Lane center line processing method, device, equipment and medium

Abstract

The invention discloses a lane center line processing method and device, equipment and a medium, and relates to the technical field of intelligent driving, and the method comprises the steps: obtaining a lane center line equation of a vehicle at a previous moment, and converting the lane center line equation of the vehicle at the previous moment into an equation representation under a coordinate system at a current moment, so as to obtain a first lane center line equation; determining a filter coefficient according to the dispersion degree of the transverse distance change, and adjusting each first lane line feature coefficient of the first lane center line equation according to the filter coefficient to obtain a second lane line feature coefficient; the transverse distance is the distance between the first lane center line equation and the lane center line equation of the vehicle at the current moment; and controlling the vehicle to run by using a second lane center line equation obtained based on the second lane line feature coefficient. Therefore, according to the method, the filtering coefficient is determined through the dispersion degree, different lane center line fluctuation conditions can be dynamically adapted, the lane center line is effectively smoothed, and the jumping phenomenon is reduced to the maximum extent.

Description

Technical Field

[0001] The present invention relates to the field of intelligent driving technology, and in particular to a lane centerline processing method, device, equipment and medium. Background Art

[0002] The current vision-based intelligent driving solutions often cause the calculated lane centerline to jump due to unstable upper-layer perception or rapid changes in road curvature. Smaller jumps may cause the vehicle's driving trajectory to be like a "dragon drawing", giving the driver a poor driving experience; larger jumps will cause the regulatory control module to plan a larger steering wheel angle to control the vehicle, which often causes the driver to panic and may even cause traffic accidents. Therefore, the above problems need to be solved urgently. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a lane centerline processing method, device, equipment and medium, which can determine the filter coefficient by the discrete degree, so as to dynamically adapt to different lane centerline fluctuations, effectively smooth the lane centerline and reduce the jump phenomenon. The specific scheme is as follows:

[0004] In a first aspect, the present application discloses a lane centerline processing method, comprising:

[0005] Obtaining a lane centerline equation of the vehicle at a previous moment, and converting the lane centerline equation at the previous moment into an equation representation in a current moment coordinate system to obtain a first lane centerline equation;

[0006] Determine a filter coefficient according to the discrete degree of the lateral distance change, and adjust each first lane line characteristic coefficient of the first lane center line equation according to the filter coefficient to obtain a second lane line characteristic coefficient; wherein the lateral distance is the distance between the first lane center line equation and the lane center line equation of the vehicle at the current moment;

[0007] The vehicle driving is controlled by using the second lane centerline equation obtained based on the second lane line characteristic coefficient.

[0008] Optionally, determining the filter coefficient according to the discrete degree of the horizontal distance change includes:

[0009] Calculating a lateral distance difference between the first lane centerline equation and the lane centerline equation at the current moment at each sampling point, and calculating a target variance based on the lateral distance difference;

[0010] The filter coefficient is determined according to the relationship between the target variance and the change range of the lane line at the previous and next moments.

[0011] Optionally, determining the filter coefficient according to the relationship between the target variance and the change amplitude of the lane line at the previous and next moments includes:

[0012] When the target variance increases, the filter coefficient increases according to a preset linear function; wherein the target variance is positively correlated with the change amplitude of the lane line at the previous and next moments.

[0013] Optionally, adjusting each first lane line characteristic coefficient of the first lane center line equation according to the filter coefficient to obtain a second lane line characteristic coefficient includes:

[0014] Determine various third lane line characteristic coefficients of the lane center line equation at the current moment;

[0015] Calculate the difference between each of the first lane line characteristic coefficients and the corresponding each of the third lane line characteristic coefficients, and calculate the product value of the filter coefficient and each of the differences;

[0016] The sum of each of the product values ​​and each of the first lane line characteristic coefficients is determined as the second lane line characteristic coefficient.

[0017] Optionally, converting the lane centerline equation at the previous moment into an equation representation in the coordinate system at the current moment to obtain the first lane centerline equation includes:

[0018] Acquire a plurality of first position points from the lane centerline equation at the previous moment; wherein the plurality of first position points are sampling points on the lane centerline equation at the previous moment;

[0019] Converting the plurality of first position points into coordinate representations in the vehicle coordinate system at the current moment to obtain a plurality of second position points;

[0020] Each of the first lane line characteristic coefficients is determined according to the multiple second position points, and an equation constructed based on each of the first lane line characteristic coefficients is determined as the first lane centerline equation.

[0021] Optionally, the acquiring a plurality of first position points from the lane centerline equation at the previous moment includes:

[0022] Performing validity judgment on the lane centerline equation at the previous moment based on a preset judgment rule;

[0023] If the lane centerline equation at the last moment is valid, the multiple first position points are obtained from the lane centerline equation at the last moment.

[0024] Optionally, converting the plurality of first position points into coordinate representations in the vehicle coordinate system at the current moment includes:

[0025] Determine the translation distance and rotation angle between the vehicle coordinate system at the previous moment and the vehicle coordinate system at the current moment according to the driving path of the vehicle from the previous moment to the current moment;

[0026] The plurality of first position points are converted into coordinate representation in the vehicle coordinate system at the current moment through the translation distance and the rotation angle.

[0027] In a second aspect, the present application discloses a lane centerline processing device, comprising:

[0028] An equation conversion module, used to obtain the lane centerline equation of the vehicle at a previous moment, and convert the lane centerline equation at the previous moment into an equation representation in the coordinate system at a current moment, so as to obtain the first lane centerline equation;

[0029] A lane line filtering module, used to determine a filtering coefficient according to the discrete degree of the lateral distance change, and adjust each first lane line characteristic coefficient of the first lane center line equation according to the filtering coefficient to obtain a second lane line characteristic coefficient; wherein the lateral distance is the distance between the first lane center line equation and the lane center line equation of the vehicle at the current moment;

[0030] The vehicle control module is used to control the vehicle driving by using the second lane center line equation obtained based on the second lane line characteristic coefficient.

[0031] In a third aspect, the present application discloses an electronic device, comprising:

[0032] Memory, used to store computer programs;

[0033] A processor is used to execute the computer program to implement the lane centerline processing method disclosed above.

[0034] In a fourth aspect, the present application discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the lane centerline processing method disclosed above is implemented.

[0035] It can be seen that the present application proposes a lane centerline processing method, including: obtaining the lane centerline equation of the vehicle at the previous moment, and converting the lane centerline equation of the previous moment into an equation representation in the coordinate system of the current moment to obtain the first lane centerline equation; determining the filter coefficient according to the discrete degree of the lateral distance change, and adjusting the first lane line characteristic coefficients of the first lane centerline equation according to the filter coefficient to obtain the second lane line characteristic coefficient; the lateral distance is the distance between the first lane centerline equation and the lane centerline equation of the vehicle at the current moment; using the second lane centerline equation obtained based on the second lane line characteristic coefficient to control the vehicle's travel. The present application first obtains the lane centerline equation of the previous moment and converts it to the vehicle coordinate system at the current moment to obtain the first lane centerline equation, and then determines the filter coefficient according to the discrete degree of the lateral distance change between the first and current lane centerline equations, and uses the coefficient to adjust the first lane line characteristic coefficient to obtain the second lane line characteristic coefficient, and then obtains the second lane centerline equation, and finally controls the vehicle's travel according to this equation. Since the degree of discreteness of the lateral distance change reflects the fluctuation of the lane centerline, the greater the degree of discreteness, the more obvious the lane centerline jump. Therefore, by determining the filter coefficient based on the degree of discreteness, it is possible to dynamically adapt to different lane centerline fluctuations, thereby effectively smoothing the lane centerline and minimizing the jump phenomenon. Furthermore, the smoothed lane centerline can provide more stable and reliable reference information for the regulation and control module, significantly improving the safety and comfort of intelligent driving. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0037] Figure 1 A flow chart of a lane centerline processing method disclosed in this application;

[0038] Figure 2 A coordinate transformation schematic diagram disclosed in this application;

[0039] Figure 3 A schematic diagram of lane centerline equations at the previous moment and the current moment disclosed in this application;

[0040] Figure 4 A schematic diagram of lane centerline point selection disclosed in this application;

[0041] Figure 5A schematic diagram of a final lane centerline output disclosed in the present application;

[0042] Figure 6 This is a schematic structural diagram of a lane centerline processing device disclosed in this application;

[0043] Figure 7 This is a structural diagram of an electronic device disclosed in this application. DETAILED DESCRIPTION

[0044] 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 ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] The current vision-based intelligent driving solutions often cause the calculated lane centerline to jump due to unstable upper-layer perception or rapid changes in road curvature. Smaller jumps may cause the vehicle's driving trajectory to be like a "dragon drawing", giving the driver a poor driving experience; larger jumps will cause the regulatory control module to plan a larger steering wheel angle to control the vehicle, which often causes the driver to panic and may even cause traffic accidents. Therefore, the above problems need to be solved urgently.

[0046] To this end, an embodiment of the present application proposes a lane centerline processing solution that can dynamically adapt to different lane centerline fluctuations, effectively smooth the lane centerline, and minimize jump phenomena.

[0047] The present application embodiment discloses a lane centerline processing method, see Figure 1 As shown, including:

[0048] Step S11: Obtain the lane centerline equation of the vehicle at the previous moment, and convert the lane centerline equation at the previous moment into an equation representation in the coordinate system at the current moment to obtain the first lane centerline equation.

[0049] In this embodiment, the lane lines output by the camera are usually expressed in the form of a cubic polynomial. To express, Indicates the lateral distance from the center axis of the vehicle to the lane line. represents the heading angle between the vehicle and the lane line, represents the curvature of the lane line, represents the curvature change rate of the lane line, to Both represent lane characteristic coefficients. For the sake of distinction, the lane centerline equation at the previous moment is expressed in the vehicle coordinate system at the current moment, and the subscripts of the lane characteristic coefficients are added with k1, and the lane centerline equation at the current moment remains unchanged. At this time, the lane centerline equation at the previous moment in the vehicle coordinate system at the current moment can be expressed as ,in, to are all unknown and need to be calculated.

[0050] It should be pointed out that the present embodiment needs to judge the validity of the lane centerline equation at the previous moment based on preset judgment rules. The preset judgment rules include, but are not limited to, evaluating the clarity, integrity, and point cloud density of the image where the lane centerline equation at the previous moment is located. Specifically, an image clarity higher than a set threshold is deemed to meet the clarity requirement. The ratio of the number of lane centerline pixels detected to the theoretical number of pixels is statistically calculated. If the ratio is higher than the threshold, it is deemed to meet the integrity requirement. If the point cloud density is higher than the threshold, it is deemed to meet the density requirement. Furthermore, if the lane centerline equation at the previous moment is valid, the multiple first position points are obtained from the lane centerline equation at the previous moment. Specifically, the effective length of the lane centerline at the previous moment is ViewEnd, and multiple first position points are obtained at equal distances from the lane centerline equation at the previous moment to obtain , , , ,in, , , , , and substitute it into In this case, we get:

[0051] ;

[0052] ;

[0053] ;

[0054] .

[0055] Furthermore, each first lane line characteristic coefficient is determined by mapping the lane center line equation at the previous moment to the position of the vehicle coordinate system at the current moment, and the first lane center line equation is obtained according to each first lane line characteristic coefficient. Specifically, according to the driving path of the vehicle from the previous moment to the current moment, the translation distance and rotation angle between the vehicle coordinate system at the previous moment and the vehicle coordinate system at the current moment are determined, and the multiple first position points are converted into coordinate representations in the vehicle coordinate system at the current moment by the translation distance and the rotation angle to obtain multiple second position points, and then the first lane line characteristic coefficients are determined according to the multiple second position points.

[0056] See also Figure 2 As shown, xoy is the vehicle coordinate system at the previous moment, is the vehicle coordinate system at the current moment, is the result of translating the vehicle coordinate system at the previous moment to the vehicle coordinate system at the current moment. F is a position point in the vehicle coordinate system at the previous moment relative to the vehicle, with coordinates (x, y). At the current moment, when the vehicle moves from point O to When the vehicle moves to a certain arc, the radius R = , (corresponding to the rotation angle), v is the vehicle speed, yawrate is the yaw rate, t is the driving time, and the displacement deviation of the vehicle movement is: , (Corresponding to the translation distance). Establish an auxiliary coordinate system , the position of F in the vehicle coordinate system at the current moment is , . , , , , , therefore, the position of F in the vehicle coordinate system at the current moment is: , It can be understood that F is one of the first position points, and the position of F in the vehicle coordinate system at the current moment is In this way, based on the above method, the present embodiment obtains the coordinate representation of all first position points in the vehicle coordinate system at the current moment, that is, obtains all second position points, and determines the coordinates of all second position points as , , , .

[0057] Substitute the coordinates of all second position points into We can get:

[0058] ;

[0059] ;

[0060] ;

[0061] .

[0062] Written in matrix form:

[0063] ;

[0064] Therefore, the characteristic coefficients of the first lane line are:

[0065] ;

[0066] At this time, the calculation of various first lane line characteristic coefficients is completed, and the equation obtained based on the first lane line characteristic coefficient is determined as the first lane centerline equation.

[0067] Step S12: Determine the filter coefficient according to the discrete degree of the lateral distance change, and adjust the first lane line characteristic coefficients of the first lane centerline equation according to the filter coefficient to obtain the second lane line characteristic coefficient; the lateral distance is the distance between the first lane centerline equation and the lane centerline equation at the current moment.

[0068] See also Figure 3 As shown, is the lane centerline equation of the previous moment expressed in the vehicle coordinate system at the current moment, , y is the lane centerline equation at the current moment, .

[0069] In this embodiment, the lateral distance difference between the first lane centerline equation and the lane centerline equation at the current moment at each sampling point is calculated, and the target variance is calculated based on the lateral distance difference, and then the filter coefficient is determined based on the target variance and the change range of the lane line at the previous and next moments. Among them, the target variance is positively correlated with the change range of the lane line at the previous and next moments, and the target variance is positively correlated with the filter coefficient. That is, when the target variance increases, the filter coefficient increases according to the preset linear function; the target variance is positively correlated with the change range of the lane line at the previous and next moments. The preset linear function can be form.

[0070] Take the longest effective distance between the lane center lines at two moments as the longest preview distance LongPreDist for lane line processing. Assuming that 10 points are sampled at equal distances in this embodiment, the spacing step between adjacent points is Substitute the distance at each sampling point into the lane centerline equation at the two previous and next moments, and calculate the lateral distance from the vehicle to each sampling point on the lane centerline at the two previous and next moments.

[0071] ;

[0072] ;

[0073] in, ,like Figure 4 shown.

[0074] The lateral distance from the vehicle to the center line at the previous moment is expressed as LatDistToLastCenterLine, and the lateral distance to the center line at the current moment is expressed as LatDistToCurrentLine. The lateral distance difference LatDistError from the lane line at the previous moment to the lane line at the current moment at each sampling point is:

[0075] ;

[0076] Then the average value LatDistErrorAverage of the lateral distance difference LatDistError from the centerline of the lane at the previous moment to the centerline of the lane at the current moment at all sampling points is:

[0077] ;

[0078] Then the target variance LatDistErrorVariance of the lateral distance LatDistError from the centerline of the lane at the previous moment to the centerline of the lane at the current moment at all sampling points is:

[0079] ;

[0080] The smaller the variance, the less obvious the change of the center line of the current lane. Conversely, the larger the variance, the greater the change of the center line of the lane between the previous and next moments. Therefore, this embodiment designs a method for adjusting the filter coefficient of the current lane center line according to the size of the variance of the lateral distance of the center line between the previous and next moments, as shown in Table 1 below. The first row in Table 1 represents the target variance of the lateral distance of the center line between the current two moments, and the second row in Table 1 represents the adopted filter coefficient. In Table 1, a=1, b=0.

[0081] Table 1

[0082]

[0083] After obtaining the filter coefficient, determine the third lane line characteristic coefficients of the lane centerline equation at the current moment, calculate the difference between the second lane line characteristic coefficients and the corresponding third lane line characteristic coefficients, calculate the product of the filter coefficient and the difference, and then determine the sum of the product values ​​and the first lane line characteristic coefficients as the second lane line characteristic coefficient. The second lane line characteristic coefficient finally output , , , for:

[0084] ;

[0085] ;

[0086] ;

[0087] ;

[0088] in, to Represents the characteristic coefficients of the third lane line, to Represents the characteristic coefficients of each first lane line.

[0089] Step S13: Using the second lane centerline equation obtained based on the second lane line characteristic coefficient to control vehicle travel.

[0090] See also Figure 5 , yend represents the centerline equation of the second lane obtained based on the characteristic coefficient of the second lane line. After the centerline equation of the second lane is obtained, the vehicle driving is controlled based on the centerline equation of the second lane.

[0091] The following is a detailed description using a specific embodiment:

[0092] In the intelligent driving system, the system will record the lane centerline equation of the previous moment, which describes the position and shape characteristics of the lane centerline of the previous moment. Since the position and posture of the vehicle are constantly changing during driving, it is necessary to convert the lane centerline equation of the previous moment to the vehicle coordinate system of the current moment. Specifically, the system selects multiple points at equal distances from the lane centerline equation of the previous moment, for example, 4 points are selected, which are located at a certain proportion of the distance from the vehicle (such as 0.25, 0.5, 0.75, and 1 times the effective length ViewEnd of the lane centerline of the previous moment). Then, according to the driving path of the vehicle from the previous moment to the current moment, the translation distance and rotation angle between the vehicle coordinate systems of the two moments are calculated. For example, the translation and rotation parameters are obtained by a specific calculation method based on information such as the vehicle's speed, yaw rate, and driving time. Using these parameters, the selected points of the previous moment are converted to the vehicle coordinate system of the current moment to obtain multiple new points (i.e., the second position points). Finally, according to the coordinate information of these new points, the characteristic coefficients of each first lane line are determined to obtain the first lane centerline equation. This equation can more accurately reflect the position relationship of the lane centerline relative to the vehicle at the current moment.

[0093] Further, the filter coefficient is determined and the lane line characteristic coefficient is adjusted. Specifically, the lateral distance difference between the first lane centerline equation and the lane centerline equation actually detected at the current moment at multiple sampling points is calculated. For example, a longer lane line is selected as the processing range, and 10 points are sampled at equal distances within this range. The lateral distance of the vehicle to each sampling point of the lane centerline at the two previous and next moments is calculated respectively, and then the lateral distance difference between the lane line at the previous moment and the lane line at the current moment is calculated for each sampling point. The lateral distance difference of all sampling points is averaged, and then the target variance is calculated based on the average value. The larger the target variance, the greater the difference between the first lane centerline equation and the lane centerline equation at the current moment, that is, the more obvious the fluctuation of the lane centerline; conversely, the smaller the variance, the less obvious the fluctuation.

[0094] Furthermore, the filter coefficient is determined according to the target variance and the change amplitude of the lane line before and after. The larger the target variance, the larger the filter coefficient; the smaller the target variance, the smaller the filter coefficient. For example, a suitable filter coefficient is selected through a pre-set correspondence table (such as when the target variance is 0.1, the filter coefficient is 0.1; when the target variance is 0.2, the filter coefficient is 0.2, etc.). Determine the third lane line characteristic coefficients of the lane centerline equation at the current moment, calculate the difference between the first lane line characteristic coefficient and the corresponding third lane line characteristic coefficient, multiply each difference by the filter coefficient, and obtain a series of product values. Finally, add the product values ​​to the corresponding first lane line characteristic coefficients to obtain the second lane line characteristic coefficients.

[0095] Finally, the vehicle is controlled. Specifically, the second lane centerline equation is constructed using the obtained second lane line characteristic coefficient. This equation is a more accurate and smooth description of the current lane centerline after filtering. The vehicle control system plans the vehicle's driving path based on the second lane centerline equation. If the vehicle deviates from the second lane centerline, the system will calculate the direction and speed that need to be adjusted to return the vehicle to the ideal driving trajectory, ensuring that the vehicle drives stably and safely in the lane, improving driving comfort and safety, and reducing vehicle driving instability caused by lane centerline jumps.

[0096] The present application indicates the changing trend of the lane centerline at the previous moment and the lane centerline at the current moment by calculating the variance of the lateral deviation between the lane centerline at the previous moment and the lane centerline at the current moment at different longitudinal distances. If the changing trend is small, a small filter coefficient is adopted, and if the changing trend is large, a larger filter is performed to achieve a smooth transition of the lane centerline. In this way, the control end will not generate a large steering wheel angle to pull the vehicle off the track, and it can also give the driver enough reaction time. If the coefficient plans an incorrect angle, the driver can take over the vehicle in time.

[0097] It can be seen that the present application proposes a lane centerline processing method, including: obtaining the lane centerline equation of the vehicle at the previous moment, and converting the lane centerline equation of the previous moment into an equation representation in the coordinate system of the current moment to obtain the first lane centerline equation; determining the filter coefficient according to the discrete degree of the lateral distance change, and adjusting the first lane line characteristic coefficients of the first lane centerline equation according to the filter coefficient to obtain the second lane line characteristic coefficient; the lateral distance is the distance between the first lane centerline equation and the lane centerline equation of the vehicle at the current moment; using the second lane centerline equation obtained based on the second lane line characteristic coefficient to control the vehicle's travel. The present application first obtains the lane centerline equation of the previous moment and converts it to the vehicle coordinate system at the current moment to obtain the first lane centerline equation, and then determines the filter coefficient according to the discrete degree of the lateral distance change between the first and current lane centerline equations, and uses the coefficient to adjust the first lane line characteristic coefficient to obtain the second lane line characteristic coefficient, and then obtains the second lane centerline equation, and finally controls the vehicle's travel according to this equation. Since the degree of discreteness of the lateral distance change reflects the fluctuation of the lane centerline, the greater the degree of discreteness, the more obvious the lane centerline jump. Therefore, by determining the filter coefficient based on the degree of discreteness, it is possible to dynamically adapt to different lane centerline fluctuations, thereby effectively smoothing the lane centerline and minimizing the jump phenomenon. Furthermore, the smoothed lane centerline can provide more stable and reliable reference information for the regulation and control module, significantly improving the safety and comfort of intelligent driving.

[0098] Correspondingly, the embodiment of the present application also discloses a lane centerline processing device, see Figure 6 As shown, the device comprises:

[0099] An equation conversion module 11 is used to obtain the lane centerline equation of the vehicle at the previous moment, and convert the lane centerline equation at the previous moment into an equation representation in the coordinate system at the current moment to obtain a first lane centerline equation;

[0100] A lane line filtering module 12 is used to determine a filtering coefficient according to the discrete degree of the lateral distance change, and adjust the first lane line characteristic coefficients of the first lane center line equation according to the filtering coefficient to obtain a second lane line characteristic coefficient; wherein the lateral distance is the distance between the first lane center line equation and the lane center line equation of the vehicle at the current moment;

[0101] The vehicle control module 13 is used to control the vehicle driving by using the second lane centerline equation obtained based on the second lane line characteristic coefficient.

[0102] Among them, for more specific working processes of the above-mentioned modules, please refer to the corresponding contents disclosed in the aforementioned embodiments, which will not be repeated here.

[0103] It can be seen that the present application proposes a lane centerline processing method, including: obtaining the lane centerline equation of the vehicle at the previous moment, and converting the lane centerline equation of the previous moment into an equation representation in the coordinate system of the current moment to obtain the first lane centerline equation; determining the filter coefficient according to the discrete degree of the lateral distance change, and adjusting the first lane line characteristic coefficients of the first lane centerline equation according to the filter coefficient to obtain the second lane line characteristic coefficient; the lateral distance is the distance between the first lane centerline equation and the lane centerline equation of the vehicle at the current moment; using the second lane centerline equation obtained based on the second lane line characteristic coefficient to control the vehicle's travel. The present application first obtains the lane centerline equation of the previous moment and converts it to the vehicle coordinate system at the current moment to obtain the first lane centerline equation, and then determines the filter coefficient according to the discrete degree of the lateral distance change between the first and current lane centerline equations, and uses the coefficient to adjust the first lane line characteristic coefficient to obtain the second lane line characteristic coefficient, and then obtains the second lane centerline equation, and finally controls the vehicle's travel according to this equation. Since the degree of discreteness of the lateral distance change reflects the fluctuation of the lane centerline, the greater the degree of discreteness, the more obvious the lane centerline jump. Therefore, by determining the filter coefficient based on the degree of discreteness, it is possible to dynamically adapt to different lane centerline fluctuations, thereby effectively smoothing the lane centerline and minimizing the jump phenomenon. Furthermore, the smoothed lane centerline can provide more stable and reliable reference information for the regulation and control module, significantly improving the safety and comfort of intelligent driving.

[0104] Furthermore, an embodiment of the present application also provides an electronic device. Figure 7 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content in the diagram cannot be regarded as any limitation on the scope of use of the present application.

[0105] Figure 7 The present invention provides a schematic diagram of the structure of an electronic device 20 provided in an embodiment of the present application. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a display screen 23, an input / output interface 24, a communication interface 25, a power supply 26, and a communication bus 27. The memory 22 is used to store a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the lane centerline processing method disclosed in any of the aforementioned embodiments. In addition, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0106] In this embodiment, the power supply 26 is used to provide working voltage for each hardware device on the electronic device 20; the communication interface 25 can create a data transmission channel between the electronic device 20 and the external device, and the communication protocol it follows is any communication protocol that can be applied to the technical solution of the present application, and is not specifically limited here; the input and output interface 24 is used to obtain external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs and is not specifically limited here.

[0107] In addition, the memory 22, as a carrier for storing resources, may be a read-only memory, a random access memory, a disk or an optical disk, etc. The resources stored thereon may include a computer program 221, and the storage method may be temporary storage or permanent storage. In addition to including a computer program that can be used to complete the lane centerline processing method executed by the electronic device 20 disclosed in any of the aforementioned embodiments, the computer program 221 may further include a computer program that can be used to complete other specific tasks.

[0108] Furthermore, an embodiment of the present application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the lane centerline processing method disclosed above is implemented.

[0109] For the specific steps of the method, reference may be made to the corresponding contents disclosed in the aforementioned embodiments, which will not be described in detail here.

[0110] The various embodiments in this application are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0111] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0112] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0113] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0114] The above is a detailed introduction to a lane centerline processing method, device, equipment, and storage medium provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, 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 application.

Claims

1. A lane centerline processing method, characterized in that: include: Obtaining a lane centerline equation of the vehicle at a previous moment, and converting the lane centerline equation at the previous moment into an equation representation in a current moment coordinate system to obtain a first lane centerline equation; Determine a filter coefficient according to the discrete degree of the lateral distance change, and adjust each first lane line characteristic coefficient of the first lane center line equation according to the filter coefficient to obtain a second lane line characteristic coefficient; wherein the lateral distance is the distance between the first lane center line equation and the lane center line equation of the vehicle at the current moment; The vehicle driving is controlled by using the second lane centerline equation obtained based on the second lane line characteristic coefficient.

2. The lane centerline processing method according to claim 1, characterized in that: The step of determining the filter coefficient according to the discrete degree of the horizontal distance change includes: Calculating a lateral distance difference between the first lane centerline equation and the lane centerline equation at the current moment at each sampling point, and calculating a target variance based on the lateral distance difference; The filter coefficient is determined according to the relationship between the target variance and the change range of the lane line at the previous and next moments.

3. The lane centerline processing method according to claim 2, characterized in that: Determining the filter coefficient according to the relationship between the target variance and the change range of the lane line at the previous and next moments includes: When the target variance increases, the filter coefficient increases according to a preset linear function; wherein the target variance is positively correlated with the change amplitude of the lane line at the previous and next moments.

4. The lane centerline processing method according to claim 1, characterized in that: The adjusting each first lane line characteristic coefficient of the first lane center line equation according to the filter coefficient to obtain the second lane line characteristic coefficient includes: Determine various third lane line characteristic coefficients of the lane center line equation at the current moment; Calculate the difference between each of the first lane line characteristic coefficients and the corresponding each of the third lane line characteristic coefficients, and calculate the product value of the filter coefficient and each of the differences; The sum of each of the product values ​​and each of the first lane line characteristic coefficients is determined as the second lane line characteristic coefficient.

5. The lane centerline processing method according to any one of claims 1 to 4, characterized in that: The converting the lane centerline equation at the previous moment into an equation representation in the coordinate system at the current moment to obtain the first lane centerline equation includes: Acquire a plurality of first position points from the lane centerline equation at the previous moment; wherein the plurality of first position points are sampling points on the lane centerline equation at the previous moment; Converting the plurality of first position points into coordinate representations in the vehicle coordinate system at the current moment to obtain a plurality of second position points; Each of the first lane line characteristic coefficients is determined according to the multiple second position points, and an equation constructed based on each of the first lane line characteristic coefficients is determined as the first lane centerline equation.

6. The lane centerline processing method according to claim 5, characterized in that: The obtaining of a plurality of first position points from the lane centerline equation at the previous moment includes: Performing validity judgment on the lane centerline equation at the previous moment based on a preset judgment rule; If the lane centerline equation at the last moment is valid, the multiple first position points are obtained from the lane centerline equation at the last moment.

7. The lane centerline processing method according to claim 5, characterized in that: The step of converting the plurality of first position points into coordinate representations in the vehicle coordinate system at the current moment includes: Determine the translation distance and rotation angle between the vehicle coordinate system at the previous moment and the vehicle coordinate system at the current moment according to the driving path of the vehicle from the previous moment to the current moment; The plurality of first position points are converted into coordinate representation in the vehicle coordinate system at the current moment through the translation distance and the rotation angle.

8. A lane centerline processing device, characterized in that: include: An equation conversion module, used to obtain the lane centerline equation of the vehicle at a previous moment, and convert the lane centerline equation at the previous moment into an equation representation in the coordinate system at a current moment, so as to obtain the first lane centerline equation; A lane line filtering module, used to determine a filtering coefficient according to the discrete degree of the lateral distance change, and adjust each first lane line characteristic coefficient of the first lane center line equation according to the filtering coefficient to obtain a second lane line characteristic coefficient; wherein the lateral distance is the distance between the first lane center line equation and the lane center line equation of the vehicle at the current moment; The vehicle control module is used to control the vehicle driving by using the second lane centerline equation obtained based on the second lane line characteristic coefficient.

9. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the lane centerline processing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store a computer program; wherein, when the computer program is executed by a processor, the lane centerline processing method as described in any one of claims 1 to 7 is implemented.

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