, it is equivalent to assuming that all points on the road surface have the same height value, that is, P(x, h, z). Assuming that the road surface is a plane can simplify the calculation, but when the curvature of the road surface becomes larger, the error of the calculation result will become larger. Therefore, based on the geodesic surface model y=f(x, z) and P uv =K×CamRCar×P / d, a more accurate lane line coordinate can be solved.

[0037] Based on the geodetic surface model is y = f (x, z) characterized the relationship between the three, and y value is real-time changes or say in different lane driving height value will change, so compared to the height value are all as the same (h = 0) case, the lane line position determination result will be more accurate.

[0038] At the same time, it is necessary to collect positioning for each lane, considering that each lane has lane lines.

[0039] So the formula P uv = K x CamRCar x P / d, the space coordinates of a certain lane line point, only x, z, d three unknowns, according to the position information of the target ground element, determine the optimized high-precision map lane line space position calculated based on the image acquisition device in the vehicle.

[0040] Further, the formula P uv = K x CamRCar x P / d can be decomposed into three equations, which can be solved for the three quantities, and then the latitude and longitude position of the point is inferred through the Yaw angle in the RTK positioning module when the target frame is collected by the image acquisition device.

[0041] In an embodiment of the present application, the RTK positioning module obtains the current position information of the vehicle and the characteristic parameters corresponding to the current position information, further comprising: the RTK positioning module respectively obtains the current position information of the vehicle on different lanes and the characteristic parameters corresponding to the current position information, and the frequency of acquisition includes multiple times.

[0042] When a vehicle collects a section of road data, it usually drives in different lanes several times, such as Figure 5 As shown, the line represents the lane line, and the dot represents the RTK trajectory point collected by the vehicle during driving in two lanes. It should be noted that different lanes must be collected, and the more times collected, the more accurate the optimization result of the lane line position.

[0043] In an embodiment of the present application, the geodetic surface model is constructed according to the height parameter value of the vehicle relative to any position on the road surface, wherein the geodetic surface model includes a plurality of position points of height parameter values, comprising: establishing the geodetic surface model according to the height parameter value and the position parameter of the target position point on the road surface corresponding to the height parameter value.

[0044] In a specific implementation, the established earth surface model is based on a grid, which is referred to as a map data grid. According to the height parameters y and the position parameters of the target position points (x, z) on the road surface corresponding to the height parameter values, a function relationship between y and x and z is established.

[0045] In an embodiment of the present application, the height parameter value of the vehicle relative to any position on the road surface is determined according to the feature parameters, which includes determining the height parameter value of the vehicle relative to any position on the road surface based on the height parameter value of the feature parameters obtained by the RTK positioning module.

[0046] In an embodiment of the present application, the height parameter value of the vehicle relative to any position on the road surface is first determined based on the height parameter value of the feature parameters obtained by the RTK positioning module. Finally, the height parameter value of each position is uniformly processed to form a grid-shaped earth surface model composed of height values. It should be noted that the earth surface model y=f(x, z) represents a function relationship between y and x and z, and this function relationship can be obtained by solving.

[0047] In an embodiment of the present application, the height parameter value of the vehicle relative to any position on the road surface is determined according to the feature parameters, which includes that in a preset condition that the vehicle is attached to the road surface of the current road, the height parameter change value of the vehicle relative to any position on the road surface is consistent with the change of the road surface height; the road surface height of the vehicle relative to any position point on the road surface is calculated to obtain the height parameter values of multiple positions; and the result obtained after the height parameter values of the vehicle relative to multiple positions on the road surface are processed by interpolation is used as the height of all points on the road surface.

[0048] In an embodiment of the present application, the height data of the vehicle can be obtained by the RTK positioning module (device). It is assumed that the vehicle is completely attached to the road surface, that is, in a preset condition that the vehicle is attached to the road surface of the current road, the height parameter change value of the vehicle relative to any position on the road surface is consistent with the change of the road surface height. The road surface height of the vehicle relative to any position point on the road surface is calculated to obtain the height parameter values of multiple positions, and then an interpolation method is used to obtain the height of all points on the road surface, so as to achieve the purpose of modeling the road surface, that is, the height parameter change value of the vehicle relative to any position on the road surface is processed by interpolation and then used as the height of all points on the road surface.

[0049] It can be understood that the interpolation can be bilinear interpolation, bicubic interpolation, or the like, which is not specifically limited in the embodiment of the present application.

[0050] In one embodiment of the present application, the height parameter values of the vehicle relative to a plurality of positions on the road surface are used after interpolation processing as the height of all points in the road surface, including the following specific calculation process of bilinear interpolation:

[0051] As shown in Figure 5 , for the height value of the target point Q(x q ,z q ), at least four data points P1, P2, P3, and P4 collected by RTK are found around the Q point, and their coordinate data are respectively denoted as P i (x i ,y i ,z i ), wherein x and z are horizontal coordinates, and y is the vertical height; according to the linear interpolation method, the point coordinate P q position parameter on the P1P2 line with the z coordinate value of z 12 is calculated; according to the linear interpolation method, the point coordinate P q position parameter on the P3P4 line with the z coordinate value of z 34 is calculated; and the y coordinate of the Q point is obtained according to the calculation results of P 12 and P 34 , and is used as the height.

[0052] In specific implementation, the specific calculation process of bilinear interpolation is as follows:

[0053] To calculate the height value of Q(x q ,z q ), first, four data points P1, P2, P3, and P4 collected by RTK are found around the Q point, and their coordinate data are respectively denoted as P i (x i ,y i ,z i ), wherein x and z are horizontal coordinates, and y is the vertical height.

[0054] a. The point coordinate P q on the P1P2 line with the z coordinate value of z 12 is calculated according to the linear interpolation method:

[0055] k 12 =(z1–z q ) / (z1-z2)

[0056] x 12 =x1*k 12 +x2*(1–k 12 )

[0057] y 12 =y1*k 12 +y2*(1–k12 )

[0058] then P 12 (x 12 ,y 12 ,z q ) can be found.

[0059] b. Similarly, the z coordinate value of the point on the P3P4 line is calculated as z q .

[0060] k 34 = (z3–z q ) / (z3-z4)

[0061] x 34 = x3*k 34 +x4*(1–k 34 )

[0062] y 34 = y3*k 34 +y4*(1–k 34 )

[0063] P 34 (x 34 ,y 34 ,z q ) can be found.

[0064] c. Using the same principle as described above, the y coordinate (height) of point Q can be found.

[0065] k = (x q – x 12 ) / (x 34 – x 12 )

[0066] y q = y 12 *k+y 34 *(1-k)。

[0067] The high-precision map lane line optimization device provided in the embodiment of the application, wherein at least an RTK positioning module is included on a vehicle, current position latitude and longitude information of the vehicle is obtained through the RTK positioning module, and a feature parameter corresponding to the current position latitude and longitude information is obtained, the feature parameter is used to represent a height parameter value, such as shown in the following formula: Figure 3 The device comprises:

[0068] A determination module 310 is configured to determine a height parameter value of the vehicle relative to any position on a road surface according to the feature parameter.

[0069] The constructing module 320 is configured to construct a grid-based earth surface model according to the height parameter value of the vehicle relative to any position on the road surface, wherein the earth surface model comprises position points of the height parameter value.

[0070] The position determining module 330 is configured to obtain position information of a target ground element according to the earth surface model, and calculate the spatial position of the optimized high-definition map lane line based on the image acquisition device in the vehicle.

[0071] In the determining module 310 in the embodiment of the application, the height parameter value of the vehicle relative to any position on the road surface is determined according to the feature parameter, i.e., the height parameter value. Meanwhile, the height value of each lane center point is obtained.

[0072] In the constructing module 320 in the embodiment of the application, the grid-based earth surface model is constructed according to the height parameter value of the vehicle relative to any position on the road surface. For the height value of each position, a certain uniformization processing is performed to form a grid-shaped earth surface model composed of multiple height parameter values.

[0073] In the position determining module 330 in the embodiment of the application, the position information of the target ground element is obtained according to the earth surface model, and the spatial position of the optimized high-definition map lane line calculated based on the image acquisition device in the vehicle is determined.

[0074] It can be understood that after the position information of multiple target ground elements is obtained according to the earth surface model, the spatial position of the optimized high-definition map lane line calculated based on the image acquisition device in the vehicle is determined, that is, the optimized lane line realizes a self-perfecting process, so that the position is more accurate.

[0075] In a specific implementation, the position information of the target ground element is obtained according to the earth surface model, and the spatial position of the optimized high-definition map lane line calculated based on the image acquisition device in the vehicle is determined, which comprises: based on the pixel coordinates P of any spatial point on the image and the position information of the target ground element obtained according to the earth surface model, wherein P is the spatial coordinates of the spatial point in the vehicle coordinate system, CamRCar is the rotation transformation relationship between the image acquisition device coordinate system and the vehicle coordinate system, d is the depth value of the spatial point in the image acquisition device coordinate system, K is the intrinsic matrix of the image acquisition device, the position information of the target ground element is (x, y, z), and the earth surface model is y=f(x, z); the spatial position of the optimized high-definition map lane line calculated based on the image acquisition device in the vehicle is determined according to the position information of the target ground element. uv ​

[0076] In the formula P uv = K x CamRCar x P / d, the CamRCar is the rotation transformation relationship between the image acquisition device coordinate system and the vehicle coordinate system, which can be obtained by the image acquisition device external parameter, and the d is the depth value of the space point in the image acquisition device coordinate system, which is known. The K is the internal parameter matrix of the image acquisition device. The P is the space coordinate (x, y, z) of the space point in the vehicle coordinate system, which is the parameter to be solved.

[0077] In the previous scheme, by assuming that the road surface is a plane, it is equivalent to assuming that all points on the road surface have the same height value, that is, P(x, h, z). Assuming that the road surface is a plane can simplify the calculation, but when the curvature of the road surface becomes larger, the error of the calculation result will become larger. Therefore, based on the geoid model y = f(x, z), combined with P uv = K x CamRCar x P / d, a more accurate lane line coordinate can be solved.

[0078] Therefore, in the formula P uv = K x CamRCar x P / d, to obtain the space coordinate of a certain lane line point, only three unknown quantities x, z, and d are required, that is, according to the position information of the target ground element, the spatial position of the high-precision map lane line calculated based on the image acquisition device in the vehicle is determined.

[0079] Further, the formula P uv = K x CamRCar x P / d can be decomposed into three equations, which can solve the three quantities, and then the latitude and longitude positions of the point are inferred through the Yaw angle in the RTK positioning module of the target frame position acquired by the image acquisition device.

[0080] It can be understood that the high-precision map lane line optimization device described above can realize each step of the high-precision map lane line optimization provided in the foregoing embodiments, and the related explanations about the high-precision map lane line optimization are all applicable to the high-precision map lane line optimization device, which will not be described here.

[0081] Figure 6 is a structural schematic diagram of an electronic device of an embodiment of the present application. Please refer to Figure 6 At the hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The memory can include a memory such as a random-access memory (RAM), and can also include a non-volatile memory such as at least one disk memory. Of course, the electronic device can also include other hardware required by the business.

[0082] The processor, the network interface and the memory can be connected with each other 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, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 6 Only one bidirectional arrow is used to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0083] The memory is used to store programs. Specifically, the program can include program code including computer operation instructions. The memory can include memory and non-volatile memory, and provide instructions and data for the processor.

[0084] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs, and forms the high-precision map lane line optimization device at the logical level. The processor executes the program stored in the memory, and is specifically used for executing the following operations:

[0085] At least an RTK positioning module is included on the vehicle, and the current position latitude and longitude information of the vehicle and the characteristic parameters corresponding to the current position latitude and longitude information are obtained through the RTK positioning module. The characteristic parameters are used to represent the height parameter value;

[0086] According to the characteristic parameters, the height parameter value of the vehicle relative to any position on the road surface is determined;

[0087] According to the height parameter value of the vehicle relative to any position on the road surface, a grid-based geodesic surface model is constructed, wherein the geodesic surface model includes a plurality of position points of height parameter values;

[0088] According to the geodesic surface model, the position information of the target ground element is obtained, and the spatial position of the high-precision map lane line calculated by the image acquisition device in the vehicle is determined.

[0089] The above as described in the present application Figure 2The method performed by the high-precision map lane line optimization device disclosed in the embodiment can be applied to a processor or implemented by the processor. The processor can be an integrated circuit chip having a signal processing capability. In the implementation, each step of the above method can be completed by integrated logic circuits of hardware in the processor or instructions in the form of software. The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; or 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. Each method, step and logic block disclosed in the embodiment of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in combination with the embodiment of the present application can be directly embodied as a hardware coding processor for execution, or a combination of hardware and software modules in the coding processor for execution. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register or other mature storage media in the art. The storage medium is located in the memory, and the processor reads information in the memory and combines the hardware to complete the steps of the above method.

[0090] The electronic device can also execute Figure 2 the method performed by the high-precision map lane line optimization device, and implement the high-precision map lane line optimization method in Figure 2 the function of the embodiment disclosed in the embodiment. The embodiment of the present application will not be repeated here.

[0091] The embodiment of the present application also proposes a computer readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by an electronic device including a plurality of applications, can cause the electronic device to execute Figure 2 the method performed by the high-precision map lane line optimization device in the embodiment disclosed in the embodiment, and specifically for executing

[0092] The vehicle includes at least an RTK positioning module, and the current position latitude and longitude information of the vehicle and the characteristic parameters corresponding to the current position latitude and longitude information are obtained through the RTK positioning module. The characteristic parameters are used to represent the height parameter value.

[0093] determine a height parameter value of the vehicle relative to any position on the road surface according to the characteristic parameter;

[0094] construct a grid-based earth surface model according to the height parameter value of the vehicle relative to any position on the road surface, wherein the earth surface model comprises a plurality of position points of the height parameter value;

[0095] obtain position information of a target ground element according to the earth surface model, and determine an optimized spatial position of a lane line of a high-definition map calculated by the image acquisition device in the vehicle.

[0096] Those skilled in the art will understand that embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can 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-ROMs, optical storage devices, etc.) containing computer usable program code.

[0097] The present application is described in reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as combinations of flows and / or blocks in the flowcharts and / or block diagrams, 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 apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce an apparatus that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in the flowchart

[0098] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction means that implement the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for performing the functions specified in the flowchart

[0099] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide a process for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocksFigure 1 steps of a function specified in one or more blocks.

[0100] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0101] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory, non-volatile memory, such as read-only memory (ROM), EPROM, and / or flash memory, etc. The memory is an example of computer readable media.

[0102] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as 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 disc read-only memory (CD-ROM), digital versatile discs (DVDs) or other optical storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0103] It should also be noted that the terms "comprising," "including," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements recited, but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without limitation, an element preceded by "comprises a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the recited element.

[0104] Those skilled in the art will appreciate that embodiments of the present application can be devised for a method, a system, or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer readable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code.

[0105] The above merely provides an example of the present application, but is not intended to limit the present application. The present application can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the scope of claims of the present application.

Claims

1. A method for optimizing lane lines in high-precision maps, wherein: At least an RTK positioning module is included on the vehicle, and the current position longitude and latitude information of the vehicle and the characteristic parameters corresponding to the current position longitude and latitude information are obtained by the RTK positioning module. The obtaining of the current position longitude and latitude information of the vehicle and the characteristic parameters corresponding to the current position longitude and latitude information by the RTK positioning module further includes: obtaining the current position information of the vehicle on different lanes and the characteristic parameters corresponding to the current position information by the RTK positioning module, and the frequency of the obtaining includes multiple times; The characteristic parameter is used to characterize the height parameter value, and the method includes: Determining a height parameter value of the vehicle relative to any position on the road surface based on the characteristic parameter; Determining a height parameter value of the vehicle relative to any position on the road surface according to the characteristic parameter, comprising: determining a height parameter value of the vehicle relative to any position on the road surface based on the height parameter value of the characteristic parameter obtained by an RTK positioning module; Determining the height parameter value of the vehicle relative to any position on the road surface based on the characteristic parameter includes: in a case where the vehicle is pre-set to be in contact with the road surface of the current road, a change in the height parameter value of the vehicle relative to any position on the road surface is consistent with a change in the road surface height; calculating the road surface height of the vehicle relative to any point on the road surface to obtain height parameter values ​​for multiple positions; and interpolating the height parameter values ​​of the vehicle relative to the multiple positions on the road surface to obtain a result as the height of all points on the road surface; Constructing a grid-based earth surface model according to the height parameter value of the vehicle relative to any position on the road surface, wherein the earth surface model includes position points of multiple height parameter values; The method of constructing a grid-based earth surface model according to the height parameter value of the vehicle relative to any position on the road surface, wherein the earth surface model includes position points of multiple height parameter values, including: Establishing the earth surface model according to the height parameter value and the position parameter of the target position point on the road surface corresponding to the height parameter value; The position information of the target ground element is obtained according to the earth surface model, and the spatial position of the lane line of the high-precision map is obtained based on the image acquisition device in the vehicle.

2. The method according to claim 1, wherein: Obtaining the position information of the target ground element according to the earth surface model and determining the optimized spatial position of the lane line of the high-precision map calculated by the image acquisition device in the vehicle includes: Based on the pixel coordinates P of any spatial point on the image uv =K×CamRCar×P / d and the earth surface model to obtain the position information of the target ground element, wherein P is the spatial coordinate of the spatial point in the vehicle coordinate system, CamRCar is the rotation transformation relationship between the image acquisition device coordinate system and the vehicle coordinate system, d is the depth value of the spatial point in the image acquisition device coordinate system, K is the intrinsic parameter matrix of the image acquisition device, the position information of the target ground element is (x, y, z) and the earth surface model is y=f(x, z); Based on the position information of the target ground element, the optimized spatial position of the high-precision map lane line calculated by the image acquisition device in the vehicle is determined.

3. The method according to claim 1, wherein The height parameter values ​​of the vehicle relative to multiple positions on the road surface are interpolated to obtain the heights of all points on the road surface, including: For the target point Q(x q ,z q ), find at least 4 RTK-collected data points P1, P2, P3, and P4 around point Q, and record their coordinate data as P i (x i ,y i ,z i ), where x and z are horizontal coordinates and y is the vertical height; According to the linear interpolation method, the z coordinate value on the P1P2 line is calculated as z q The coordinates of point P 12 Positional parameters; According to the linear interpolation method, the z coordinate value on the P3P4 line is calculated as z q The coordinates of point P 34 Positional parameters; According to the P 12 and P 34 The calculated result is the y coordinate of point Q and used as the height.

4. A high-precision map lane line optimization device, wherein: At least an RTK positioning module is included on the vehicle, and the current position longitude and latitude information of the vehicle and the characteristic parameters corresponding to the current position longitude and latitude information are obtained by the RTK positioning module. The method of obtaining the current position longitude and latitude information of the vehicle and the characteristic parameters corresponding to the current position longitude and latitude information by the RTK positioning module further includes: obtaining the current position information of the vehicle on different lanes and the characteristic parameters corresponding to the current position information by the RTK positioning module, and the frequency of obtaining includes multiple times; The characteristic parameter is used to characterize the height parameter value, and the device includes: a characteristic determination module, configured to determine a height parameter value of the vehicle relative to any position on the road surface based on the characteristic parameter; Determining a height parameter value of the vehicle relative to any position on the road surface according to the characteristic parameter, comprising: determining a height parameter value of the vehicle relative to any position on the road surface based on the height parameter value of the characteristic parameter obtained by an RTK positioning module; Determining the height parameter value of the vehicle relative to any position on the road surface based on the characteristic parameter includes: in a case where the vehicle is pre-set to be in contact with the road surface of the current road, a change in the height parameter value of the vehicle relative to any position on the road surface is consistent with a change in the road surface height; calculating the road surface height of the vehicle relative to any point on the road surface to obtain height parameter values ​​for multiple positions; and interpolating the height parameter values ​​of the vehicle relative to the multiple positions on the road surface to obtain a result as the height of all points on the road surface; A construction module, configured to construct a grid-based earth surface model according to a height parameter value of the vehicle relative to any position on the road surface, wherein the earth surface model includes position points of a plurality of height parameter values; The method of constructing a grid-based earth surface model according to the height parameter value of the vehicle relative to any position on the road surface, wherein the earth surface model includes position points of multiple height parameter values, including: Establishing the earth surface model according to the height parameter value and the position parameter of the target position point on the road surface corresponding to the height parameter value; The position determination module is used to obtain the position information of the target ground element according to the earth surface model, and calculate the spatial position of the optimized high-precision map lane line based on the image acquisition device in the vehicle.

5. An electronic device comprising: processor; as well as A memory arranged to store computer executable instructions, which when executed cause the processor to perform the method of any one of claims 1 to 3.

6. A computer-readable storage medium storing one or more programs, which, when executed by an electronic device including a plurality of application programs, causes the electronic device to execute the method according to any one of claims 1 to 3.

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